From a35fddb7784be056b8ac2b956dec9ee69549868e Mon Sep 17 00:00:00 2001 From: "Benjamin T. Vincent" Date: Sun, 24 Jan 2021 16:43:29 +0000 Subject: [PATCH 1/8] create truncated regression example --- .../GLM-truncated-regression.ipynb | 1089 +++++++++++++++++ 1 file changed, 1089 insertions(+) create mode 100644 examples/generalized_linear_models/GLM-truncated-regression.ipynb diff --git a/examples/generalized_linear_models/GLM-truncated-regression.ipynb b/examples/generalized_linear_models/GLM-truncated-regression.ipynb new file mode 100644 index 000000000..9a34f145f --- /dev/null +++ b/examples/generalized_linear_models/GLM-truncated-regression.ipynb @@ -0,0 +1,1089 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Truncated regression\n", + "\n", + "**Author:** [Ben Vincent](https://github.com/drbenvincent)\n", + "\n", + "The notebook provides an example of how to conduct linear regression when you have a truncated outcome variable. Truncation is a type of missing data problem where you are simply unaware of any data that falls outside of a certain set of bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running on PyMC3 v3.10.0\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import pymc3 as pm\n", + "import arviz as az\n", + "\n", + "print(f\"Running on PyMC3 v{pm.__version__}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "%config InlineBackend.figure_format = 'retina'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For this example of `(x, y)` scatter data, we can describe the truncation process as simply filtering out any data for which our outcome variable `y` falls outside of a set of bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def truncate_y(x, y, bounds):\n", + " keep = (y >= bounds[0]) & (y <= bounds[1])\n", + " return (x[keep], y[keep])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Generate some true (latent) data before any truncation takes place. In the real world, you would not have access to this `(x, y)` data." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "m, c, σ, N = 1, 0, 2, 200\n", + "x = np.random.uniform(-10, 10, N)\n", + "y = np.random.normal(m * x + c, σ)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Rather, in a real world context, you would have access to truncated data, where our outcome variable `y` falls within the bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "bounds = [-5, 5]\n", + "xt, yt = truncate_y(x, y, bounds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can visualise this latent data (in grey) and the remaining truncated data (black) as below." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 614 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 8))\n", + "ax.plot(x, y, '.', c=[0.7, 0.7, 0.7], label=\"all data\")\n", + "ax.plot(xt, yt, '.', c=[0, 0, 0], label=\"truncated data\")\n", + "ax.axhline(bounds[0], c='r', ls='--')\n", + "ax.axhline(bounds[1], c='r', ls='--')\n", + "ax.set(xlabel=\"x\", ylabel=\"y\")\n", + "ax.legend();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Linear regression of truncated data underestimates the slope" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Before we get into truncated regression, it is useful to understand why it is needed. If you haven't guessed already from the plot above, then a regression on the truncated data is likely to underestimate the true regression slope. Let's see that in action." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def linear_regression(x, y):\n", + "\n", + " with pm.Model() as model:\n", + " m = pm.Normal(\"m\", mu=0, sd=1)\n", + " c = pm.Normal(\"c\", mu=0, sd=1)\n", + " σ = pm.HalfNormal(\"σ\", sd=1)\n", + " y_likelihood = pm.Normal(\"y_likelihood\", mu=m*x+c, sd=σ, observed=y)\n", + "\n", + " with model:\n", + " trace = pm.sample()\n", + "\n", + " return model, trace" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", + " warnings.warn(\n", + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [σ, c, m]\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
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\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 12 seconds.\n" + ] + } + ], + "source": [ + "# run the model on the truncated data (xt, yt)\n", + "linear_model, linear_trace = linear_regression(xt, yt)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 296, + "width": 656 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(linear_trace, var_names=['m'], ref_val=m, figsize=(9, 4));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, the posterior of the regression slope `m` is underestimated, by quite lot in this example.\n", + "\n", + "Let's visualise how bad that fit is by plotting the data and posterior predictions." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 623 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "def pp_plot(x, y, trace):\n", + " fig, ax = plt.subplots(figsize=(10, 8))\n", + " # plot data\n", + " ax.plot(x, y, 'k.')\n", + " # plot posterior predicted... samples from posterior\n", + " xi = np.array([np.min(x), np.max(x)])\n", + " n_samples=1000\n", + " for n in range(n_samples):\n", + " y_ppc = xi * trace[\"m\"][n] + trace[\"c\"][n]\n", + " ax.plot(xi, y_ppc, c=\"steelblue\", alpha=0.01, rasterized=True)\n", + " # plot true\n", + " ax.plot(xi, m * xi + c, \"k\", lw=3, label=\"True\")\n", + " # plot bounds\n", + " ax.axhline(bounds[0], c='r', ls='--')\n", + " ax.axhline(bounds[1], c='r', ls='--')\n", + " ax.legend()\n", + " ax.set(xlabel=\"x\", ylabel=\"y\")\n", + " \n", + "pp_plot(xt, yt, linear_trace)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that the degree of estimation bias will depend upon a number of things, including the truncation boundaries and the measurement noise. In some situations with high measurement precision and/or little measurement noise, the estimation bias may not be very large. Otherwise, this could have a negative impact upon your research conclusions." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Truncated regression avoids this underestimate" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Truncated regression solves this problem. By using a truncated normal likelihood distribution we are explicity stating our knowledge about the generative process which gave rise to your dataset. We can impliment a [truncated regression model](https://en.wikipedia.org/wiki/Truncated_regression_model) as below." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def truncated_regression(x, y, bounds):\n", + "\n", + " with pm.Model() as model:\n", + " m = pm.Normal(\"m\", mu=0, sd=1)\n", + " c = pm.Normal(\"c\", mu=0, sd=1)\n", + " σ = pm.HalfNormal(\"σ\", sd=1)\n", + "\n", + " y_likelihood = pm.TruncatedNormal(\n", + " \"y_likelihood\",\n", + " mu=m * x + c,\n", + " sd=σ,\n", + " observed=y,\n", + " lower=bounds[0],\n", + " upper=bounds[1],\n", + " )\n", + " \n", + " with model:\n", + " trace = pm.sample()\n", + "\n", + " return model, trace" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", + " warnings.warn(\n", + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [σ, c, m]\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " \n", + " 100.00% [8000/8000 00:04<00:00 Sampling 4 chains, 0 divergences]\n", + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 13 seconds.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" + ] + } + ], + "source": [ + "# run the model on the truncated data (xt, yt)\n", + "truncated_model, truncated_trace = truncated_regression(xt, yt, bounds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And we can check that the inferences are much better by examining the posterior distribution over our slope parameter `m`." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", + " warnings.warn(\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 296, + "width": 656 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(truncated_trace, var_names=['m'], ref_val=m, figsize=(9, 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And also by doing our graphical posterior predictive checks. Looks good." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 614 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pp_plot(xt, yt, truncated_trace)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Last updated: Sun Jan 24 2021\n", + "\n", + "Python implementation: CPython\n", + "Python version : 3.8.5\n", + "IPython version : 7.19.0\n", + "\n", + "pymc3 : 3.10.0\n", + "matplotlib: 3.3.2\n", + "numpy : 1.19.2\n", + "arviz : 0.11.0\n", + "\n", + "Watermark: 2.1.0\n", + "\n" + ] + } + ], + "source": [ + "%load_ext watermark\n", + "%watermark -n -u -v -iv -w" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From bc3d65921969fcb245e66e474c43f6315515cdb1 Mon Sep 17 00:00:00 2001 From: "Benjamin T. Vincent" Date: Mon, 25 Jan 2021 16:24:38 +0000 Subject: [PATCH 2/8] delete truncated regression example from main branch --- .../GLM-truncated-regression.ipynb | 1089 ----------------- 1 file changed, 1089 deletions(-) delete mode 100644 examples/generalized_linear_models/GLM-truncated-regression.ipynb diff --git a/examples/generalized_linear_models/GLM-truncated-regression.ipynb b/examples/generalized_linear_models/GLM-truncated-regression.ipynb deleted file mode 100644 index 9a34f145f..000000000 --- a/examples/generalized_linear_models/GLM-truncated-regression.ipynb +++ /dev/null @@ -1,1089 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Truncated regression\n", - "\n", - "**Author:** [Ben Vincent](https://github.com/drbenvincent)\n", - "\n", - "The notebook provides an example of how to conduct linear regression when you have a truncated outcome variable. Truncation is a type of missing data problem where you are simply unaware of any data that falls outside of a certain set of bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running on PyMC3 v3.10.0\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import pymc3 as pm\n", - "import arviz as az\n", - "\n", - "print(f\"Running on PyMC3 v{pm.__version__}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%config InlineBackend.figure_format = 'retina'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For this example of `(x, y)` scatter data, we can describe the truncation process as simply filtering out any data for which our outcome variable `y` falls outside of a set of bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def truncate_y(x, y, bounds):\n", - " keep = (y >= bounds[0]) & (y <= bounds[1])\n", - " return (x[keep], y[keep])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Generate some true (latent) data before any truncation takes place. In the real world, you would not have access to this `(x, y)` data." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "m, c, σ, N = 1, 0, 2, 200\n", - "x = np.random.uniform(-10, 10, N)\n", - "y = np.random.normal(m * x + c, σ)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Rather, in a real world context, you would have access to truncated data, where our outcome variable `y` falls within the bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "bounds = [-5, 5]\n", - "xt, yt = truncate_y(x, y, bounds)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can visualise this latent data (in grey) and the remaining truncated data (black) as below." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 614 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 8))\n", - "ax.plot(x, y, '.', c=[0.7, 0.7, 0.7], label=\"all data\")\n", - "ax.plot(xt, yt, '.', c=[0, 0, 0], label=\"truncated data\")\n", - "ax.axhline(bounds[0], c='r', ls='--')\n", - "ax.axhline(bounds[1], c='r', ls='--')\n", - "ax.set(xlabel=\"x\", ylabel=\"y\")\n", - "ax.legend();" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Linear regression of truncated data underestimates the slope" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Before we get into truncated regression, it is useful to understand why it is needed. If you haven't guessed already from the plot above, then a regression on the truncated data is likely to underestimate the true regression slope. Let's see that in action." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "def linear_regression(x, y):\n", - "\n", - " with pm.Model() as model:\n", - " m = pm.Normal(\"m\", mu=0, sd=1)\n", - " c = pm.Normal(\"c\", mu=0, sd=1)\n", - " σ = pm.HalfNormal(\"σ\", sd=1)\n", - " y_likelihood = pm.Normal(\"y_likelihood\", mu=m*x+c, sd=σ, observed=y)\n", - "\n", - " with model:\n", - " trace = pm.sample()\n", - "\n", - " return model, trace" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", - " warnings.warn(\n", - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [σ, c, m]\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
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\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 12 seconds.\n" - ] - } - ], - "source": [ - "# run the model on the truncated data (xt, yt)\n", - "linear_model, linear_trace = linear_regression(xt, yt)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 296, - "width": 656 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(linear_trace, var_names=['m'], ref_val=m, figsize=(9, 4));" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As we can see, the posterior of the regression slope `m` is underestimated, by quite lot in this example.\n", - "\n", - "Let's visualise how bad that fit is by plotting the data and posterior predictions." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 623 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "def pp_plot(x, y, trace):\n", - " fig, ax = plt.subplots(figsize=(10, 8))\n", - " # plot data\n", - " ax.plot(x, y, 'k.')\n", - " # plot posterior predicted... samples from posterior\n", - " xi = np.array([np.min(x), np.max(x)])\n", - " n_samples=1000\n", - " for n in range(n_samples):\n", - " y_ppc = xi * trace[\"m\"][n] + trace[\"c\"][n]\n", - " ax.plot(xi, y_ppc, c=\"steelblue\", alpha=0.01, rasterized=True)\n", - " # plot true\n", - " ax.plot(xi, m * xi + c, \"k\", lw=3, label=\"True\")\n", - " # plot bounds\n", - " ax.axhline(bounds[0], c='r', ls='--')\n", - " ax.axhline(bounds[1], c='r', ls='--')\n", - " ax.legend()\n", - " ax.set(xlabel=\"x\", ylabel=\"y\")\n", - " \n", - "pp_plot(xt, yt, linear_trace)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that the degree of estimation bias will depend upon a number of things, including the truncation boundaries and the measurement noise. In some situations with high measurement precision and/or little measurement noise, the estimation bias may not be very large. Otherwise, this could have a negative impact upon your research conclusions." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Truncated regression avoids this underestimate" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Truncated regression solves this problem. By using a truncated normal likelihood distribution we are explicity stating our knowledge about the generative process which gave rise to your dataset. We can impliment a [truncated regression model](https://en.wikipedia.org/wiki/Truncated_regression_model) as below." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "def truncated_regression(x, y, bounds):\n", - "\n", - " with pm.Model() as model:\n", - " m = pm.Normal(\"m\", mu=0, sd=1)\n", - " c = pm.Normal(\"c\", mu=0, sd=1)\n", - " σ = pm.HalfNormal(\"σ\", sd=1)\n", - "\n", - " y_likelihood = pm.TruncatedNormal(\n", - " \"y_likelihood\",\n", - " mu=m * x + c,\n", - " sd=σ,\n", - " observed=y,\n", - " lower=bounds[0],\n", - " upper=bounds[1],\n", - " )\n", - " \n", - " with model:\n", - " trace = pm.sample()\n", - "\n", - " return model, trace" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", - " warnings.warn(\n", - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [σ, c, m]\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " \n", - " 100.00% [8000/8000 00:04<00:00 Sampling 4 chains, 0 divergences]\n", - "
\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 13 seconds.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" - ] - } - ], - "source": [ - "# run the model on the truncated data (xt, yt)\n", - "truncated_model, truncated_trace = truncated_regression(xt, yt, bounds)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And we can check that the inferences are much better by examining the posterior distribution over our slope parameter `m`." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", - " warnings.warn(\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 296, - "width": 656 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(truncated_trace, var_names=['m'], ref_val=m, figsize=(9, 4))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And also by doing our graphical posterior predictive checks. Looks good." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 614 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pp_plot(xt, yt, truncated_trace)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Last updated: Sun Jan 24 2021\n", - "\n", - "Python implementation: CPython\n", - "Python version : 3.8.5\n", - "IPython version : 7.19.0\n", - "\n", - "pymc3 : 3.10.0\n", - "matplotlib: 3.3.2\n", - "numpy : 1.19.2\n", - "arviz : 0.11.0\n", - "\n", - "Watermark: 2.1.0\n", - "\n" - ] - } - ], - "source": [ - "%load_ext watermark\n", - "%watermark -n -u -v -iv -w" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} From d84d852ef3dca88b243e7a2fdc03826ab404708f Mon Sep 17 00:00:00 2001 From: "Benjamin T. Vincent" Date: Sun, 24 Jan 2021 16:43:29 +0000 Subject: [PATCH 3/8] create truncated regression example --- .../GLM-truncated-regression.ipynb | 1089 +++++++++++++++++ 1 file changed, 1089 insertions(+) create mode 100644 examples/generalized_linear_models/GLM-truncated-regression.ipynb diff --git a/examples/generalized_linear_models/GLM-truncated-regression.ipynb b/examples/generalized_linear_models/GLM-truncated-regression.ipynb new file mode 100644 index 000000000..9a34f145f --- /dev/null +++ b/examples/generalized_linear_models/GLM-truncated-regression.ipynb @@ -0,0 +1,1089 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Truncated regression\n", + "\n", + "**Author:** [Ben Vincent](https://github.com/drbenvincent)\n", + "\n", + "The notebook provides an example of how to conduct linear regression when you have a truncated outcome variable. Truncation is a type of missing data problem where you are simply unaware of any data that falls outside of a certain set of bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running on PyMC3 v3.10.0\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import pymc3 as pm\n", + "import arviz as az\n", + "\n", + "print(f\"Running on PyMC3 v{pm.__version__}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "%config InlineBackend.figure_format = 'retina'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For this example of `(x, y)` scatter data, we can describe the truncation process as simply filtering out any data for which our outcome variable `y` falls outside of a set of bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def truncate_y(x, y, bounds):\n", + " keep = (y >= bounds[0]) & (y <= bounds[1])\n", + " return (x[keep], y[keep])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Generate some true (latent) data before any truncation takes place. In the real world, you would not have access to this `(x, y)` data." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "m, c, σ, N = 1, 0, 2, 200\n", + "x = np.random.uniform(-10, 10, N)\n", + "y = np.random.normal(m * x + c, σ)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Rather, in a real world context, you would have access to truncated data, where our outcome variable `y` falls within the bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "bounds = [-5, 5]\n", + "xt, yt = truncate_y(x, y, bounds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can visualise this latent data (in grey) and the remaining truncated data (black) as below." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 614 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 8))\n", + "ax.plot(x, y, '.', c=[0.7, 0.7, 0.7], label=\"all data\")\n", + "ax.plot(xt, yt, '.', c=[0, 0, 0], label=\"truncated data\")\n", + "ax.axhline(bounds[0], c='r', ls='--')\n", + "ax.axhline(bounds[1], c='r', ls='--')\n", + "ax.set(xlabel=\"x\", ylabel=\"y\")\n", + "ax.legend();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Linear regression of truncated data underestimates the slope" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Before we get into truncated regression, it is useful to understand why it is needed. If you haven't guessed already from the plot above, then a regression on the truncated data is likely to underestimate the true regression slope. Let's see that in action." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def linear_regression(x, y):\n", + "\n", + " with pm.Model() as model:\n", + " m = pm.Normal(\"m\", mu=0, sd=1)\n", + " c = pm.Normal(\"c\", mu=0, sd=1)\n", + " σ = pm.HalfNormal(\"σ\", sd=1)\n", + " y_likelihood = pm.Normal(\"y_likelihood\", mu=m*x+c, sd=σ, observed=y)\n", + "\n", + " with model:\n", + " trace = pm.sample()\n", + "\n", + " return model, trace" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", + " warnings.warn(\n", + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [σ, c, m]\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
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\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 12 seconds.\n" + ] + } + ], + "source": [ + "# run the model on the truncated data (xt, yt)\n", + "linear_model, linear_trace = linear_regression(xt, yt)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 296, + "width": 656 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(linear_trace, var_names=['m'], ref_val=m, figsize=(9, 4));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, the posterior of the regression slope `m` is underestimated, by quite lot in this example.\n", + "\n", + "Let's visualise how bad that fit is by plotting the data and posterior predictions." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 623 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "def pp_plot(x, y, trace):\n", + " fig, ax = plt.subplots(figsize=(10, 8))\n", + " # plot data\n", + " ax.plot(x, y, 'k.')\n", + " # plot posterior predicted... samples from posterior\n", + " xi = np.array([np.min(x), np.max(x)])\n", + " n_samples=1000\n", + " for n in range(n_samples):\n", + " y_ppc = xi * trace[\"m\"][n] + trace[\"c\"][n]\n", + " ax.plot(xi, y_ppc, c=\"steelblue\", alpha=0.01, rasterized=True)\n", + " # plot true\n", + " ax.plot(xi, m * xi + c, \"k\", lw=3, label=\"True\")\n", + " # plot bounds\n", + " ax.axhline(bounds[0], c='r', ls='--')\n", + " ax.axhline(bounds[1], c='r', ls='--')\n", + " ax.legend()\n", + " ax.set(xlabel=\"x\", ylabel=\"y\")\n", + " \n", + "pp_plot(xt, yt, linear_trace)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that the degree of estimation bias will depend upon a number of things, including the truncation boundaries and the measurement noise. In some situations with high measurement precision and/or little measurement noise, the estimation bias may not be very large. Otherwise, this could have a negative impact upon your research conclusions." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Truncated regression avoids this underestimate" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Truncated regression solves this problem. By using a truncated normal likelihood distribution we are explicity stating our knowledge about the generative process which gave rise to your dataset. We can impliment a [truncated regression model](https://en.wikipedia.org/wiki/Truncated_regression_model) as below." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def truncated_regression(x, y, bounds):\n", + "\n", + " with pm.Model() as model:\n", + " m = pm.Normal(\"m\", mu=0, sd=1)\n", + " c = pm.Normal(\"c\", mu=0, sd=1)\n", + " σ = pm.HalfNormal(\"σ\", sd=1)\n", + "\n", + " y_likelihood = pm.TruncatedNormal(\n", + " \"y_likelihood\",\n", + " mu=m * x + c,\n", + " sd=σ,\n", + " observed=y,\n", + " lower=bounds[0],\n", + " upper=bounds[1],\n", + " )\n", + " \n", + " with model:\n", + " trace = pm.sample()\n", + "\n", + " return model, trace" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", + " warnings.warn(\n", + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [σ, c, m]\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " \n", + " 100.00% [8000/8000 00:04<00:00 Sampling 4 chains, 0 divergences]\n", + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 13 seconds.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" + ] + } + ], + "source": [ + "# run the model on the truncated data (xt, yt)\n", + "truncated_model, truncated_trace = truncated_regression(xt, yt, bounds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And we can check that the inferences are much better by examining the posterior distribution over our slope parameter `m`." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", + " warnings.warn(\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 296, + "width": 656 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(truncated_trace, var_names=['m'], ref_val=m, figsize=(9, 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And also by doing our graphical posterior predictive checks. Looks good." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 614 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pp_plot(xt, yt, truncated_trace)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Last updated: Sun Jan 24 2021\n", + "\n", + "Python implementation: CPython\n", + "Python version : 3.8.5\n", + "IPython version : 7.19.0\n", + "\n", + "pymc3 : 3.10.0\n", + "matplotlib: 3.3.2\n", + "numpy : 1.19.2\n", + "arviz : 0.11.0\n", + "\n", + "Watermark: 2.1.0\n", + "\n" + ] + } + ], + "source": [ + "%load_ext watermark\n", + "%watermark -n -u -v -iv -w" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From d3dabca59f38a0a46e8aae6bde713979017e7bf5 Mon Sep 17 00:00:00 2001 From: "Benjamin T. Vincent" Date: Mon, 25 Jan 2021 16:24:38 +0000 Subject: [PATCH 4/8] delete truncated regression example from main branch --- .../GLM-truncated-regression.ipynb | 1089 ----------------- 1 file changed, 1089 deletions(-) delete mode 100644 examples/generalized_linear_models/GLM-truncated-regression.ipynb diff --git a/examples/generalized_linear_models/GLM-truncated-regression.ipynb b/examples/generalized_linear_models/GLM-truncated-regression.ipynb deleted file mode 100644 index 9a34f145f..000000000 --- a/examples/generalized_linear_models/GLM-truncated-regression.ipynb +++ /dev/null @@ -1,1089 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Truncated regression\n", - "\n", - "**Author:** [Ben Vincent](https://github.com/drbenvincent)\n", - "\n", - "The notebook provides an example of how to conduct linear regression when you have a truncated outcome variable. Truncation is a type of missing data problem where you are simply unaware of any data that falls outside of a certain set of bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running on PyMC3 v3.10.0\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import pymc3 as pm\n", - "import arviz as az\n", - "\n", - "print(f\"Running on PyMC3 v{pm.__version__}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%config InlineBackend.figure_format = 'retina'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For this example of `(x, y)` scatter data, we can describe the truncation process as simply filtering out any data for which our outcome variable `y` falls outside of a set of bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def truncate_y(x, y, bounds):\n", - " keep = (y >= bounds[0]) & (y <= bounds[1])\n", - " return (x[keep], y[keep])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Generate some true (latent) data before any truncation takes place. In the real world, you would not have access to this `(x, y)` data." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "m, c, σ, N = 1, 0, 2, 200\n", - "x = np.random.uniform(-10, 10, N)\n", - "y = np.random.normal(m * x + c, σ)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Rather, in a real world context, you would have access to truncated data, where our outcome variable `y` falls within the bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "bounds = [-5, 5]\n", - "xt, yt = truncate_y(x, y, bounds)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can visualise this latent data (in grey) and the remaining truncated data (black) as below." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 614 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 8))\n", - "ax.plot(x, y, '.', c=[0.7, 0.7, 0.7], label=\"all data\")\n", - "ax.plot(xt, yt, '.', c=[0, 0, 0], label=\"truncated data\")\n", - "ax.axhline(bounds[0], c='r', ls='--')\n", - "ax.axhline(bounds[1], c='r', ls='--')\n", - "ax.set(xlabel=\"x\", ylabel=\"y\")\n", - "ax.legend();" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Linear regression of truncated data underestimates the slope" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Before we get into truncated regression, it is useful to understand why it is needed. If you haven't guessed already from the plot above, then a regression on the truncated data is likely to underestimate the true regression slope. Let's see that in action." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "def linear_regression(x, y):\n", - "\n", - " with pm.Model() as model:\n", - " m = pm.Normal(\"m\", mu=0, sd=1)\n", - " c = pm.Normal(\"c\", mu=0, sd=1)\n", - " σ = pm.HalfNormal(\"σ\", sd=1)\n", - " y_likelihood = pm.Normal(\"y_likelihood\", mu=m*x+c, sd=σ, observed=y)\n", - "\n", - " with model:\n", - " trace = pm.sample()\n", - "\n", - " return model, trace" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", - " warnings.warn(\n", - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [σ, c, m]\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
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\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 12 seconds.\n" - ] - } - ], - "source": [ - "# run the model on the truncated data (xt, yt)\n", - "linear_model, linear_trace = linear_regression(xt, yt)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 296, - "width": 656 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(linear_trace, var_names=['m'], ref_val=m, figsize=(9, 4));" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As we can see, the posterior of the regression slope `m` is underestimated, by quite lot in this example.\n", - "\n", - "Let's visualise how bad that fit is by plotting the data and posterior predictions." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 623 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "def pp_plot(x, y, trace):\n", - " fig, ax = plt.subplots(figsize=(10, 8))\n", - " # plot data\n", - " ax.plot(x, y, 'k.')\n", - " # plot posterior predicted... samples from posterior\n", - " xi = np.array([np.min(x), np.max(x)])\n", - " n_samples=1000\n", - " for n in range(n_samples):\n", - " y_ppc = xi * trace[\"m\"][n] + trace[\"c\"][n]\n", - " ax.plot(xi, y_ppc, c=\"steelblue\", alpha=0.01, rasterized=True)\n", - " # plot true\n", - " ax.plot(xi, m * xi + c, \"k\", lw=3, label=\"True\")\n", - " # plot bounds\n", - " ax.axhline(bounds[0], c='r', ls='--')\n", - " ax.axhline(bounds[1], c='r', ls='--')\n", - " ax.legend()\n", - " ax.set(xlabel=\"x\", ylabel=\"y\")\n", - " \n", - "pp_plot(xt, yt, linear_trace)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that the degree of estimation bias will depend upon a number of things, including the truncation boundaries and the measurement noise. In some situations with high measurement precision and/or little measurement noise, the estimation bias may not be very large. Otherwise, this could have a negative impact upon your research conclusions." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Truncated regression avoids this underestimate" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Truncated regression solves this problem. By using a truncated normal likelihood distribution we are explicity stating our knowledge about the generative process which gave rise to your dataset. We can impliment a [truncated regression model](https://en.wikipedia.org/wiki/Truncated_regression_model) as below." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "def truncated_regression(x, y, bounds):\n", - "\n", - " with pm.Model() as model:\n", - " m = pm.Normal(\"m\", mu=0, sd=1)\n", - " c = pm.Normal(\"c\", mu=0, sd=1)\n", - " σ = pm.HalfNormal(\"σ\", sd=1)\n", - "\n", - " y_likelihood = pm.TruncatedNormal(\n", - " \"y_likelihood\",\n", - " mu=m * x + c,\n", - " sd=σ,\n", - " observed=y,\n", - " lower=bounds[0],\n", - " upper=bounds[1],\n", - " )\n", - " \n", - " with model:\n", - " trace = pm.sample()\n", - "\n", - " return model, trace" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", - " warnings.warn(\n", - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [σ, c, m]\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " \n", - " 100.00% [8000/8000 00:04<00:00 Sampling 4 chains, 0 divergences]\n", - "
\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 13 seconds.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" - ] - } - ], - "source": [ - "# run the model on the truncated data (xt, yt)\n", - "truncated_model, truncated_trace = truncated_regression(xt, yt, bounds)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And we can check that the inferences are much better by examining the posterior distribution over our slope parameter `m`." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", - " warnings.warn(\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 296, - "width": 656 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(truncated_trace, var_names=['m'], ref_val=m, figsize=(9, 4))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And also by doing our graphical posterior predictive checks. Looks good." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 614 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pp_plot(xt, yt, truncated_trace)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Last updated: Sun Jan 24 2021\n", - "\n", - "Python implementation: CPython\n", - "Python version : 3.8.5\n", - "IPython version : 7.19.0\n", - "\n", - "pymc3 : 3.10.0\n", - "matplotlib: 3.3.2\n", - "numpy : 1.19.2\n", - "arviz : 0.11.0\n", - "\n", - "Watermark: 2.1.0\n", - "\n" - ] - } - ], - "source": [ - "%load_ext watermark\n", - "%watermark -n -u -v -iv -w" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} From 664ab97019402a10a8482e01ec9ec2e860b1ffc1 Mon Sep 17 00:00:00 2001 From: "Benjamin T. Vincent" Date: Sun, 24 Jan 2021 16:43:29 +0000 Subject: [PATCH 5/8] create truncated regression example --- .../GLM-truncated-regression.ipynb | 1089 +++++++++++++++++ 1 file changed, 1089 insertions(+) create mode 100644 examples/generalized_linear_models/GLM-truncated-regression.ipynb diff --git a/examples/generalized_linear_models/GLM-truncated-regression.ipynb b/examples/generalized_linear_models/GLM-truncated-regression.ipynb new file mode 100644 index 000000000..9a34f145f --- /dev/null +++ b/examples/generalized_linear_models/GLM-truncated-regression.ipynb @@ -0,0 +1,1089 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Truncated regression\n", + "\n", + "**Author:** [Ben Vincent](https://github.com/drbenvincent)\n", + "\n", + "The notebook provides an example of how to conduct linear regression when you have a truncated outcome variable. Truncation is a type of missing data problem where you are simply unaware of any data that falls outside of a certain set of bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running on PyMC3 v3.10.0\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import pymc3 as pm\n", + "import arviz as az\n", + "\n", + "print(f\"Running on PyMC3 v{pm.__version__}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "%config InlineBackend.figure_format = 'retina'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For this example of `(x, y)` scatter data, we can describe the truncation process as simply filtering out any data for which our outcome variable `y` falls outside of a set of bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def truncate_y(x, y, bounds):\n", + " keep = (y >= bounds[0]) & (y <= bounds[1])\n", + " return (x[keep], y[keep])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Generate some true (latent) data before any truncation takes place. In the real world, you would not have access to this `(x, y)` data." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "m, c, σ, N = 1, 0, 2, 200\n", + "x = np.random.uniform(-10, 10, N)\n", + "y = np.random.normal(m * x + c, σ)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Rather, in a real world context, you would have access to truncated data, where our outcome variable `y` falls within the bounds." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "bounds = [-5, 5]\n", + "xt, yt = truncate_y(x, y, bounds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can visualise this latent data (in grey) and the remaining truncated data (black) as below." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 614 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 8))\n", + "ax.plot(x, y, '.', c=[0.7, 0.7, 0.7], label=\"all data\")\n", + "ax.plot(xt, yt, '.', c=[0, 0, 0], label=\"truncated data\")\n", + "ax.axhline(bounds[0], c='r', ls='--')\n", + "ax.axhline(bounds[1], c='r', ls='--')\n", + "ax.set(xlabel=\"x\", ylabel=\"y\")\n", + "ax.legend();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Linear regression of truncated data underestimates the slope" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Before we get into truncated regression, it is useful to understand why it is needed. If you haven't guessed already from the plot above, then a regression on the truncated data is likely to underestimate the true regression slope. Let's see that in action." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def linear_regression(x, y):\n", + "\n", + " with pm.Model() as model:\n", + " m = pm.Normal(\"m\", mu=0, sd=1)\n", + " c = pm.Normal(\"c\", mu=0, sd=1)\n", + " σ = pm.HalfNormal(\"σ\", sd=1)\n", + " y_likelihood = pm.Normal(\"y_likelihood\", mu=m*x+c, sd=σ, observed=y)\n", + "\n", + " with model:\n", + " trace = pm.sample()\n", + "\n", + " return model, trace" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", + " warnings.warn(\n", + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [σ, c, m]\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
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\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 12 seconds.\n" + ] + } + ], + "source": [ + "# run the model on the truncated data (xt, yt)\n", + "linear_model, linear_trace = linear_regression(xt, yt)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 296, + "width": 656 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(linear_trace, var_names=['m'], ref_val=m, figsize=(9, 4));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, the posterior of the regression slope `m` is underestimated, by quite lot in this example.\n", + "\n", + "Let's visualise how bad that fit is by plotting the data and posterior predictions." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 623 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "def pp_plot(x, y, trace):\n", + " fig, ax = plt.subplots(figsize=(10, 8))\n", + " # plot data\n", + " ax.plot(x, y, 'k.')\n", + " # plot posterior predicted... samples from posterior\n", + " xi = np.array([np.min(x), np.max(x)])\n", + " n_samples=1000\n", + " for n in range(n_samples):\n", + " y_ppc = xi * trace[\"m\"][n] + trace[\"c\"][n]\n", + " ax.plot(xi, y_ppc, c=\"steelblue\", alpha=0.01, rasterized=True)\n", + " # plot true\n", + " ax.plot(xi, m * xi + c, \"k\", lw=3, label=\"True\")\n", + " # plot bounds\n", + " ax.axhline(bounds[0], c='r', ls='--')\n", + " ax.axhline(bounds[1], c='r', ls='--')\n", + " ax.legend()\n", + " ax.set(xlabel=\"x\", ylabel=\"y\")\n", + " \n", + "pp_plot(xt, yt, linear_trace)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that the degree of estimation bias will depend upon a number of things, including the truncation boundaries and the measurement noise. In some situations with high measurement precision and/or little measurement noise, the estimation bias may not be very large. Otherwise, this could have a negative impact upon your research conclusions." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Truncated regression avoids this underestimate" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Truncated regression solves this problem. By using a truncated normal likelihood distribution we are explicity stating our knowledge about the generative process which gave rise to your dataset. We can impliment a [truncated regression model](https://en.wikipedia.org/wiki/Truncated_regression_model) as below." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def truncated_regression(x, y, bounds):\n", + "\n", + " with pm.Model() as model:\n", + " m = pm.Normal(\"m\", mu=0, sd=1)\n", + " c = pm.Normal(\"c\", mu=0, sd=1)\n", + " σ = pm.HalfNormal(\"σ\", sd=1)\n", + "\n", + " y_likelihood = pm.TruncatedNormal(\n", + " \"y_likelihood\",\n", + " mu=m * x + c,\n", + " sd=σ,\n", + " observed=y,\n", + " lower=bounds[0],\n", + " upper=bounds[1],\n", + " )\n", + " \n", + " with model:\n", + " trace = pm.sample()\n", + "\n", + " return model, trace" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", + " warnings.warn(\n", + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [σ, c, m]\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " \n", + " 100.00% [8000/8000 00:04<00:00 Sampling 4 chains, 0 divergences]\n", + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 13 seconds.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" + ] + } + ], + "source": [ + "# run the model on the truncated data (xt, yt)\n", + "truncated_model, truncated_trace = truncated_regression(xt, yt, bounds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And we can check that the inferences are much better by examining the posterior distribution over our slope parameter `m`." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", + " warnings.warn(\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", + "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 296, + "width": 656 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(truncated_trace, var_names=['m'], ref_val=m, figsize=(9, 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And also by doing our graphical posterior predictive checks. Looks good." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 479, + "width": 614 + }, + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pp_plot(xt, yt, truncated_trace)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Last updated: Sun Jan 24 2021\n", + "\n", + "Python implementation: CPython\n", + "Python version : 3.8.5\n", + "IPython version : 7.19.0\n", + "\n", + "pymc3 : 3.10.0\n", + "matplotlib: 3.3.2\n", + "numpy : 1.19.2\n", + "arviz : 0.11.0\n", + "\n", + "Watermark: 2.1.0\n", + "\n" + ] + } + ], + "source": [ + "%load_ext watermark\n", + "%watermark -n -u -v -iv -w" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From cc6693fe22d0913e7d7219e84ebdc27289834109 Mon Sep 17 00:00:00 2001 From: "Benjamin T. Vincent" Date: Mon, 25 Jan 2021 16:24:38 +0000 Subject: [PATCH 6/8] delete truncated regression example from main branch --- .../GLM-truncated-regression.ipynb | 1089 ----------------- 1 file changed, 1089 deletions(-) delete mode 100644 examples/generalized_linear_models/GLM-truncated-regression.ipynb diff --git a/examples/generalized_linear_models/GLM-truncated-regression.ipynb b/examples/generalized_linear_models/GLM-truncated-regression.ipynb deleted file mode 100644 index 9a34f145f..000000000 --- a/examples/generalized_linear_models/GLM-truncated-regression.ipynb +++ /dev/null @@ -1,1089 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Truncated regression\n", - "\n", - "**Author:** [Ben Vincent](https://github.com/drbenvincent)\n", - "\n", - "The notebook provides an example of how to conduct linear regression when you have a truncated outcome variable. Truncation is a type of missing data problem where you are simply unaware of any data that falls outside of a certain set of bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running on PyMC3 v3.10.0\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import pymc3 as pm\n", - "import arviz as az\n", - "\n", - "print(f\"Running on PyMC3 v{pm.__version__}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%config InlineBackend.figure_format = 'retina'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For this example of `(x, y)` scatter data, we can describe the truncation process as simply filtering out any data for which our outcome variable `y` falls outside of a set of bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def truncate_y(x, y, bounds):\n", - " keep = (y >= bounds[0]) & (y <= bounds[1])\n", - " return (x[keep], y[keep])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Generate some true (latent) data before any truncation takes place. In the real world, you would not have access to this `(x, y)` data." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "m, c, σ, N = 1, 0, 2, 200\n", - "x = np.random.uniform(-10, 10, N)\n", - "y = np.random.normal(m * x + c, σ)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Rather, in a real world context, you would have access to truncated data, where our outcome variable `y` falls within the bounds." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "bounds = [-5, 5]\n", - "xt, yt = truncate_y(x, y, bounds)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can visualise this latent data (in grey) and the remaining truncated data (black) as below." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 614 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 8))\n", - "ax.plot(x, y, '.', c=[0.7, 0.7, 0.7], label=\"all data\")\n", - "ax.plot(xt, yt, '.', c=[0, 0, 0], label=\"truncated data\")\n", - "ax.axhline(bounds[0], c='r', ls='--')\n", - "ax.axhline(bounds[1], c='r', ls='--')\n", - "ax.set(xlabel=\"x\", ylabel=\"y\")\n", - "ax.legend();" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Linear regression of truncated data underestimates the slope" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Before we get into truncated regression, it is useful to understand why it is needed. If you haven't guessed already from the plot above, then a regression on the truncated data is likely to underestimate the true regression slope. Let's see that in action." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "def linear_regression(x, y):\n", - "\n", - " with pm.Model() as model:\n", - " m = pm.Normal(\"m\", mu=0, sd=1)\n", - " c = pm.Normal(\"c\", mu=0, sd=1)\n", - " σ = pm.HalfNormal(\"σ\", sd=1)\n", - " y_likelihood = pm.Normal(\"y_likelihood\", mu=m*x+c, sd=σ, observed=y)\n", - "\n", - " with model:\n", - " trace = pm.sample()\n", - "\n", - " return model, trace" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", - " warnings.warn(\n", - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [σ, c, m]\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
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\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 12 seconds.\n" - ] - } - ], - "source": [ - "# run the model on the truncated data (xt, yt)\n", - "linear_model, linear_trace = linear_regression(xt, yt)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": 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d06OxiVlVDtf0aKzw4NwVonM3Hdbe46kmZgQAAABUHBQgAQCAHA6HJn+3SYfznPvYrE6QnruioywWzn08G38fL918Xu4qSLtD+nApqyABAAAAiQIkAACQ9NXq/Vq4Pd6I/bytendsNwX5eZuYVeVyfZ8mCvHPfb++X39QR5LSTcwIAAAAqBgoQAIAUM3FJqTo2V+3u4w9dSnnPpZUiL+PJvaLMuJsm0Mf/bXXvIQAAACACoJlDQAAVGPZNrvun71R6dk2Y+zCdvV0XS/OfSyJNWvWaMeOHUqOO6CM6EOyB4bJr3EHzVq9X/ec30K1guggDgAAgOqLAiQAANXY24t2K/pgkhGHB/vphdGc+1hcH3/8sV566SXt2bOn4JNe3gps0Udvtw/Sk2MGlPlrR0VFad++fed0j88++0wTJ050+9yUKVP09NNPl/ievXv31sqVK88pLwAAAFQtbMEGAKCaWrfvpN5Z7Fo4e+XqTqod7GdSRpVHVlaWRo8erVtuucV98VGSbDlK2/m3pt40UnPnzS/fBIspNDTU7BQAAABQDbACEgCAaiglM0f/mb1Rdkfu2A19IzWkdV3zkqpEbr31Vv34449GHB4ervHjx6tNmzY6deqU3p35gw5sWS1JsqWf1lVXXa3VK5erY8eOZZZDVFSUvL1L9qNcTExuZ+7Q0FCNGDGiWPO8vb0VGRlZrGsbN2b7PgAAAFxRgAQAoBp6es5WHTiZ26G5eZ0gPXJRWxMzqjy++eYbzZgxw4jPP/98/fjjj6pRI7dpzyXjb9fgO1/U8V+nSbZsZaSlaOzYsYqOjpbVWjYbUJYsWVKi65cvX67+/fsb8ZgxYxQQEFCsuY0aNSp8pScAAABwFmzBBgCgmpm/5ai+XXfQiL2tFr05pqsCfL1MzKpysNlsevLJJ404IiKiQPFRkto3DNXwSy5XrYHjjbEtW7Zo1qxZ5ZZrfp9++qlLfNNNN5mUCQAAAKobVkACAFBCycnJWrJkifbv36/Tp08rIiJCQ4YMUURERKFzTp06pSVLligmJkY2m02NGjXS0KFDVb9+/VLlkJ2dreXLlys2NlbHjh2Tv7+/GjZsqIEDB6pevXqFzjuZmqXHftzsMvZ/F7ZSh0ahOnXqlDZt2qRdu3bp5MmTcjgcql27tpo3b66+ffsWe7VccXJfsmSJYmNjderUKYWHh6tXr17q1KlTmdzfk37//Xft3LnTiJ966qkCxcczbh3YTMt2jVLyul9kS06QJL355psaN25cueSaV1pamr755hsjbt++vXr16lXueQAAAKB6ogAJAIAbEydONLbZDho0SEuWLFFqaqomT56sGTNmKC0tzeV6Ly8vTZgwQW+++aaCg4ON8cTERD300EP67LPPlJ2d7TLHarXqlltu0bRp0xQUFFSsvI4ePaopU6Zo1qxZSk5OLvC81WrV+eefr2nTprkt6E2Zs1UnUrOMuH1who4vm6Ue//1ZGzZskN1ud/u6vr6+GjdunJ566qlinQWYt4NyZGSk4uLi5HA49Morr2jatGk6duxYgTldunTR+++/rz59+pz1/mb56aefjMdBQUEaM2ZModcOaBmudo1qKanDUCUtd658XLt2rQ4fPqyGDRt6OlUX3333nU6fPm3EN954Y7m+PgAAAKo3tmADAFAM8fHx6t27t95///0CxUfJuTX3008/1bBhw5SRkSFJ2r9/v3r06KH//e9/BYqPkmS32/Xhhx9q1KhRbp/Pb86cOWrZsqU+/PBDt8XHM/dcuHChunXr5nJOoSQt2HpUc6IPG7G/j1X2VV/oqSef1Lp16wotPkrOrs+fffaZunbtqqVLl5411/wyMzN1ySWX6KGHHnJbfJSkjRs36vzzz9fixYtLfP/y8ttvvxmP+/bt61Jszs9isejWgU3l37SLMeZwODRv3jxPpujWZ599Zjz29vbW+PHji7gaAAAAKFusgAQA4CxsNpvGjBmjrVu3KiAgQKNHj1bv3r0VEBCg7du3a8aMGTpx4oQkaeXKlXr66af1+OOP6+KLL1ZMTIwCAgJ0xRVXqHfv3goMDNSOHTs0ffp0Y86iRYv0xhtvaPLkyYXmMHv2bI0bN042m80Y69evny688EJFREQoLS1Nq1ev1vfff6/09HTZbDbdeOONCg4O1pVXXqnEtCw99tMWl3tOHt5G87bn/ijQrl079e3bV23btlWtWrWUmZmp2NhYzZ07V9u3b5fk3Eo+atQobdq0SU2aNCn2e3jnnXcaxbuhQ4fqggsuUN26dXXixAnNmTNHf//9tyQpPT1d48eP1/bt2xUSElLs+5eHU6dO6dChQ0ZcnJWal3RqqJdadVS81UuyO3/v/l69XjfffLPH8swvNjbWpWg8cuRI1a1Lt3MAAACUI4fDUdovAACqrAkTJjgkOSQ5LBaLQ5KjU6dOjr179xa49siRI47mzZsb1wcFBTkmTZrkkOTo3Lmz2zmHDx92NGvWzJgTHh7uyMrKcpvL7t27HcHBwca19erVcyxatMjttbGxsY727dsb19auXdsRHx/vuH/2BkfkQ78aX6Pf+8eRY7M7xo4d67jzzjsdW7ZsKfS9sNvtjo8//tjh6+tr3Peaa64p8v176qmnCrx/derUcSxbtszt9S+99JJxvSTHG2+8UeT9zfDPP/+45Dh9+vRizfvorxiHV426xrymnft6OFNXTzzxhEveP//8c7Hm5f09DA0NdYwdO9bRvHlzR2BgoCMgIMARERHhGDhwoOOJJ55wbN261cO/CgAAAFQQpaojWhwOR6lrl6WdCABARZf3DEhJCg8P19atWwtdOfbrr7/q0ksvdRmrU6eOtm7dqjp16ridM2fOHI0aNcqI58+fr+HDhxe4buTIkcbqwZCQEK1evVpt2rQpNPejR4+qffv2OnnypCTpulvu0fKw3Pv6eVv1230D1LxOsDIyMuTv71/ovfL66KOPdOutt0qSfHx8tH///kKb6OQ9A/LM9StXrlS3bt0Kvf/gwYONlXq9e/fWypUrC7123LhxWrVqVbHyLqkvv/xSvXv3djt+/fXXG/Gff/6pIUOGnPV+KZk5qteqi9L2b5Uk+dRqqEP7YlUnxK/ski6E3W5X06ZNtX//fklSvXr1dPDgQXl7n30TTP7fw6JYLBaNHj1a77//fqHf7wAAAKgSLKWZxBmQAAAUw+OPP17kttWLLrpItWrVKjCnqGLMxRdfrJo1axrx6tWrC1yzc+dOlzMDp0yZUmTxUZLq16+vxx57zIi/++oLOey5W7f/b1grNa/jPLuwuMVHSZo0aZKaNWsmydnJ+s8//yz23FtuuaXI4qMkl23JGzduVE5OTqHXHjp0SDExMR75Sk9Pd/ua+c/dzP/7XZhgP29FNsj93rFlpWnG8rhizT1XixYtMoqPkjR+/PhiFR/d8fLyUt26dRUZGVmg87fD4dD333+vrl27asuWLYXcAQAAANUVBUgAAIph7NixRT7v5eWlDh06lGiOt7e3OnbsaMQ7d+4scM3s2bN1ZreCv7+/sQLxbPI2GclOTVTWsb2SpE4Robr5vKbFukd+FovFZcXfunXrij33hhtuOOs1eVcdZmZmKi4urkT5eVpKSopLXJLibcuGYcZjR1aGZq7ap7SswgusZSVv8xmp5N2v27Rpo6lTp2r16tVKSUlRfHy84uLilJSUpNjYWL366qsuq2APHTqkSy65pNBGQwAAAKieKEACAHAWUVFRxdpWWq9ePeNx06ZNFR4eXqI5iYmJBZ4/05xFks4777wiuy7nVadOHTVqHGnEWUd2yWqRnr+io7y9Sv/Hf/5iU3H4+PicdfWjJDVq1Mgldvd+nLFkyZJzOce6yK/Bgwe7fc0z3c3P8PX1Peuv6YzQ4EDjsSMnS4lp2fpu3cFizy+NpKQk/fjjj0bcu3dvtWvXrtjz7777bm3fvl1PPPGEevbsWaDg2rRpUz3wwAPatGmT+vfvb4zv27fPZQUuAAAAQAESAICzyFskLEpQUJDxuLhdhvPOSU1NLfB8dHS08bht27bFuqfk3BKb7pVbrMw5fVwT+kWpQ6NQt9cnJibq448/1nXXXacOHTooPDxcvr6+slgsLl/PPfecMScpKalYuYSFhcnHx+es1+V9LyT374eZ8hfgsrKyij03MzPTeGzxdhYuP/l7r2x2zx2pPWvWLJeiaUlXPxangC45i91z5sxRRESEMTZ9+nQdPny4RK8HAACAqosCJAAAZ1GSrbbnMsddY7gzjWQk6e233y5QECzsy2q16mTc1tx87On6v2Gt3L7ma6+9psaNG+uWW27R119/ra1bt+rEiRPKzs4uMt/8KwILU5r34kxuFUn+1afF/fVLcjlX0uLrfD/2nUjTH9viyyY5Nz799FPjcUBAgMaMGeOx1woLC3NZ9ZiTk6P58+d77PUAAABQuVCABACggkpNTS2yEUtJdKofoBD/gqsQ77rrLj3wwAMFzje0WCwKDw9X48aN1bx5c+Mrb+OVilYg9LT8jVdOnTpV7Ll5t5NbfQOMxx8viz3nvNzZunWr1qxZY8SjR49WaKj71a9l5YorrnCJi+piDgAAgOqldG0QAQCAxwUEBMhqtcput0tybnXNXwRz50RKllIycwuXAb5e6toqssB1v/32m95//30jbtasme677z4NHTpULVu2dLtt+qmnntLUqVNL88up9Jo2dW3ek7e79NnkvTa0bu5W5bX7TmnD/lPq2qR4HbWLK3/zmZtuuqlM7+9OvXr1FBoaamzNpxENAAAAzqAACQBABWW1WlWzZk1jG/b999+vRx55pMg5q/ee1DUfrtCZtW5+3lYt/L9BahwWWODaN99803jcoUMH/fPPP2ctcBbVGKY8jRs3TqtWrfLIvb/88kuXjtxn5D+DMyYmplj3y8zMdGnY07trR23N8/zHy/bq3XFlV4DMycnRzJkzjTgqKsqle7knBQQEGAXIvNvOAQAAUL1RgAQAoAJr06aNli9fLknasWNHkddm2+x6/KfNLmP3XtDSbfHRbrdryZIlRvz4448Xa3Xl3r17i5G15x06dKjYBcCSKqxwVqtWLTVq1MgoJq5YsaJY91uzZo3LVvpLB/fW8RN+ik92NqaZt+WIDpxMc/v7VBpz585VfHzu2ZITJ06UxWIpk3sXxWaz6cSJE0Zc3CY2AAAAqPo4AxIAgAps0KBBxuP58+fLZrMVeu3Mlfu0Kz73LMcWdYN1y4Bmbq89ceKESxfnzp07nzWXrKws/fPPP8VJu8q66KKLjMcrVqwoVqfuP/74w3hssVh06SUjNaFflDFmd0if/lN2hd28268tFosmTpxYZvcuyqpVq1waF+Xfsg4AAIDqiwIkAAAV2DXXXGM8PnbsmGbMmOH2uqS0bL25aLfL2LOXd5Cvt/s/6vM3kClOR+dZs2a5dOU205IlS+RwODzyNXjw4EJf9/LLLzcep6amatasWUXmabPZNH36dCPu3r27GjVqpHG9IhXo62WMf7PmgJLSi+46XhzHjh3Tb7/9ZsTnn3++IiMLnv/pCW+//bZLPHTo0HJ5XQAAAFR8FCABAKjAunTpohEjRhjxAw884HYr9tt/7lZiWm4Ba2THBurTrLYk98XF2rVrKzAwd8vv3Llzi8zj8OHDmjx5conzr2pGjBihVq1aGfHTTz+t5OTkQq9/4403XBrQ3HvvvZKk0EAfXdOjsTGemmXTrNX7je3SZ77i4uJKlN/MmTNdViGWtvlMSc9vnDVrlr7++msjbtasmc4777xSvTYAAACqHgqQAABUcG+99ZZxPmNiYqL69++v2bNnG92x446nasaKOON6Xy+rHhrRRuvXr9e9996rAQMGFLinl5eXS2OSF154QUuXLnX7+hs3btTAgQOVkJAgq7V6/+jg5eWlp59+2ogPHjyo0aNHuy1Cfv/993rssceMuF27dho3bpwR39S/qax5jmb87J+9sttdV6aWVN7t16GhobriiitKdZ977rlHEydO1Jo1a4q8LiMjQ88995zGjx/vMv7888/L25ujxgEAAODET4YAAFRwLVu21Jdffqkrr7xSWVlZOnnypMaMGaNHH31UF154oTanBOvUyRw5crJkS0tSYx3XeV/cpgMHDkiSWrdu7fa+Dz74oLHyMTU1Veeff74uvfRSDR48WDVr1lRCQoIWL16s33//XXa7XQ0bNtRll12mDz74oNx+7RXRmDFjNHfuXKPT9KJFi9SiRQvdcMMNat26tRITE7VgwQItXLjQmBMcHKyvvvrKpYDbpHaghrevr3lbjkqS4pMzFXgqrdR5rVmzRlu2bDHi6667TgEBAaW6V05OjmbMmKEZM2YoKipKffv2Vfv27VW7dm35+/srMTFR0dHRmjt3rhISElzm3n///br22mtL/esAAABA1UMBEgCASuCSSy7Rn3/+qSuvvNLocBwbG+u2GJiUL/by8ipwjSQNHDhQU6dO1ZNPPinJ2Rn7559/1s8//1zg2jp16uiHH37QvHnzzu0XUkV8/PHHSk5O1pw5cyRJCQkJmjZtmttra9asqVmzZrlt9DNpQDOjACnJpYlQSeVd/ShJN954Y6nvlVdcXFyxtoL7+Pho6tSpeuihh8rkdQEAAFB1VO99VAAAVCL9+/fXnj179Oyzz6px48ZFXuvn56chQ4bo7bff1l9//VXodU888YRmzpxZ6P38/Px07bXXKjo6Wr179z6n/KsSPz8//fzzz/rwww/VrJn7TuO+vr668sorFR0d7XKOZ17dI2upe2QtIy5tI5qMjAyXhjjt27dXr169SnUvSRo9erRGjx6tBg0anPXakJAQ3XrrrYqOjtbDDz8si8Vy1jkAAACoXiz5u2CWwLkdUgQAAM7JBz//pSc++UW2tCTZs9JVp1YNPXZlb7Vv21YdOnQo0fbbnJwcrVy5UtHR0UpKSlKtWrXUqFEjDRw4UDVr1vTcL6KKWL16tXbs2KEjR44oKChIERERGjhwoMLCws46d/6WI7p95nojHty6jqbfWPriYVmLi4vT1q1bdfDgQSUmJio7O1shISEKCwtTx44d1bFjx0JX2QIAAKDKKdW/NlOABACgEsq22XXh639p7/FUY+yjG3poWLt6JmaF0rDZHTp/2hLtO5F7/uOC+weqVb0QE7MCAAAA3CpVAZIt2AAAVELfrTvoUnzsHllLQ9vWNTEjlJaX1aKb+jd1GftwaaxJ2QAAAABljwIkAACVTEa2TW8s3OUy9tCINpy9V4ld3SNCtQJ9jPjnjYd0ODHdxIwAAACAskMBEgCASmbG8jjFJ2ca8flt6qpX07OfNYiKK9DXWzf0jTLiHLtDHy/ba15CAAAAQBmiAAkAQCWSlJ6t95bEGLHFIk0e3trEjFBWJvSLUoBPbjOXWav361RqlokZAQAAAGWDAiQAAJXI//6KUVJ6thGP6txQbRvUMDEjlJWwIF9d27OxEadn2/T5in0mZgQAAACUDQqQAABUEseSM/Tp33FG7G216P+GsfqxKpk0oKm8rblneU5fvldpWTkmZgQAAACcOwqQAABUEm//uUfp2TYjHtu7iZrUDjQxI5S1iFqBuqxLQyM+lZatb9YcMDEjAAAA4NxRgAQAoBLYdyJVs1bvN+IAHy/dfX4LEzOCp9w+qLlL/NGyvcq22U3KBgAAADh3FCABAKgEXv9jl3LsDiO++bymqhvib2JG8JRW9UI0tG1dIz6UmK5fNx02MSMAAADg3FCABACggttzLEU/R+cWoGoG+ujWQc1MzAieln8V5PtLYmTPU4AGAAAAKhMKkAAAVHDvLd4jR57a020Dm6uGv495CcHjekSFqWdULSPeFZ+ixTuPmZgRAAAAUHoUIAEAqMD2Hk/VTxsPGXGtQB/d0DfSxIxQXtytggQAAAAqIwqQAABUYO8u3qO8O28nDWimID9v8xJCuRnSuq5a1wsx4rX7Tmll7AkTMwIAAABKhwIkAAAV1P4TafpxQ+7qx9AAVj9WJ1arRbcPdj3r861Fu03KBgAAACg9CpAAAFRQ7y7eI1u+ztchnP1YrVzaqaGiagca8fKYE1oTd9LEjAAAAICSowAJAEAFdOBkmr5ff9CIQ/y9NaFflHkJwRTeXlbdNaSFyxirIAEAAFDZUIAEAKACen9pjHLyrH68qX9ThQaw+rE6uqJrIzUJy10FuWz3ca3bd8rEjAAAAICSoQAJAEAFcygxXd+uPWDEwX7euql/UxMzgpm8vay6m1WQAAAAqMQoQAIAUMF8sCRG2bbc1Y8T+0UpNJDVj9XZFd0aKaJWgBEv3ZWgjQcSzUsIAAAAKAEKkAAAVCBHkzI0e03u6scgXy/dfB6rH6s7HzdnQb65cJdJ2QAAAAAlQwESAIAK5MO/YpRlsxvxDf2iVCvI18SMUFFc2S1CjWrmroJcvDOBsyABAABQKVCABACggjiZmqWvV+eufgzw8dIkVj/iX77eBVdBTluw06RsAAAAgOKjAAkAQAUxfXmc0rNtRjy2dxPVDvYzMSNUNFf3iHDpiL085oSW7zluYkYAAADA2VGABACgAkjNzNGM5XFG7ONl0aQBrH6EKx8vq/4ztKXL2CsLdsrhcBQyAwAAADAfBUgAACqAWav3Kyk924gv79JIDUIDipiB6mpUl0ZqUTfYiDfsT9SfO46ZmBEAAEA19s+b0oLHnV//vGl2NhUWBUgAAEyWlWPXx8v2GrHFIt02qJmJGaEi87Ja9H/DWrmMTVuwS3Y7qyABAADKXWqClHzE+ZWaYHY2FRYFSAAATPbTxkM6mpxhxBe2q6cWdUNMzAgV3Yj29dWuQQ0j3nYkWfO2HDUxIwAAAKBwFCABADCRze7QB0tjXMbuGNyikKsBJ6vVov8Od10F+crvO5SVYzcpIwAAAKBwFCABADDRH9uOKjYh1Yj7Na+tLo1rmpcQKo0hreuqe2QtI447kaaZK/eZmBEAAADgHgVIAABM4nA49P6S/Ksfm5uUDSobi8WiRy9u4zL21p+7lZSWXcgMAAAAwBwUIAEAMMmKmBOKPphkxB0a1dB5LcJNzAiVTffIMI3s2MCIE9Oy9fafu03MCAAAACiIAiQAACZ5P//Zj4NayGKxmJQNKquHRrSRr1fuj3QzVsQp7nhqETMAAACA8kUBEgAAE2w5lKRlu48bcVTtQI3oUN/EjFBZNakdqIn9o4w42+bQS/N3mJcQAAAAkA8FSAAATPC/v2Jd4tsGNZeXldWPKJ27hrRQrUAfI5635ajWxJ00MSMAAAAgFwVIAADK2aHEdM3dfMSIw4P9dEXXRiZmhMouNMBH/xnaymXs2V+3yW53mJQRAAAAkIsCJAAA5Wz6P3tly1MYmtA3Uv4+XiZmhKpgbO8malYnyIijDybpl02HTcwIAAAAcKIACQBAOTqdka2vVx8wYn8fq67vE2liRqgqfLyseuSiti5jL8/fqYxsm0kZAQAAAE4UIAEAKEez1xzQ6cwcI76qe4RqBfmamBGqkqFt66pPszAjPpSYro/ynTcKAAAAlDcKkAAAlJMcm12f/RNnxBaLdPN5zcxLCFWOxWLR4yPbyZKnn9G7S/bowMk085ICAABAtUcBEgCAcvLblqM6lJhuxEPb1lPT8KAiZgAl16FRqMb0bGzEGdl2PfPrNhMzAgAAQHVHARIAgHLgcDj08TLXrbC3DGD1Izxj8vA2qhnoY8QLtsVr8Y5jJmYEAACA6owCJAAA5WD13pPadDDJiDtHhKpnVC0TM0JVFhbkq8nDW7uMTfllKw1pAAAAYAoKkAAAlIOPlu11iScNaCZL3oP6gDI2pmcTdYoINeJ9J9JoSAMAAABTUIAEAMDDYhJStGhHvBE3qhmgizrUNzEjVAdeVoueGdXBpSHNO4v3aP8JGtIAAACgfFGABADAwz75e68cjtz4xv5R8vbij2B4XufGNTWmZxMjzsyx6/Gft8iR9xsSAAAA8DD+9gMAgAedSMnU9+sOGnGIn7euzdOhGPC0B4e3Vq08DWn+2pWgOdGHTcwIAAAA1Q0FSAAAPGjmyv3KzLEb8djeTRTi71PEDKBs1Qry1eMj27mMPfPrNiWmZZmUEQAAAKobCpAAAHhIRrZNX6yMM2Jvq0UT+0eZlg+qr9HdGql/i9pGfDwlSy/8tsPEjAAAAFCdUIAEAMBDftpwSMdTcleZXdKpgRqEBpiYEaori8Wi5y7vKD/v3B/9Zq89oJWxJ0zMCgAAANUFBUgAADzAbnfo47/3uoxNGtDMpGwAKSo8SPde0NJl7NEfNysj22ZSRgAAAKguKEACAOABS3cnaM+xFCPu26y2OjQKNTEjQLplQDO1qhdsxLEJqXpj4W4TMwIAAEB1QAESAAAP+GRZ/tWPTU3KBMjl623VC6M7yWLJHfvfXzHaeCDRtJwAAABQ9VGABACgjG07nKy/9xw34mZ1gjSkdV0TMwJydY+spZv75xbE7Q5p8rfRbMUGAACAx1CABACgjH2S/+zH85rJarUUcjVQ/h64sLWahgcZ8e5jKXprEVuxAQAA4BkUIAEAKEPHkjM0J/qQEdcK9NHobo1MzAgoKMDXSy9f5boV+4OlMYpmKzYAAAA8gAIkAABlaMaKOGXbHEY8vk+k/H28TMwIcK9nVJhu7Oe6FfuBb6OVnsVWbAAAAJQtCpAAAJSRtKwcfblqvxH7elk1vm+UeQkBZzF5eGtF1g404j3HUvT8b9tNzAgAAABVEQVIAADKyPfrDioxLduIL+/aUHVC/EzMCChagK+XXr26s/IeUfrFyn36Y1u8eUkBAACgyqEACQBAGbDbHQWbzwxoZlI2QPH1jArT3UNauIw99P0mHUvOMCkjAAAAVDUUIAEAKAOLdhxT3Ik0Ix7Yqo5a1QsxMSOg+O69oKW6NqlpxCdTs/TAt9Gy2x2FTwIAAACKiQIkAABl4KNlsS7xpPOaFnIlUPF4e1n15rVdFeznbYwt231cn/6zt4hZAAAAQPF4n/0SAADKSPxWKWGnlJogZaVKQXWkkAZS416Sf42yeY2MZOnAainlqJRyTPIJlILrSuGtpPodyuY18tl0MFGr95404tb1QjSgZbj7iz3xHqSfkvYtlxL3O+8ZUEuq31Fq2E3yKuEf9Yc3SDvn58ZN+kjNh5QuL1QqTWoH6pnL2+v+2dHG2Evzd6hPs9rqUNdPOrBKSj4spcRLXj5ScD2pVlOpYVfJavK/aZ+IkeK3OD/zmclSYG0puL4U0UMKKuSzeDaZKdL+ldLJGCnztOQfKtVpLTXuLXmX8GzXk7FS9OzcuG5bqf3lpcsLAACgEqIACQDVkd0uHd8pHVovHVonHV7vLIzZstxfPyWp9K+VlSr9/Ya06WtngcwdL1+p6UBpwANSZL/Svc6+5dKyadLevwr/ddRsInW6Vjrvfsk3qHSv48bHy1xXid08oKksljxdPTz1HqSfkv54Uto4S7JnF3w+pKE05BGp2w3Fu58tR/rxDinh3y7I3gFSl7HFm1vZnYhxfh4O//uZOLJJykl3f+19m6RakeWbXzm5omuEluxM0M8bD0uSmtn36cRnb8thiZYlO9X9pKC6UvsrpEEPSUG1yy9ZW7a06gNpw0wpYYf7ayxezoJhv7ulNiOLd9/sDGnxc9Kaj6XstILPB9SS+t8n9buv+IXXuf+VYhadSUq6+Y/izQMAAKgiLA5Hqc/24VAgAKiMfrxD2j5Hykop/pzSFiBjFks/3yUlHyrmBIvUZZx0yWvFX2GUnSHN/T9p45fFz6tGhHTF+86C3zk6nJiuAS8vlu3fs/LCg/30z8ND5Oft5bzAU+/B6aPSpyOkU8XYIttzkjRy2tmvW/6OtOCx3Hjwo9Lgh84+rzJbNFVa84mUkVj8OVW4AClJyRnZGvnGUo1Lma6bvX6Tj8VWvIkBtZzfZx2u9GyCkrNA/P0k5z+kFFerEdIVH0oBNQu/JjNF+vwyZxH6rPe7SBrzpWT1Kvq6bXOkb8bnxl2uly5/t1gpAwCASmDB41LyEefjGg2kC581Nx/Ps5z9koI4AxIAqpujm0tWfCyt3Qulr64tQeFNkhzSxpnS7OulnMyzX56dIX09tmTFR0lKPih9ebUU82fJ5rkxY3mcUXyUpAl9I3OLj558D769MV/x0SK1GyX1/49Ut53rtWs+dq4SK8rpeGnpS7lxzUjnKq+q7tiOkhUfq4Eavl76MeJr3e79S/GLj5JzRe73k5wrcj3p8EZpxqUlKz5K0q750heXS+mJhV8z94GCxcfmFzhXTUf0yne/ea6fGXey0qTf8xT1/UKloVNKkDQAAEDVQAESAFD2TsRIs8dJtmIUEd3ZvUCaV4yVd7/l3dZYQjkZ0tfjpJOlb7KRkpmjr1bnbqn297FqXJ9/V8Z58j3Ys0jav9x17MJnpGs+l4Y9Ld26VGrQxfX5JS9K9iKKSQsed56dd8aIFyUf/1Kljkpu2TSF7/m2dHMddunnO6X9q8o2pzPSTkpfXlX6ovHhDdL3N7t/7vhuadNs17Fet0rjf3AWDW9eILW+2PX5Fe86C6+FWTZNSspz7MKQR6XgOqVKHQAAoDKjAAkAcDZqCapbdveb+3/OAp877UZJY7+RblogXfSys1GEO+umF13E2Le88FV9wfWcBbSbFkhjv3WeT+dOdppzxVMpfbPmgE5n5Bjxld0iFBbk6ww8+R5s/8U19gt1brM+w9tX6neP6zVJB5wrx9zZt1za/E1u3PJCqc3F7q+tTBIPSCkJJZ/n5etsDFTRZSRLx/eU7T1PxEjLXnX71GlHgKb7X6/M8XOl8T9JPW6S2x04Drv063+cZzSWtT+ecDZwcqfpQOmaL6SbF0qXvSPVbuH+uj0Lpc3fFRzf/otcThiyWJ0rio3Y4lwJmVdWivOYBXdOxkrL386N63WQet3i/loAAIAqjiY0AFDdePlI9TtJjbo5uyQ36ubcsrv0ZWnpi+d+/5g/pdgl7p/rdat08Su5cZPeUqvh0gcDXFffSZIc0sIp0k3z3N9r4RS5PY7Yr4Z00+9SWNPcsVYXOrtNr/6fm3wXSbFLpWaDCv0luWOzO/TpP66rJ28679/X9PR7cHSza9ygk+QT4DrWON92UUk6Gi1FdHcds9uk3ybnxl5+zuJtZZWZIm37WYqeJcX9LU34pegVZ1arVKdN7mehUTepXkdp87fOlXwVjd3m/P6KniXt+M25TX7II2V3/yUvuC2c5zisGp/1iDZmttDO6FC9MLqjszt6WDPn6tn8jm2Tor+Wuo0v+FxpHd8jbSjkuIXWF0vXfpnbFKZxT2fTmQ8Hua5APGPh086zKvM2i8r/uQptLIU2ch1r1MPZ2MaRZzXx0U1Sh9EFX2PeQ64roC96+eznRQIAAFRRFCABoLqZtNCzfwne+JX7cZ8g6YInC47XipJ63y799XLB5/Yvd64iCmvmOn4iRjpQyOrIPne4Fh/PuOBJ54pJd11tN35Z4gLk71uP6uCp3C7JF7Spq+Z1gv+9n4ffg/xbPoPdrF4NrldwzN1W0dUfSfFbcuN+90i1m7tNv8Ky26W9S5xnD+741f3vcWGunlE5ikJHtziLjpu/lVLiPfMaGcnS9l/dPvWzvb82OpwrCmet3q8+zcI0qksjqc9dzsK+u+7uG78s2wJk9FcqtAfi8OcLdqQODJMGPSjNubvg9Un7pb1LpWaDc8eK87myWqWgcNffA3efqx2/OY9ROKPjNVJUf/e5AwAAVANswQaA6saTxZbs9EILGGpxvuQX4v65dqMKv+cmN2fRbS7ifLrC7uUXIjU/3/1z239xNrQpgY+XxbrEkwb8WyAsj/fAO9/ZjFluCm5ZqQXH8s9LSZAWP58b14iQBpR+S3q5O7Zd+uNJ6fX20hdXOLeRl6T4KFXs4mPKMecZg++fJ33QX1rxjueKj5KzeJuT7vYp7w6Xu8SP/rBZMQkpzoJcm0vd32//CveFydIq7HPfoLP7f3SQpLaXOrdSu1Oaz5VU8LOVf152hjT/4dzYN8R5RisAAEA1RgESAFB2jm4ptIChhl0Ln1e3reQd4P65g2sKjh1Y7f5a7wDndtrCFJZDdpoUv7Xwefms23dK6/cnGnH7hjXUp1mYMyiP9yD/ttDEfQXnnIorOBYa4Rr/8aSUmZQbj3he8g0sPMeKIPW4tPID59ba9/pI/7wpnT5sdlZlJztD2vKDs0v7a22l3x+V4jeffV5ZKOxzJemSESPVr3ltI07NsumuL9crI9tW9Pf1wbVlk9vp+MKLmUW9fkBNqVYhxcmzfa6SDhZs3JR6wnnuo8u8fJ+rv193/UwOfkgKKeScVwAAgGqCAiQAoOwc2Vj4c4U1hJCcq9BqRRVyz+iCY0c3ub82rGnRK9qKyqGo3PP55O/8qx+bynLmLLnyeA+iBrjGx7YVLKDmb7JhsUpN+uXG+1c5t/Se0Wxw0aswzZST6TzX8asx0rQ20vyHzv77Vb+TNOwZ5+q4ymDfCmnOvdKrraTvbnRu37XnFH59jQip371S52vLLgd3nzVJ8g2WV2gDvTGmi8KD/YzhHUdP67Eft8hR1Jb9wu5ZVrlJRX+uinr+xG7X1Yz5P1eZSa7bqCX3qzCjzst9fCpO+ueN3Di8tfN4BQAAgGqOMyABAGXn+K7Cnztbl+3gOlLC9oLjqcektJPO89wk5+PCuuAGFdFsRHJ/ptsZCTuLnvuvAyfTNH/LUSOuX8NfIzs2zL2gPN6DLuOczULybjf+8XZp9P+cq712/Cqt+dj1Hu0uz23GYrdLv/1Xxnl6Vh/poldU4RxY4zz3b8sPUkbi2a8PayZ1uErqdI0U3tLj6Z2zk3ulTbOdzVpO7T379QFhziJxx6ulyH6uDVTKQmHfu/9+ruqG+OutMV007pNVcvz7rfP9+oPqF15bVxZ2z2J+rs6eWxH3Kc7nyh2HXTq+W2rYxRm3vliq0UhKPpR7zbwHpcBwZyE7blnBRl2NeriuwJz3sGsTn4tfdjb+AgAAqOYoQAIAyk56YuHP+YcWPbeo5zOScotv7ho+lNVrFMOn/+yVPU8fjAn9ouTrnWdDQXm8B0G1peHPSb/en/v80U3OLcnuBNWRLnw2N177iesq0j53SHVaFZ1beUncL0XPdq7OPBlz9uuD60vtr3AW5fJ3+K6IMpKkrT85f337V5z9ep8gqfVFzl9fiws8V8yy5RTcWnxGnu/Lfi3C9cCwVnp1QW6xcurCQ7rSt5D7FvNzdVbn9LmqWfhzefPz9pUufVP66hpncVJyfj9+MtT9XO8A6dI3cuNdC6RdeTrWt7vctckNAABANUYBEgBQdjJPF/6ct1/hz0mSVxHPZyaX72sUIik9W9+sOWDEgb5eGturSb77lFN+PW6ScrKkBY9L9uzC59VqKo35Kvd8u9QT0p95ipEhDaRBDxWdl6dlnnZusY7+Wor7W4V2Oj7DL9TZXKTjVVLTQQW7H1c0dpu0Z5Gz6LjzN9cVcu5YfZwNkzpeLbW5WPIN8nyORX3/5/u+vXNwC206mKQF25wNcdLsRfw4WYzPVbEU+bkqrPr5L68ins+fX8th0lWfST/fVXhBVnIW9a+eIdXv6IxzMp1HA5zhE+j8RwIAAABIogAJAChLRXUgPlu34aJWduXtRptdSIMXSbKe5Y81ryKed9c1Op+vV+9XalZuU4prejRWaGC+vMvjPTijz+1S6xHS6o+k2KXO1VrZaVJALalee6ntJVLX8a4FpIVPuW5nvvBZyS84Nz4dL635yFkwOxnrfF8Cakp120ltRkrdbpB8CmmWU1pfj5X2/lX0Nd7+UqvhzqJcywvPXsytSJZNkxafrRhlkZr0dRZV21+Ru9q1vJTgc2W1WjTtms4a9e4/ik1IVbaK+L4uxueqePkV9bk62+e+hJ+r9pdLkf3//RwslE7EOIuRfjWczaJaXuj8BwD/Grlz/nnL+Xk5Y+B/XZvTZCRJaz91rpI8vlPKSJb8QqTwVlKrC6UeNzs/ZwAAAFUUBUgAQNnxKaKDsq2IhhqSZMsq/Lm8nZmLKn7ZilgJeLbnz7LKLNtm1/TlcUZssUg39o8qeGF5vAd51Yoq/kqrg+ukDTNz48j+zoLXGVu+l36+R8rOVzRKTZD2LnV+rXhHuvZLqUGn4r1mcdjt7sctXlKzQc6iY9tLnQWbyih/J+W86nV0/h50vKpgN+XyVMLPVYi/j/43vrtGvfOPsrOKWNFZVqs3i/xcne1zX4rPVXAdacijzq+zSdwv/f1abhzWXOp7T2689y/p24lS2gnXeeknpQMrnV/L35Gu+lRqPuTsrwcAAFAJVfA9SwCASqWoAlFRRQDJuYWx0PvmWWlUHq/hxm+bj+hIUm6hZXi7+oqs7aa4YlJ+Z2W3S789oNzGM97SxXkaz+z6Xfru5oLFx/wS90ufj3L+19M6XSMNnSJ1GVt5i49FieglDZsi9b3b3OKjVPT3VyHfty3qhmjaNV3kqyIKgOf6fWvcp6jP1VkKkDlFfO7KIr/5j7iu0Lzopdxt4Yc3Sl9eXbD4mF/6SWnWGOnQ+nPPBwAAoAKiAAkAKDtFbSE8WxfjoppV5G0yEVDrHF6jiOeLaGThcDj08TLXLsWTBjR1f3F5vAelsX66dHhDbtzzFuc2bclZ+PzlPrmcvVirqXTLYumxeOdZd97+uc+ln5R+L8bKsHMVPUv6cKD0Tk9pyUvOrbBVycHV0swrpdfaSHP/K+1fKaO9dHnz8pZ8g90/V8T37YgO9XV33/DC73uu37dnnNPnqojnzzW/PQudXefPaD3SeY7kGb/+x/XMz8Da0vifpMePSTfMccZn5GS4NpYCAACoQihAAgDKTngRnZRT4ouem3LM/XhQXdfz8ALDnA0gSnKP4jxfp3WhT63ee1KbD+UWB7s0rqnukYUUQsvjPSiptJPSomfy3K+ONOSR3HjHXOn0Edc5F78iNeom+fg7z8Trdavr89t/dZ4XWRY6jHZuJS/M8V3Skuelt7tJ/xssrXhXSj5S+PUVTdR5UkTPwp9PTXCeN/jpcOmNTtIfT0lHt5RffmcU9r17ls/VLd2KWJ1YxOeqRMKLuE9pP1cWqxTesvQ55WRJ8/I0nvH2l0Y8nxsfXOda9JecW7qbD3GeYdpskDT4Edfnj2x0zgMAAKhiKEACAMpOgy6FP3diT+HP2XKkU3GF3LNzwbH6hZw/eCqu6PP2isqhiNw/crP60WKxlPg+ZfoelMSiqc5Vi2cMm+q68ivub9fr/WtKzS9wHetwZb6bOqT9y88trzN63izdFy3dOM/Z5MaviFVphzc4V1++3k6afom0brqUfqps8vCUpgOkSQule9ZLA/4rhTYp/Nqk/dI/b0gf9Jfe7S399Yp0cm/h15elwr7PstOk5MOFTvM6Wfj3dXa9juealVNRn4GiPleSdGK3+/HaLc/tjMoV77i+9nn3uxbS45YVnJP/c5T3DNYz9v1dcAwAAKCSowAJACg79TtI3oU0szi0wf24JB3bKtkKOf/Q3cqxxr3cX5uTIcVvLfx18q9GOsMnMHc7cj6xCSlatCN3hVWjmgEa0b5+4a9RXu9BcR3eIK2fkedevaTO17lek7+4VKORZM33I0JNN0WzIopSpRLZT7rsbem/u6QrP5FaDHU2onHHYXcWeH65T3q1lfTVGGnzd+67GlcUtZtLFzwh/WeTNOFXqcs4ybeI1YMJO6Q/n5Xe6iJ9dIG08v2yW3XqTmGfK6noswkL+1xJem1bDTnKYlt5SD3334NS0Z+rtJPSqX3unzuXz1XSIemvV3PjmpFS//+4XpP/8+EbUvAIiYBaBbe+l/XnCgAAoAKgCzYAoOz4BEhtL5E2f1vwuZg/pYxkyd9N04etPxV+T3crhDpeLS15wf31235y36E5I0mKWex+TttLnVuN3bBMv0R7/fIUODIkPSMp8jzpxrkFJ5TXe1AcDofzbEHHv12mLVZp5KvOFt555eTrYuyuM7C7lWL555UVH//cztCn46XN30gbZzmLtO7YsqRd85xfPkFSm4ulDldJLS6QvHw8k+O5sFicqyKbDpAuflXa/ovzvMu9S3N/r/I7tNb59fujUtSA3M7gRZ2NWFJtLpG8/0/KSS/43LafnN/X+dltzu34bqy2t9b7G7PVMGq/xveJdH3yxzuk6K8KTgptIt2/2X1+Ha+Wlk0rOB6/2Xk+aO3mbvL+WS5nm+bV6Wr348Xx+6OuDZtGvFjw/yHF+VxJzs9WVkrh8wAAAKoAVkACAMpWl7Hux3PSpYVTCo6fjJVW/8/9nCb93BcVajeXGvd2P2fVh8575rfwafeFFcm5Es2NU6lZSkgpRTGgPN6D4tjwhbNodUb3G91vZc1/vmRqQsFr3J2jF3AO51IWV0g9qd890p3LpduWSX3udJ6JWZjsVGfxd9a10qstzTlLsSR8A6XO10o3/CTdv9XZ9btOm8Kvd9idhco5dztXfq7/vOxy8a/hvsgoSVt+kA6sLji+/G0p+aDbKd/aBkmSnp6zVatiz9IFujg6j5VUyNEHvz9a8PiFtJOuqxTzCm0iNR1UujxilzgLsme0GOYseueX/3OVdqJgkyGHo2CH7PL4XAEAAJQzVkACQHWz8gNp718Fx4/vKnzOrEIKape+KQXnawjT/HznX+z3Li14/dpPnMWtruOdK7cOb3CuaMq7+sdgkYY+VXhOFzwlTR+pAqubslKkT4ZLAx6QGnaVMpOdhbhtP7u/T/Pznc0g3Phi5T71cqjQmkehyus9KEr6KWfR9YzA2tL5j7u/tn4nacv3uXHiAefKw5B6uWN5C5lnuFtp6kkNOjm/hj3j7D4cPUvaOa/wrevpp85+PuTm75zFtfySDhQ+55f7nNv28zv/caleu6Jfryg1GjrPETzvfueW5+ivpS3fFSxQnWHLdG4FLkuDH5G2zSn4njps0hejpfP+I0X2dz6/9Sdp3Wdub3PIJ0o/ZpwnScqxO3Tnl+s1557z1KhmIccTFEd4C6nrOGnDzILP7ZovfT5K6n2bFFzfuX3979cKLY5q6FMFVwIXhy1b+u3B3NjLT7roJffX5j+r1p7j/Lw36pY7dni9czyv8v5cAQAAlAMKkABQ3RyJlna62TpclMKuH1HINuhLXpfe7+d+K+H2Oc6vs+k+UWrSp/Dno/pLXa93FhfzSz0mzX+o4Hh+PoHSyNfcPpWeZdP05XEq4lS8opXHe1CUP5+V0o7nxhc8WXgn7TaXSIuezt3+67BJK9+Thv1bwLTbnIXrvEKbFN1wx5O8vKXWI5xf6YnS1h+cxboDq0p+r+O7S/55iC1kK3+fO0r++oVp1M35Nfw5afcCaeNXzv/assruNdyp3VwaOFla/GzB57JOS38+U3A8P4tVNa99T1FzcrTnmLOwfiI1S7d+vlbf3d5PAb6FnOtZHMOekXb97n6Vbtwy941f8mt+QemPNVj5nnR8Z27c7+7CVyg3H+I83zHvPy6seEe66tM88buuc3yDpWZDSpcbAABABcYWbABA2avdXLp2pnN1UGm0GFb4qqK8Ln7VudqwNLz9pTFfSmFN3T79zdoDOpl6DsWe8noP3DmySVqbZ2Vaw65S1xsKvz68hdTpWtexf95wNnZZOEX66HzpwErX5wc/LFnPoZBUVgJqSj1ukm5e4OwyPfDBwpuVVEZePlKbkc7v1Qd2Or/nG3X37GsOeKDQYwnOymKVRr2roBb99dENPVTDP/ffurceTtaD3286t6Y0gWHSuO+cndpLo0EX1wJgSSQfkZa+nBvXiHB2NS9MQC2p712uY1u+lz4b6VydPP0S15XHktT37rI91xMAAKCCoAAJAPCMlsOksbOlkIYlm9dlnLPY4l2Mwp2PvzRmVsGuzmdTo5E09ptCi5c5Nrs+WubmHMmSKo/3ID+HQ/rtv85VjJIki3TxtIJdrfO7+FWpYTfXsV3zpL9fl45sdB3vOcm5Fbaiqd1cOv8x6b5N0sS5zhWy7rZKV1aBYVKvW6Rb/pTuXiud939SSBEd2UvLapUue0fqd2/hXcjdCagljf7IOAO1aXiQ3rquq6x5djr/En1YH/51jp+thl2kCXOk8FYlm9dyuPOszdIW+BY87rqacfhzhTeWOWPQQ1Kri1zH9v3t3B6ef7Vmq4ukQQ8KAACgKqIACQDwnOZDpLvXOLd0hhaxKs3L17kt8sZ50uXvlazw5uMvXfGBc27zC5z3KkxoE2cud68p9NxHSZq7+YgOniqkYU1Jlcd7kFf0LNetyF2vlyKKsWLOL9j52v3uKbxoF9LAee7nSDediCsSi0WKOk8a9W7xfu2VUXhL5zmGPW70zP2tVunCZ6Tb/pLaXlZ0ITeortTrNunudQW2Ng9uXVcPjnBtqvPS/B06mnyOn68GnaU7lksXPlt0IdJilZr0la79Uhr3jbNIWhpxfzvP4zyj6SCp/eVnn2f1ksZ85TyztrBVm/6hziMSxnxVMVYVAwAAeIDlHLbBnMP+GQBAtXR0s7PZTUqClJ0mBYU7i1qNezs78JaFjGRnAe70ESn1uOQTIAXVkeq0lup3POt0h8Ohi95cph1HTxtj39zWV72allFnWk+/B2s+dt77jF63OF+jJDJTpH3LpZMxUlaqc8VY3fZSRE/n+YuofrLTpf0rpeTDzvMXrd5ScD3nEQYNuxW5wtbhcOi+rzdqTvRhYyzE31s/39VfzeoEl01+x/dI8VucuWUmOztJB9dzfs/mb5RVGpu/c54Xekana0renT47w3mUQcIuKTNJ8qvhLJ426ev8hxQAAFA5LXjceVSLJNVo4PwH0qqtFJ38KEACAOBi8c5juvGzNUbcrUlNfX9HP1lK0zEXgCRnU6erPliurYeTjbHW9UL00139z60pDQAAgNkoQBYLW7ABAMjjgyUxLvEdg1tQfATOUYCvl/53Qw/VDso9ImFn/Gk9+fMWE7MCAABAeaEACQDAv9btO6VVe08accu6wbqgTV0TMwKqjkY1A/TO2G4uTWm+XXdQ36w9YF5SAAAAKBcUIAEA+Nc7f+52iW8d2ExWK6sfgbLSt3lt/d8w16YxT/68RTuOJhcyAwAAAFUBBUgAACRtOZSkxTtzm7c0qhmgy7s2MjEjoGq6c3ALDWyV2xgmI9uuO79cr5TMHBOzAgAAgCdRgAQAQNI7f+5xie8Y3Fw+XvwxCZQ1q9WiN67tovo1cjs/xyak6pEfNuscmiMCAACgAuNvVgCAam9X/GnN33rUiOvV8NNV3SNMzAio2sKCfPXuuK7yznPEwS/Rh/Xlqv0mZgUAAABPoQAJAKj23l3suvrx1oHN5e/jZVI2QPXQPTJMD41o4zI29Zdt2nIoyaSMAAAA4CkUIAEA1dre46n6JfqwEdcO8tV1vRqbmBFQfUwa0FTD2tUz4iyb8zzI5IxsE7MCAABAWaMACQCo1t5fskf2PMfO3TygqQJ9vc1LCKhGLBaLXr2qsyJqBRhj+0+m6cFvN3EeJAAAQBVCARIAUG0dSkzXD+sPGXENf2+N7xNpYkZA9RMa6KN3x3aTj1fueZDztx7VzJX7TMwKAAAAZYkCJACg2vpwaYxy8ix/nNi/qUL8fUzMCKieOjeuqcdHtnMZe+637YpNSDEpIwAAAJQlCpAAgGrpWHKGvl5zwIiDfL10Y78o8xICqrkb+kZqePvc8yAzsu26/5to5djsJmYFAACAskABEgBQLX20LFZZObmFjev7RqpWkK+JGQHVm8Vi0fNXdFR4sJ8xFn0gUe8ujjExKwAAAJQFCpAAgGon4XSmvshzvpyft1WTzmtmYkYAJKl2sJ9evqqjy9hbf+5W9IFEcxICAABAmaAACQCodj5cGqOM7NzVj9f1aqI6IX5FzABQXs5vU09jezcxYpvdofu/2aiMbJuJWQEAAOBcUIAEAFQrx05naOYq19WPdw5ubmJGAPJ77OK2iqwdaMSxCal6/Y9dJmYEAACAc0EBEgBQrXywJNZl9eO43pGqW8PfxIwA5Bfk563XrukiqyV37KNlsdp0MNG0nAAAAFB6FCABANVGfLLr6kd/H6tuH8zZj0BF1D2ylm4+r6kR2x3Sg99tcmkeBQAAgMqBAiQAoNp4f0mMS/FifJ9I1Q1h9SNQUf3fsNYuW7F3HD2tD5bSFRsAAKCyoQAJAKgWjiZl6KvV+404wMdLtw3i7EegIgvw9dILo127Yr/9527tjj9tUkYAAAAoDQqQAIBq4d3Fe1xWP97QN1LhwXS+Biq6fs3DdV2v3K7Y2TaHHvx+k+x2h4lZAQAAoCQoQAIAqry446malWf1Y6Cvl24dyNmPQGXxyMVtVD9Ps6gN+xP19ZoDJmYEAACAkqAACQCo8qb9sUs5eVZL3dg/SrVZ/QhUGjX8ffTs5R1cxl7+fYdOpmaZlBEAAABKggIkAKBK23IoSb9EHzbimoE+nP0IVEJD29XT0Lb1jDgxLVsvz99hYkYAAAAoLgqQAIAq7eXfd7rEdw1uoRr+PiZlA+BcPHVpO/n75P74+vWaA1q//5SJGQEAAKA4KEACAKqs5THH9deuBCNuEOqv8X0jTcwIwLloHBaou4e0cBl74qctstGQBgAAoEKjAAkAqJIcDodemu+6+vH+oa3k7+NlUkYAysItA5upWXiQEW89nKyZK/eZmBEAAADOhgIkAKBKmr/lqKIPJBpxi7rBGt2tkXkJASgTft5emnJZe5exaQt26hQNaQAAACosCpAAgConx2bXKwtcVz9OHt5a3l78sQdUBQNb1dHFHesbcXJGjt5YuMvEjAAAAFAU/iYGAKhyvlt3ULEJqUbctUlNXdiuXhEzAFQ2j17cVn7euT/Kzly1X7vjT5uYEQAAAApDARIAUKVkZNv0xsLdLmMPjWgji8ViUkYAPCGiVqBuGdDMiG12h577bbuJGQEAAKAwFCABAFXKJ3/v1dHkDCMe3LqO+jSrbWJGADzljsHNVSfEz4iX7EzQ4p3HTMwIAAAA7lCABABUGceSM/Tu4j0uY5OHtzYpGwCeFuTnrQfzfcafm7td2Ta7SRkBAADAHQqQAIAq45Xfdyoty2bEV3WPUPuGoSZmBMDTruwWoQ6NahjxnmMp+mrVfhMzAgAAQH4UIAEAVcLmg0n6bv1BIw709WL1I1ANWK0WPTGyncvYW4t2KyUzx6SMAAAAkB8FSABApedwODT1161yOHLH7hrSQvVq+JuXFIBy07tZbV3Uob4Rn0jN0ifL9pqYEQAAAPKiAAkAqPR+23xUa+JOGXGjmgG6+bymJmYEoLz9d3hreVlzu91/tCxWJ1IyTcwIAAAAZ1CABABUahnZNj3/23aXsUcvbit/Hy+TMgJghuZ1gnV19wgjTsnM0buLY0zMCAAAAGdQgAQAVGqf/L1XhxLTjbhXVJgu7li/iBkAqqr7hraUr3fuj7czV+7TwVNpJmYEAAAAiQIkAKASi0/O0LuL9xixxSI9eWk7WSyWImYBqKoahAZoYr8oI86y2fXGwt3mJQQAAABJFCABAJXYK7/vVFqWzYiv7h6hDo1CTcwIgNnuGNRcIX7eRvzD+oPaFX/axIwAAABAARIAUCltOpio79YdNOIgXy/9d3hrEzMCUBHUCvLVbYOaGbHdIb3+xy4TMwIAAAAFSABApeNwODT1l20uY3ed30J1Q/xNyghARXLTeU0VHuxnxPO2HNW2w8kmZgQAAFC9UYAEAFQ6v246orX7Thlx47AA3dS/qYkZAahIAn29dXueVZCS9OYiVkECAACYhQIkAKBSScvK0YvzdriMPXpRW/n7eJmUEYCK6Po+kaoTkrsK8vet8dp6OMnEjAAAAKovCpAAgErljYW7dSgx3Yh7Nw3TiA71TcwIQEXk7+OlOwY1dxmjIzYAAIA5KEACACqNLYeS9PGyWCP2slr05KXtZLFYTMwKQEU1tncT1auRuwryj23x2nKIVZAAAADljQIkAKBSyLHZ9cgPm2V35I5NOq+p2jcMNS8pABWav4+X7hzcwmXsjYWcBQkAAFDeKEACACqFGSv2aXOelUuNwwJ039CWJmYEoDK4tmdj1a/hb8QLtx/TpoOJ5iUEAABQDVGABABUeAdPpWnagp0uY89e3lGBvt4mZQSgsvD38dJdQ1zPgnznzz0mZQMAAFA9UYAEAFRoDodDT/68VWlZNmNsVJeGGtSqjolZAahMrsm3CnLBtnjtij9tYkYAAADVCwVIAECF9tvmo/pzxzEjDg3w0ROXtDMxIwCVjZ+3l24d2Mxl7L3FrIIEAAAoLxQgAQAVVlJatp6as9Vl7LGL2yo82K+QGQDg3phejRUW5GvEc6IPa9+JVBMzAgAAqD4oQAIAKqwX5+/Q8ZRMI+7TLExX94gwMSMAlVWgr7duPq+pEdsd0gdLY0zMCAAAoPqgAAkAqJBW7z2pWav3G7Gvt1XPX9FRFovFxKwAVGbj+0YqxD+3edV36w7qaFKGiRkBAABUDxQgAQAVTmaOTY/+uNll7O4hLdSsTrBJGQGoCmr4+2hC3ygjzrY59L+/Ys1LCAAAoJqgAAkAqHA+WBKrPcdSjLhl3WDdPqi5iRkBqCpu7B+lAB8vI/5q9T6dyHPUAwAAAMoeBUgAQIWy51iK3s3XnfaF0R3l680fWQDOXe1gP13Xq4kRZ2Tb9dk/ceYlBAAAUA3wtzkAQIVhtzv06I+blWWzG2NjezdRj6gwE7MCUNXcOrCZfL1yfwyesSJOyRnZJmYEAABQtVGABABUGN+uO6DVe08acZ0QPz00oo2JGQGoiuqH+uvK7hFGfDojR1+s2GdiRgAAAFUbBUgAQIWQcDpTz83d7jL29GXtFRrgY1JGAKqy2wc1k9WSG3/y916lZeWYlxAAAEAVRgESAFAhPPPrNiVn5P7l/4I2dXVRh/omZgSgKousHaTLOjc04pOpWfpmzQETMwIAAKi6KEACAEy3eOcxzYk+bMSBvl6aenkHWSyWImYBwLm5c0gLl/ijZXuVnecMWgAAAJQNCpAAAFOlZeXo8R+3uIz998LWalQzwKSMAFQXreqFaGjbekZ8KDFdv+T5xxAAAACUDQqQAABTvf7HLh1KTDfiThGhmtAvyryEAFQrdwxu7hJ/sDRGdrvDpGwAAACqJgqQAADTbDmUpE/+3mvEXlaLXhjdUV5Wtl4DKB/dI2upV9MwI94Vn6I/dxwzMSMAAICqhwIkAMAUOTa7Hvlhs/IuNJp0XlO1bxhqXlIAqqX8qyDfW7JHDgerIAEAAMoKBUgAgCmmL4/T5kNJRtw4LED3DW1pYkYAqqvBreqoTf0QI16/P1Fr4k6ZmBEAAEDVQgESAFDuDp5K02t/7HIZe/byjgr09TYpIwDVmcViKbAK8v0le0zKBgAAoOqhAAkAKFcOh0NP/rxVaVk2Y2xUl4Ya1KqOiVkBqO5GdmygxmEBRrx4Z4K2H0k2MSMAAICqgwIkAKBczd18xKXBQ2iAj564pJ2JGQGA5O1l1a0DC3bEBgAAwLmjAAkAKDdJadmaMmeby9hjF7dVeLCfSRkBQK6ru0coPNjXiH+JPqz9J9JMzAgAAKBqoAAJACg3L87foeMpmUbcp1mYru4RYWJGAJDL38dLN/ZvasR2h/TRslgTMwIAAKgaKEACAMrF6r0nNWv1fiP29bbq+Ss6ymKxmJgVALi6vk+kgv1yG2J9s/aAEk5nFjEDAAAAZ0MBEgDgcZk5Nj3ywyaXsbuHtFCzOsEmZQQA7oUG+GhcnyZGnJlj1/Tle03MCAAAoPKjAAkA8LgPlsQqJiHViFvWDdbtg5oXMQMAzHNz/6by9cr9MfnzFft0OiPbxIwAAAAqNwqQAACP2nMsRe8u3uMy9sLojvL15o8gABVT3Rr+urJ77vm0pzNy9OWq/UXMAAAAQFH42x8AwGPsdoce/XGzsmx2Y2xs7ybqERVmYlYAcHa3DWwma54jaj/5e68ysm3mJQQAAFCJUYAEAHjMt+sOaPXek0ZcJ8RPD41oY2JGAFA8UeFBuqhjAyNOOJ2pH9YfMjEjAACAyosCJADAIxJOZ+q5udtdxp6+rL1CA3xMyggASuaOfGfVfvhXjGx2h0nZAAAAVF4UIAEAHjH1121Kzsgx4qFt6+qiDvVNzAgASqZDo1ANbFXHiPedSNO8LUdMzAgAAKByogAJAChzi3ce0y/Rh4040NdLT4/qIIvFUsQsAKh48q+CfH9JjBwOVkECAACUBAVIAECZSsvK0eM/bnEZ+++FrdWoZoBJGQFA6fVpFqYujWsa8dbDyVq2+7h5CQEAAFRCFCABAGXq9T926VBiuhF3igjVhH5R5iUEAOfAYrHojsEFV0ECAACg+ChAAgDKzJZDSfrk771G7GW16IXRHeVlZes1gMprWNt6al4nyIhXxJ7Qhv2nTMwIAACgcqEACQAoEzk2ux75YbPyNoiddF5TtW8Yal5SAFAGrFaLbs93FuQHS1kFCQAAUFwUIAEAZWL68jhtPpRkxI3DAnTf0JYmZgQAZWdUl0ZqEOpvxL9vjdeeY6dNzAgAAKDyoAAJADhnhxPT9dofu1zGnr28owJ9vU3KCADKlq+3VZMGNHMZ+3BprEnZAAAAVC4UIAEA5+zpX7YqLctmxJd1bqhBreqYmBEAlL0xPRurZqCPEf+08ZAO52m6BQAAAPcoQAIAzsnCbfH6fWu8EYf4e+uJS9qZmBEAeEaQn7cm9I0y4mybw6XxFgAAANyjAAkAKLW0rBw9NWery9hDI9qoToifSRkBgGdN6BelAB8vI561er9OpWaZmBEAAEDFRwESAFBqby3ao0N5th92bVJTY3s1MTEjAPCssCBfjenV2IjTsmyasSLOvIQAAAAqAQqQAIBS2Xn0tD5eltuAwctq0XOXd5TVajExKwDwvEkDmsk7z//rpi+PU1pWjokZAQAAVGwUIAEAJWa3O/TYj5uVY3cYYzf2i1K7hjVMzAoAykejmgEa1aWRESemZevr1QdMzAgAAKBiowAJACixb9cd0Np9p4y4Qai//jOslYkZAUD5un1QM5f442Wxysqxm5QNAABAxUYBEgBQIidSMvXCvB0uY09d2l7Bft4mZQQA5a9lvRANa1fPiA8nZWhO9GETMwIAAKi4KEACAErkhXk7lJiWbcQXtKmr4e3rFTEDAKqmOwY3d4k/WBoje56jKQAAAOBEARIAUGwrY0/ou3UHjdjfx6opl7WXxULjGQDVT7cmtdS7aZgR7zmWogXb4k3MCAAAoGKiAAkAKJasHLse/2mLy9h9F7RS47BAkzICAPPdOaSFS/z2n7vlcLAKEgAAIC8KkACAYvloWaz2HEsx4lb1gjVpQFMTMwIA8w1sGa6OjUKNeOvhZC3afszEjAAAACoeCpAAgLPafyJNby3a7TL27OUd5ePFHyMAqjeLxaJ7L2jpMvbmIlZBAgAA5MXfHAEARXI4HHpyzhZl5tiNsWt6RKhXnnPPAKA6G9q2rto1qGHEmw8lacnOBBMzAgAAqFgoQAIAijR/y1GXv0jXCvTRwxe1NTEjAKhY3K2CfINVkAAAAAYKkACAQqVk5mjKL1tdxh65uK3CgnxNyggAKqYL29VTm/ohRhx9IFFLd7EKEgAAQKIACQAowmsLdik+OdOIe0WF6apuESZmBAAVk9XKWZAAAACFoQAJAHBry6EkTV++14i9rRY9e0UHWa0WE7MCgIprRPv6alUv2Ig37E/UElZBAgAAyNvsBAAAFY/N7tBjP26WPc/CnVsGNlOreiGFT0K5iY2N1cqVKxUfH6/s7Gw1bNhQbdq0UY8ePcxOza3ExEQtXLhQe/fulZeXl1q3bq3zzz9fAQEBJbpPdna2Xn75ZWVnZyssLEz33nuvhzIGSsdqteie81vqnlkbjLFpC3ZqcKs6slj4xxsAAFB9sQISAFDAV6v3K/pgkhFH1ArQvee3LGIGysM333yjDh06qHnz5ho3bpz+7//+Tw899JDGjx+vnj17qkWLFnrvvffKdMvnsWPHFBYWJovFYnxFRUUVe/6LL76oRo0a6eqrr9aDDz6oBx54QJdccokaN26szz//vES5vPHGG3r88cf19NNPy9vbc/+GGhcX5/LrnTJlSonvMX36dJd7LFmypNBrp0yZ4nJt/i8fHx+FhISoSZMm6tWrl8aNG6eXX35ZK1eulN1uL/S+hVmyZInL/adPn17ie6BwIzs2cDkLcsuhZM3fctTEjAAAAMxHARIA4OLY6Qy9PH+Hy9jUUe0V4OtlUkZIT0/XmDFjdO2112rr1q2FXhcTE6O77rpLw4cPV0pKSpm89n/+8x+dOnWqVHPvv/9+PfLII0pLSyvw3IkTJzRhwgS99dZbxbrXoUOHNHXqVElS165ddfvtt5cqp8ooJydHKSkpOnDggNasWaOvvvpKDz30kPr27avGjRvriSeeUEIC23wrCqvVov9e2Npl7NUFO2WzcxYkAACovihAAgBcPDd3u05n5BjxiPb1dX6beiZmVL05HA6NHTtWs2fPNsYCAwN1ww036O2339ZHH32khx9+WC1atDCe/+OPPzRmzBjZbLZzeu3ff/9ds2bNKtXcRYsW6Y033jDiESNG6P3339ebb76pXr16GeOTJ0/Wzp07z3q/Bx54QCkpKbJYLHrvvfdktVbdH2EiIyPVvHlz46tp06YKCwtzu+rz8OHDevbZZ9WqVSt98sknJmQLdy5oW1ddm9Q04piEVP244ZB5CQEAAJis6v70DgAosb93H9fPGw8bcZCvl566rJ2JGeG9997TTz/9ZMRdu3bVjh07NGPGDN19992aNGmSXnjhBW3btk2TJ082rps7d65LAbCk0tLSdMcdd0iS/Pz8SrTtWpJeffVV4/Fdd92lefPm6fbbb9e9996rFStW6KKLLpIkZWVl6c033yzyXosXLzYKsDfeeKP69OlTolwqmyVLlmjPnj3GV2xsrE6cOKHs7Gzt27dPs2fP1s033+xyhmZiYqImTZrk8j0A81gsFk0e7roK8vU/dikz59z+UQAAAKCyogAJAJAkZWTb9MTPW1zG7h/WSg1CS9YoBGUnMzNTzz//vBHXqVNH8+fPV+PGjQtc6+Pjo5dfflnXX3+9Mfb8888rKSmpwLXFMWXKFO3d6+yC/vDDDysyMrJEeS9evFiSc7Vm/jMUrVarXnzxRSOeP39+offKzs7W3XffLUmqWbOmy7zqqEmTJrrmmmv08ccfa//+/brppptcnn/11Vf1wQcfmJQd8urXPFzntQg34kOJ6Zq95oCJGQEAAJiHAiQAQJL0wdIY7T2easRtG9TQxH5R5iUE/fnnnzp8OHdF6uTJk1W3bt0i57zwwgvGVt2TJ0+WqsFIdHS0Xn/9dUlSixYt9Mgjj5Ro/p49e5SZmSlJ6tKli8LDwwtc06lTJ9WvX1+StHfvXrfnRErSm2++qW3btkmSnn32WdWpU6dEuVRl4eHh+uSTTwqco3nPPfdoz549JmWFvP6bbxXkW4v2KC0rp5CrAQAAqi4KkAAA7T2eqvcWxxixxSI9f0UHeXvxx4SZ8ndOvvLKK886JyIiwmWL8vfff1+i17Tb7br11luVk+Mskrz33nvy8/Mr0T0SExNd8ilM3pWceeeccfjw4WrbeKYk7rnnHpeVkDk5OXruuedMzAhndGlcUxe2yz1D93hKpmYs32diRgAAAObgb5YAUM05HA498dMWZdnsxtjYXk3UtUktE7OCJMXFxRmPg4OD1axZs2LN69Spk/H4n3/+KVEX63fffVerV6+WJF177bUaNmxYseeekbdgefr06UKvy/ucv79/gef/+9//6vTp07JYLHr33Xfl5UUn9sK89NJLLu/hzJkzdfToURMzwhkPXNhaFktu/MHSGCWlZ5uXEAAAgAkoQAJANTcn+rD+3nPciMODffXg8DYmZoQz8hYOQ0NDiz2vZs2axmO73a4tW7YUfnEehw4d0mOPPSZJqlGjhrENu6QaNmxoPN61a5fbazIzM7Vvn3MlWEBAgEvOknP155kO3BMnTlTfvn1LlUt1ER4errFjxxpxTk5OgRW0MEfr+iG6vEsjI05Kz9bHy2JNzAgAAKD8UYAEgGosKT1bz/y63WXs8ZHtFBroY1JGyCtvl+OMjIxiz0tPT3eJt2/fXsiVru6++25jVeKzzz6rBg0aFPs182rYsKGxvTomJkZ//PFHgWs+++wzI8+ePXvKas39kSQnJ4fGM6WQf7Xq0qVLTcoE+f1naEt5W3OXQX68bK/ik4v/mQYAAKjsKEACQDX26u87dTwl04j7Na+tUV0aFjED5Slvw5WTJ08Wu6P1me7VZ8TGnn211Y8//qiffvpJktStWzfdeeedxU/UjfHjxxuPb731Vq1du9aI58+f79LY5oYbbnCZ+9Zbb2nr1q2SnIXQszXegVPesz8lacOGDSZlgvwiawfp2p65Z56mZ9s0bcFOEzMCAAAoXxQgAaCa2nggUTNX5TZD8PWy6pnLO8iS97AymKp79+7GY4fDoT///POsc7KysrRs2TKXseTk5CLnnD59Wvfcc48kyWq16v333z/n8xYfeOABYwVlXFycevbsqQYNGig8PFwXXXSR0XSma9euLgXII0eOaMqUKZKcHbQrQuOZp59+WhaLpURfN954Y7nnGRkZ6bKS9Pjx40VcjfJ239CWCvLN/Vx9u+6gth8p+rMJAABQVVCABIBqKMdm12M/bpbDkTt2x+Dmal4n2LykUMCwYcNcCsKvv/66HHl/09z47LPPdOLECZexohrBSNKjjz6qQ4cOSZJuu+029erVq5QZ5woLC9Ovv/7qsorz6NGjLrm1bt1aP/30k3x8crf8n63xTGpqqv7++2/98ssvWrFihTIzMwUni8WikJAQIz558qSJ2SC/uiH+un1QcyN2OKTnf9t+1s80AABAVeBtdgIAgPL3+Yp92no4d+VNVO1A3TG4eREzYIYWLVrokksu0S+//CJJWrZsmZ588kk988wzbq9fs2aNJk+eXGA8/5mQea1atUrvvfeeJKlevXp6/vnnyyBzp27dumnbtm169dVXNWfOHMXFxcnLy0utWrXS1VdfrXvvvVeBgYHG9X/99Ze++uorSdKECRPUr18/47nExEQ98sgjmj59ust5mMHBwbr33nv15JNPunTfLku1atVSWFhYieacPn1ax44d80g+RQkODja26p+t8IzyN2lAM325ar+O/nv+47Ldx7VkV4KGtOaYAQAAULVRgASAauZoUkaBs8eeubyD/H3ObcstPOPVV1/VkiVLXJrDbNiwQffff7969Oghf39/xcTE6Ouvv9a0adOUlpYmb29veXt7G4W64GD3K1tzcnJ06623ym63S5KmTZtWoBv1uQoPD9eLL7541kYyOTk5uuuuuyQ5G8+89NJLxnOJiYkaPHiwoqOjC8xLSUnR888/r7Vr12ru3Lny9i77H23uvfdeY1t4cU2fPt2Ubdh5i441atQo99dH0QJ8vTR5eGs98G3u9/Lzc7drQItweXuxMQkAAFRd/KQDANXM1F+3KjXLZsSXdW6oAS3rFDEDZmrVqpW++uorl47Yc+fO1dChQ1WzZk35+/urffv2euaZZ5SWliZJeuedd1y2NRdWVJw2bZo2bdokSRoyZIjGjRvnuV/IWbz99tvasmWLJOmZZ55xaTxz3333GcXH888/X5s3b1ZGRoZWrVqlzp07S5IWLFigF154ofwTr0DsdrtLAbKkqzZRPq7o2kjtG+YWh3cfS9HstQdMzAgAAMDzKEACQDWyeMcx/bb5qBGH+Hvr8UvampgRiuOSSy7RX3/9pW7duhV5XVhYmGbPnq3rr7/epRAVHh5e4NrY2Fg9/fTTkiRfX19jG7YZjh49aqww7Ny5s+644w7jubi4OM2cOVOS1LBhQ/3666/q0KGD/Pz81KtXL/3222/G1uszK0Crq3379rmcJ+ju9x3ms1otemyk6/93py3YpaS0bJMyAgAA8DwKkABQTaRn2fTknC0uYw8Ob626If4mZYSS6NGjh9auXasFCxboP//5j4YMGaKOHTuqW7duuvzyy/XBBx8oJiZG11xzjbZv3+4yt0uXLgXu98ADDxhnQ06ePFlt2rQpj1+GW5MnT1ZycrLbxjM///yzsUX8jjvucFkJKjmLkmPHjpUkJSUlaeHCheWXeAWzYsUKlzhvF3VULP2ah2to23pGfDI1S6/9sbOIGQAAAJUbZ0ACQDXxzuLdOnAytxlJ54hQje0daWJGKCmLxaJhw4Zp2LBhRV63atUql7hnz54Frtm7d6/x+PPPP9fXX39d5D3PdMk+87hFixZGPGzYML3//vtFzi/MsmXLjBWON9xwg/r37+/y/Lp164zHvXv3dnuPPn366LPPPpMkrV+/XpdddlmpcqnsFixY4BIPGjTIpExQHI+PbKu/diUoy+YssH+xcp/G9Gqitg04uxMAAFQ9FCABoBrYHX9a//sr1oitFum5KzrKy2oxMSt4yrx584zH7du3V7169Yq4WjpwoGTnz+Xk5CgmJsaIO3ToULIE/2Wz2YzGM6GhoS6NZ85ISEgwHkdERLi9T97xvNdXJwkJCZo9e7YR+/j4aPDgweYlhLOKCg/SrQOb6Z3FeyRJdof01M9bNfu2PrJY+H8zAACoWtiCDQBVnMPh0GM/bVG2LfdsuAn9otShUaiJWcFTjhw5ovnz5xvxzTffbGI2RXvnnXe0efNmSc7GM+4KpWe2X0sytoznl3fcZrO5vaaqe/jhh42u55I0YcIE1alDc6mK7s4hzdUwNPcYjNVxJzUn+rCJGQEAAHgGBUgAqOK+X39Iq/eeNOJ6Nfz0f8NamZgRPOmRRx4xinCBgYEaP3682+s2btwoh8NR7K+823kjIyNdnvvpp59KnGd8fLyeeuopSc7GM3feeafb6/J2ct6/f7/ba/Ku4KyOnZ/ffvttffrpp0bs7e2tRx55xMSMUFyBvt56bGQ7l7Hnf9uulMwckzICAADwDAqQAFCFnUrN0vO/uTYkeerS9grx9zEpI3jSzJkz9fnnnxvx1KlTK2wn5MmTJyspKclt45m8OnbsaDz+/vvv3V7z3XffGY87depUtolWYCdOnNCkSZN07733uoy/++67atasmUlZoaQu7lhf/ZrXNuL45Ey9/eduEzMCAAAoexQgAaAKe3HeDp1MzTLiwa3r6KIO9U3MCCWVnZ2tp556SgcPHiz0mszMTE2dOlUTJ06Uw+Hcat+rVy/95z//KacsS+bvv//WF198IUkaP358gcYzeY0cOdJ4PHv2bG3cuNHl+d9++03//POPJMnPz08XXHBB2SdcgRw4cEDffvutJk2apMaNG+uTTz5xef7hhx/WrbfealJ2KA2LxaIpl7V3OZP307/3KiYhxcSsAAAAyhZNaACgiloVe0Kz1+ZuTfXztmrqZR1oblDJ2Gw2TZ06Vc8884y6d++ufv36qWXLlgoODtaJEye0bds2/fLLLy7NVzp06KC5c+cWuqrQTDabTXfffbckZ+OZl19+ucjrO3furKFDh2rhwoXKzs7WwIEDddddd6lly5aKjo7WBx98YFw7ceLEKnHu4eDBg+Xtnfsjmt1uV3JyspKSkpST435rbq1atTRt2jTdeOON5ZUmylCreiGa2C9Kn/zt7E6fbXPo6V+2acaNPfl/NgAAqBIoQAJAFZSZY9OjP252Gbv3gpZqUjvQpIxwrhwOh9auXau1a9cWed2IESM0Y8aMCrv1+t1331V0dLQk5xbxs3XolqSPPvpIffr0UXx8vE6fPq0XX3yxwDXt2rU7azGzsti3b1+xr23YsKFuvvlm3XvvvRX29xzFc9/Qlvp542EdT8mUJP21K0G/b43XCFatAwCAKoAt2ABQBf1vaaxiElKNuFW9YN0ygDPhKiMfHx9NmDBBERERhV5jsVjUp08fff3115o3b57q1q1bjhkW37Fjx/Tkk09Kcp7VeNdddxVrXlRUlJYtW1boVu3LLrtMS5YsUY0aNcos14rEy8tLgYGBatSokXr06KHrrrtOL730klauXKmDBw9W6LM+UXw1/H308EVtXMaemrNFpzOyTcoIAACg7FjOnBVVCqWeCADwnL3HUzX8jb+UlWM3xr67va96RFW/7sBVzc6dO7Vjxw7Fx8frxIkTCg0NVYMGDdSzZ88iC5QVxbJly7Ro0SJJ0qhRo9S1a9cS32PDhg1auXKlTp06pTp16mjQoEFq1Yqu7qga7HaHrvlwhdbuO2WM3dA3UlNHdTAxKwAAUKQFj0vJR5yPazSQLnzW3Hw8r1Tnw1CABIAqxOFw6PpPVumfPSeMset6NdELozsWMQsAUFHsjj+ti99apmyb80dti0X67vZ+6h5Zy+TMAACAWxQgi4Ut2ABQhfy08ZBL8TE82FcPj2hTxAwAQEXSsl6I7hjcwogdDumRHza5rGoHAACobChAAkAVcSo1S8/8ut1l7IlL2ik00MekjAAApXHn4OZqVifIiHfFp+jDpTEmZgQAAHBuKEACQBXx4rwdOpmaZcQDWobrss4NTcwIAFAa/j5eeuEK16Mz3v5zj/YcSzEpIwAAgHNDARIAqoBVsSc0e+0BI/bzturZyzvIYinV8RwAAJP1blZb1/VqbMRZNrse/C5aNjvHsAMAgMqHAiQAVHKZOTY9+uNml7F7L2ipyNpBhcwAAFQGD1/UVnVD/Ix4/f5EffbPXhMzAgAAKB0KkABQyf1vaaxiElKNuFW9YN0yoJmJGQEAykJogI+ez7cV+5Xfdyo2ga3YAACgcqEACQCVWGxCit5evMdl7PkrOsrXm/+9A0BVMLRdPV3RtZERZ+bY9eB3m9iKDQAAKhX+hgoAlZTd7tBD329SVo7dGLuuVxP1iAozMSsAQFl76tJ2Cg/O3Yq9dt8pTV8eZ15CAAAAJUQBEgAqqZmr9mlN3CkjDg/208Mj2piYEQDAE2oG+ur5Kzq4jL3y+w66YgMAgEqDAiQAVEIHT6XppXk7XMaeGdVeoYE+JmUEAPCkC9vX12WdGxpxRrZd/5m9wWUVPAAAQEVFARIAKhmHw6FHftis1CybMXZRh/q6qGMDE7MCAHja05e1d+mKveVQst5ctMvEjAAAAIqHAiQAVDLfrTuoZbuPG3FogI+eHtXexIwAAOWhVpCvXrm6s8vY+0titCbupEkZAQAAFA8FSACoROKTM/TMr9tcxp68pJ3qhviblBEAoDwNalVHE/tFGbHdId0/e6NOZ2SblxQAAMBZUIAEgErC4XB2vU7OyDHGBrWqo9HdGpmYFQCgvD18URu1qBtsxAdPpWvKnG1FzAAAADAXBUgAqCRmrzmgJTsTjDjEz1vPj+4oi8ViYlYAgPLm7+OlN67tIh+v3P//f7/+oOZuOmJiVgAAAIWjAAkAlcCBk2kFt15f2k6NagaYlBEAwEwdGoXqgQtbu4w9+uNmHU3KMCkjAACAwlGABIAKzm536L/fRrt0vR7atq6u6h5hYlYAALPdMqCZejcNM+Kk9Gw98O1G2e0OE7MCAAAoiAIkAFRw05fHadXe3A6ntQJ92HoNAJCX1aLXru2iEH9vY+yfPSf0/tIYE7MCAAAoiAIkAFRge46l6KX5O1zGnr28I12vAQCSpEY1A/Ts5R1cxl77Y5fW7TtlUkYAAAAFUYAEgAoqx2bXA99GKzPHboxd2rmhRnZqYGJWAICKZlSXRro6z7EcNrtD987aoKT0bBOzAgAAyEUBEgAqqA+Wxij6QKIR1wnx09TL2puXEACgwnp6VHs1qxNkxIcS0/XID5vkcHAeJAAAMB8FSACogNbtO6XXF+52GXvpyo6qFeRrUkYAgIos0Ndbb1/XVb5euT/e/7b5qL5ctd/ErAAAAJwoQAJABZOUnq17Z22QLU8X02t7NNb5beqZmBUAoKJr3zBUj41s6zI29Zdt2nQw0ZyEAAAA/kUBEgAqEIfDoYe/36RDienGWLPwID15aTsTswIAVBY39I3UsHa5/2CVZbPrjpnrlZiWZWJWAACguqMACQAVyJer9mvelqNG7Otl1dtjuyrIz9vErAAAlYXFYtGrV3VW47AAY+xQYrrun71RdjvnQQIAAHNQgASACmLH0WRN/XWby9hjI9uqfcNQkzICAFRGoYE+en9cd/l65/6ov3hngt5bssfErAAAQHVGARIAKoDTGdm6c+Z6ZeXYjbEL29XTDX0jTcwKAFBZdWgUqqmXtXcZe+2PXfpnz3GTMgIAANUZBUgAMJnD4dCD321S7PFUY6xRzQC9fFUnWSwWEzMDAFRm1/ZsrKu6Rxix3SHdO2uDjiZlmJgVAACojihAAoDJPl621+XcRx8vi966rqtqBvqamBUAoLKzWCx6ZlQHtakfYoydSM3SnV+uc1lxDwAA4GkUIAHARKtiT+jF+Ttcxh4f2U7dI2uZlBEAoCoJ8PXSB9d3V0ieZmbr9yfq2bnbipgFAABQtihAAoBJjiVn6O5ZG2TL05X0ss4NOfcRAFCmosKD9Oo1nV3GPl+xT9+sOWBSRgAAoLqhAAkAJsjItumWL9Yp4XSmMdaybrBeGN2Rcx8BAGVuePv6un1Qc5exx3/aog37T5mUEQAAqE4oQAJAOXM4HJr83SZFH0g0xoJ8vfT+9d0VlGeLHAAAZWny8NYa2KqOEWfZ7Lp95jodS6YpDQAA8CwKkABQzt5ctFu/RB82YotFeu3aLmpRN9jErAAAVZ2X1aK3x3RVZO1AYyw+OVN3fLmepjQAAMCjKEACQDmaE31Ybyzc7TL24PA2Gt6+vkkZAQCqk9BAH/1vfA8F+noZY+v2ndKUX7aamBUAAKjqKEACQDlZt++k/vtttMvYld0idPugZiZlBACojlrXD9Fr+ZrSfLVqv75ctc+kjAAAQFVHARIAysGu+NO6afpaly1uvaLC9PzoDjSdAQCUuxEdGuie81u4jE2Zs1UrY0+YlBEAAKjKKEACgIcdTkzXhE9XKyk92xhrHBag96/vJj9vryJmAgDgOfcPbaUL2tQ14mybQ7fPXKe9x1NNzAoAAFRFFCABwINOpWbphk9X60hSbofR2kG++vym3qod7GdiZgCA6s5qtej1MV3UvE6QMZaYlq2bp69RYlqWiZkBAICqhgIkAHhIamaObpqxRnuOpRhjQb5emn5jLzUNDypiJgAA5aOGv48+ndhTtQJ9jLHY46m6YyadsQEAQNmhAAkAHpCeZdNN09dow/5EY8zHy6IPx/dQx4hQ8xIDACCfyNpB+nB8D/l45Z5JvCL2hJ74aYscDoeJmQEAgKqCAiQAlLGMbJtu+XytVu09aYxZLNJr13TReS3DTcwMAAD3ejUN04ujO7mMzV57QB8tizUpIwAAUJVQgASAMpSZY9NtX6zT33uOu4w/d3lHXdq5oUlZAQBwdld2j9BdQ5q7jL0wb4d+33rUpIwAAEBVQQESAMpIRrZNd85cr6W7ElzGn76svcb2bmJSVgAAFN8Dw1rr4o71jdjhkO77eoPW7TtZxCwAAICiUYAEgDKQmpmjm2es0aIdx1zGHx/ZVhP6RZmTFAAAJWS1WjTt6i7qnOe84oxsu26avla74k+bmBkAAKjMKEACwDlKSs/W+E9W6Z89J1zGJw9vrUkDmpmUFQAApRPg66WPJvRQ47AAYywpPVs3fLJahxLTTcwMAABUVhQgAeAcHE/J1HX/W6n1ebpdS9IjF7XRXUNamJMUAADnqG6Ivz6/qbdqB/kaY0eTM3TDJ6t0MjXLxMwAAEBlRAESAErpSFK6rv1whbYdSTbGLBbp2cs76LZBzYuYCQBAxdc0PEjTb+ylIF8vYywmIVU3TV+jtKwcEzMDAACVDQVIACiFfSdSdfUHKxSTkGqMeVkteu2azrq+T6SJmQEAUHY6RoTqw/E95ONlMcY2HkjUnV+uV7bNbmJmAACgMqEACQAltH7/KY1+b7kOnso9B8vXy6p3x3bTFV0jTMwMAICyd17LcL1+bRdZcmuQWrIzQffP3iib3WFeYgAAoNKgAAkAJTB/yxFd97+VOpHn/Ct/H6s+ntBDIzrUNzEzAAA855JODTXl0vYuY79uOqLJ30XLThESAACcBQVIACgGh8Ohj5fF6o4v1yszJ3fLWWiAj764ubcGtqpjYnYAAHjehH5Ruvd81wZrP6w/pEd/3EwREgAAFMnb7AQAoKKz2R165tdtmr48zmW8cViAPpvYSy3qBpuTGAAA5ez+Ya2Unm3TR8v2GmNfrzkgHy+rpo5qL0vefdoAAAD/ogAJAEVIzczRfV9v1MLt8S7jnRvX1CcTeig82M+kzAAAKH8Wi0WPXtxW2TaHyz/MfbFyn3y9rXp8ZFuKkAAAoAAKkABQiLjjqbr1i7XaFZ/iMn5hu3p6c0xXBfh6mZQZAADmsVgseurSdsrMsWvW6v3G+Cd/75Wft1WTh7emCAkAAFxQgAQANxbvOKZ7v96g0xk5LuM39W+qx0a2lZeVv1gBAKovi8Wi5y7voGybXd+tO2iMv7ckRja7Qw9f1IYiJAAAMFCABIA87HaH3l28R68t3CVHnvP0vawWPTGyrSb2b2pecgAAVCBWq0UvXdlJ2Ta7ft542Bj/8K9YpWTm6JlRHWTlH+wAAIAoQAKA4XRGth74JloLtrme91g7yFfvjO2mvs1rm5QZAAAVk5fVomlXd1aOzaG5m48Y41+u2q/0LJtevqqTvL2sJmYIAAAqAgqQACBpz7EU3fbFWsUkpLqMd4oI1QfXd1fDmgEmZQYAQMXm7WXVm2O6yN/HS9+vz92O/cOGQ0rLsunN67rIz5tzkwEAqM7450gA1d6CrUd1+bv/FCg+XtU9Qt/c1pfiIwAAZ+HtZdUrV3XSDX0jXcbnbz2qWz5fp/Qsm0mZAQCAioACJIBqy2536LU/dunWL9YpJTO32Yy31aJnRrXXK1d1kr8PKzYAACgOq9Wipy9rrzsGN3cZ/2tXgiZ8ulpJ6dkmZQYAAMxGARJAtZSUnq1bPl+rtxbtdhkPD/bTrFv7aHzfKLp3AgBQQhaLRQ+NaKPJw1u7jK+OO6lrPlihI0npJmUGAADMRAESQLWzK/60Ln/3Hy3accxlvGuTmvr1nvPUMyrMpMwAAKga7hrSQk9d2s5lbGf8aV353nLtjj9tUlYAAMAsFCABVCvzNh/R5e/+o73HXc97vK5XE319ax/VD/U3KTMAAKqWG/s31WvXdJa3NXdHweGkDF31wQqt23fSxMwAAEB5owAJoFqw2R16ef4O3fHleqXlOQjfx8ui56/oqBdGd6RDJwAAZWx0twh9PKGHAn1z/4xNSs/W2I9W6Y9t8SZmBgAAyhMFSABVXmJalm6cvkbvLYlxGa9Xw09f39pXY3s3MSkzAACqvsGt62rWLX1UO8jXGMvMseu2L9Zq5sp9JmYGAADKCwVIAFXa9iPJuvSdv/XXrgSX8Z5RtfTLPeepe2QtkzIDAKD66Ny4pr67o58ahwUYY3aH9PhPWzRlzlbl2OwmZgcAADyNAiSAKmtO9GGNfm+5Dpx07bh5Q99IfTmpj+qGcN4jAADlpWl4kL6/o5/aN6zhMj59eZxumrFWSenZJmUGAAA8jQIkgConx2bX879t172zNig9O/e8R19vq165qpOmjuogX2/+9wcAQHmrG+Kv2bf11ZDWdVzG/9qVoNHv/aO4fE3iAABA1cDfwIH/b+++w6Os8v//v046qQQSIJDQm9IFbKBYEVnFAogF7HVt635W/a1lsf10XfXzWV11XVcXd62rqICuqMiiFFGK0gWlEwIJJY2E1DnfP2YymQmZMGRmMgk8H9eVK/c5c859Tq5LD/e871NwVCkordC105bq1fmbvfIzUuI0/dZTNHFYVph6BgAAJCkxNkqvXTNcN47s5pW/aU+JLn55kb7dtDdMPQMAAKFCABLAUWPD7mKNe3GRFm70/uJyUrc2+uTOkRqY2To8HQMAAF4iI4weuuB4PT1+gKIjjTu/oLRSV7++RG8u3iprbRh7CAAAgokAJICjwudrduuSlxdp+/5Sr/zrRnTVWzeepLTE2DD1DAAA+DJpeGe9dcNJSo2PdudVOawenrlW905fpTKPrVQAAEDLRQASQIvmcFj935yfdetby1Va4b3f43MTB2nqhf0UHclQBwBAc3VS97aaeftI9WqX6JU/fXm2Jr6yWDsLDvqoCQAAWgq+lQNosQ6UV+nWt5br+bm/eOW3T47V+7ecovFDM8PUMwAAcCQ6t43XR78+VaOPb++Vv3pnoS78y0L2hQQAoIUzAeytwqYsQJg5HA4tWrRImzZt0u7du5WamqqsrCyNGjVKCQkJYenTgQMHtGjRIu3cuVN5eXlKSkpS+/bt1blzZw0ePFgxMTGNvre1VsuXL9cvv/yidRu36d9Lt2m/TVBkQqpi2nVTZHyKTujcWq9MHqp2yXFB/KsAAEBTcDisXpq3Uf/71c/y/JoSGWH0+/P76oaR3WSM8X2DeuTn52v+/PnKzs7WgQMH1LFjR/Xt21fDhw8Pcu8bVl1drdWrV2vlypXau3evysrKlJycrMzMTA0fPlyZmbw4BYAW6cuHpKJdzuvkDGn0E+HtT+gd2T/ELlHB7gWA0Kuurtazzz6rF154QTk5OYd8npCQoCuuuEJ/+tOflJqa2iR9WrFihR577DHNnj1bZWVl9ZaJjY3VmWeeqRdffFE9evTw+97FxcV66qmn9NZbb2nHjh0+y6Vl9dDYRx5Uu+QRR9x/AAAQfhERRnee3Uv9M1N097s/qqisSpJU7bB64j8/aVV2of44foDiYw7/NWbHjh36n//5H82cOVMVFRWHfN6zZ0/df//9uvHGG4P+d3gqLi7WH//4R73++uvKzc31WW748OG69957NXHixKC0+/e//10333yzV97UqVP1yCOPBOX+AAAcCWZAAi1MQUGBLrjgAi1atOiwZTMzMzVr1iwNGTIkZP2prq7WAw88oOeee07V1f5tFD9nzhydc845fpe9/vrrlZ2d7Vf5q666Sm+99ZZfZQEAQPO1dW+Jbn1rudbvLvbK79shSa9OGabObeN91v3yyy81adIkFRQUHLadSy65RO+9915AqzR8Wbt2rcaOHavt27f7XWfChAl6++23A+pPbm6ujjvuOOXn53vlE4AEgBBgBqRfmAEJtCBVVVWaOHGiV/Cxc+fOmjx5srp27ao9e/ZoxowZWrp0qSQpOztbF1xwgZYuXaqOHTsGvT8Oh0PXXXed3nzzTXdeXFyczj77bJ166qlq3769KisrtXPnTi1btkxff/21z9mR9fnss890ySWXeM1aiE7vqlbdhyoyKU0R0bGKrSrVoMRirV66yO8gJQAAaP66piXoo1+fqvumr9Knq3a589fvLtaFLy7U85cP1hl92h1Sb/Xq1ZowYYKKi2sDl+eee67OOeccpaSkaP369XrzzTe1b98+SdLHH3+sW265RdOmTQtq//Py8nT22Wd7zXps06aNJkyYoIEDByo+Pl55eXmaN2+evvzyS9VMDJk+fbpiY2MDeqH6m9/85pDgIwAA4cQMSKAF+dOf/qT777/fnb7yyis1bdq0Q96Qv/DCC/rNb37jfpAdO3as/vOf/wS9P/fdd5+eeeYZd/qSSy7Riy++6DPYWVpaqnfeeUcnnXSSBgwY0OC9f/jhB5166qkqLy+XJLVKba+kc36tVt2Husv07ZCkv189TFltnDMgFi1apI0bN+qaa64J9E8DAADNhLVWry3Yoqdm/ySHxzcQY6Q7z+qlu8/upcgI52QMh8OhQYMGac2aNZKc27+8/fbbGj9+vNc9i4qKdPHFF2vevHnuvPfffz9oy58l6eabb9bf//53d3rs2LF65513lJKSckjZRYsWady4cdq/f7877+uvv9aoUaOOuN3PP/9c559/viSpb9++Wr9+vfszZkACQAgwA9K/SgQggZahqKhI3bp1cz+YDhkyREuWLFFUVP0Tme+88069+OKL7vTChQs1YkTw9kZctmyZTj75ZPey6+uuu06vv/76EW8MX5/q6mqdeOKJ+uGHHyRJMSntlH7lHxWVXDvL4VcDMvTMxIF+7QEFAABavkUb9+qOd35QfmmlV/6Inm3150lDlJ7knDU4ZcoU92fPPfecfvvb39Z7v8LCQvXr1087d+6UJPXp00dr165VZGRkwH2tqKhQenq6ioqKJDm3xdmwYYPi430vG585c6Yuvvhid/qmm27Sq6++ekTtlpaWql+/ftq6datiYmI0a9YsjRkzxv05AUgACAECkH6JCHYvAITGW2+95fVW/E9/+pPP4KMkPfHEE14Puc8//3xQ+3PHHXe4g489evTQyy+/HJTgo+TcNL0m+ChJrc+70x18NEa697w+evHKIQQfAQA4hozomaZP7hypAZ28ZxAu2rhPv3phgb7fvE8vvPCCO79z5866++67fd4vJSXFKxi3YcMGffHFF0Hp66ZNm9zBR8m5aqWh4KMkjRs3Tu3a1b5sXbly5RG3O3XqVG3dulWSdP/996tPnz5HfA8AAEKBACTQQsyYMcN93bVrV5199tkNlk9JSdGECRPc6c8//7zeEyAb48cff9T333/vTj/66KOKi4sLyr0l6eW//tV9HddlsFp1cx6ikxgbpdeuHqbbz+wZtGAnAABoOTJT4/XBrado8smdvfLziss18X8/1bJly9x511133WFnM15++eVegcGZM2cGpZ+eL40l58vawzHGqHv37u70ke7huGLFCv35z3+WJHXv3l0PPPDAEdUHACCUCEACLcDBgwf19ddfu9PnnHOOXwG4c889131dXFysBQsWBKU/r7/+uvs6OTlZl156aVDuK0lfzf9Wq1etcqcTBzpPy+6elqAZt4/Q2ce1D1pbAACg5YmLjtQTFw/Q85cPVnxMbYCxZNNyeW4v5fkc5EtiYqJOOeUUd/qzzz4LSh9TU1O90iUlJX7V8yyXnp7ud3sOh0M333yzqqqqJEkvvfRSUF8OAwAQKAKQQAuwfv16VVbW7nd08skn+1XP84Facp4KGQxz5851X48aNUqtWrUKyn3X5hTqhqe8T6CM63aCzuiTro9vH6Ge7RKD0g4AAGj5LhrcSbPuGKne7Z3PB5V7tro/MxGRimp3+FmHkvfzUnZ2dlBOj+7Tp49XENLzRbIveXl5WrdunTt9+umn+93eiy++qKVLl0qSJkyY4LXvIwAAzQEBSKAF+Omnn7zSPXv29Kte165dvZYe1b1PYxQVFWnDhg3udE0wtKioSC+99JJOO+00ZWRkKDY2Vh07dtTpp5+uJ554Qjk5OQ3e95OVORr/12+1d3Ptg3dUakfdPmaIXr9muL5fME9XXHGFevbsqVatWqlNmzbq16+fbrvtNr8e6gEAwNGnZ7tEzbh9hC49oZMq92W78yOS0jT5jR80bdEWHe7QzbrLoz1PjW6syMhI3XLLLe70J598oq+++qrBOvfcc497f+34+HjdeuutfrWVnZ2thx56SJKUlJTkXoYNAEBzQgASaAG2bNnile7cubOPkt4iIyOVkZHhTm/evDngvqxatcrrQb537976+uuv1b9/f91xxx1auHChdu/erYqKCu3atUsLFizQww8/rJ49e+rJJ5885H7VDqunP1+vO9/9UWWVDlXk1f6tg/sfp5tOTNeE8ZfqvPPO03vvvadNmzaprKxM+fn5WrdunV555RWdeeaZGj16tHJzcwP++wAAQMsSHxOl5yYOUuvq2pmLUcnpqqy2evSTdbr1reUqKPW9D3ZWVpZXOhjPS5L08MMPa/DgwZIka60uvPBCPfnkk9q9e7e7jMPh0Pfff6+xY8fqnXfekeTcC/LVV19Vly5d/Grn9ttvV3FxsSTpscceU6dOnYLSfwAAgokAJNACeJ6iKB26r1BDPMvWPJwGYs+ePV7pTZs2acyYMdqxY4c7Ly0tTRkZGYqIqB1iDh48qAcffFDXX3+9O6+orFI3/nOp/vr1JndedWmh+7p3Vnudf/75XgfwJCQkKCsr65CTJOfMmaOTTjrJqx8AAODYYIyRo7zUnY6Iq9225Yu1uRr7/AIt3bq/vqqHPFcF43lJcs5inDt3rnuv7LKyMj344IPKyMhQ+/bt1bVrVyUnJ+vkk0/W7NmzJTkPj/nss8901VVX+dXGRx99pFmzZkmSBg0apDvvvDMofQcAINgIQAItwIEDB7zSR7KpuOf+jHXv0xgFBQVe6Ycffljl5eWKjIzUfffdpx07dmjPnj3KycnR3r179ec//1lJSUnu8tOmTdNLL72kjXkHdPGLizRvQ21A01qHbOVBd/qDDz5w72c0YsQILViwQMXFxdq+fbuKioo0d+5cDR061F1+27ZtmjRpknsDdgAAcOzwfM7p1DbJ67OcwjJN+tti/WXuL6p2eC/JrruXdTCel2q0adNGH374of773/+qV69e7vy8vDxt27bN69CZq666SkuXLvV7/8aioiLdddddkpwB2FdeeeWwp34DABAuBCCBFqCsrMwrHRMT43fd2NhY9/XBgwcbKOmfuqc41hyO8+abb+rpp59WZmam+7PU1FTdfffdmjdvnteMxf/vgQc17n/naPNe73tNGtxO8ljeXXPvCy64QPPmzdPIkSPdp39HRkbqrLPO0oIFCzRq1Ch3ncWLF+u9994L+O8EAAAti+fz0im9Oujxi/srJqr2647DSs/N+VlXvfadcotqy3o+K0nBeV6qUVpaqnvvvVcXXHCBfvnllwbLvv322+revbuee+65w+5bKUm///3vtXPnTknSTTfd5PchhQAAhAMBSKAFqDvjsaLC9z5GdZWXl7uvg3FadX2zL6+88kpdccUVPusMHTpUf/jDH9zpA0WFyv1hjjsdHWn05CUD9OTEoYfUTU5O1rRp0xQdHV3vvVu1aqU333zTKyj7wgsv+PW3AACAo4fnM0pFRYWmnNxFM28foZ7tEr3Kfbd5v8b8eb4+X+Pci9HzWUkKzvOSJO3du1ennHKKnn32WZWWlioqKkq33XabFi5cqIKCAlVUVCg7O1vvvfeeO3hYWFio3/3ud5oyZUqDQcjvvvtOr7zyiiQpPT1df/zjH4PSZwAAQoUAJNACJCZ6PzjXnRHZEM+3+HXvE4y+SNIdd9xx2HpTrrtBEVG1QcSybSslSWmJMXrnppN15UmdFRUVdcgshMsvv1xpaWkN3jsrK0sXX3yxO718+XIVFhb6rgAAAI46ns8oNc9Kx2Uka9YdIzRpmPdBM/mllbr1reX63Qcrtbeg2Od9GstaqyuuuEKrVq2S5AxqfvXVV3r55Zc1YsQIpaSkKDo6Wp06ddKkSZO0aNEir+ept99+2+cL1aqqKt18881yOBySpGefffaI9gcHACAcCEACLUBycrJXOj8/30fJQ3nu2ei5F2Ow+hIfH6/hw4c3WGfH/lLd8O5Pikrv6s6ryNusAZ1SNOuOkRretY3P+59xxhl+9ctzGbbD4XA/8AMAgGOD5zOE57NSfEyUnp4wUH+5YoiSYqO86kxfnq3b/rHAKy8Yz0uzZ8/WV1995U4/9dRTXs8qdUVEROj555/XkCFD3HmPP/54vcvBn332Wa1evVqS8/nn6quvDri/AACEGgFIoAXo1q2bV3r79u1+1auurlZOTo473b1794D7UvceHTt2VFRUlI/S0sJf9uqilxbpp11FikpKd+dHlB/QB7eeoo6tvZc51b1/586d/epXVpb3zIa9e/f6VQ8AABwdPJ+X6ntWunBQR31292ka3tV7tuDunGyvdDCelzz3o46JidGNN9542DoRERG67bbb3Ol9+/ZpwQLv4Oju3bv12GOPSZKio6P18ssvB9xXAACaAgFIoAXo27evV3rTpk1+1du6dauqq6t93qcxevbs6bXfYt0l0zUcDqsX//uLpvzje+0vce1Z6bEEW9UVios+9KTG448/3ivt6/511d2b8kiWqQMAgJbP8zknOzv7kL0dJSmrTbzeu/kU3T+mr6IjnQfbVeXv8iqT7WgdcF9qZihK0nHHHaeEhAS/6g0bNswrvW7dOq/07t273bMiIyIiNG7cOPXs2dPnT92VJC+88ILX556zNAEACCXf05YANBt9+/ZVdHS0+1ToxYsX6/rrrz9svcWLF3ulBwwYEHBfoqKidPzxx2vFihWS6l8OXlBaod++v1L/XZ/nlR9RUeq+btOmTd1qkqRBgwZ5pf1dbl63nK/7AwCAo9PAgQPd11VVVVq2bJlGjBhxSLnICKPbzuih03un6Z5/r9CCnPW1nyW21b2fbNacTSV67KL+6pBy6OF7/igpKXFf+xt8lA7df7KhE7nLy8v9fildIz8/3+uZ6cCBA0dUHwCAxmIGJNACxMfHe+0bNHfu3AZPRqwxZ07tSdOJiYk67bTTgtKfCy64wH2dk5OjPXv2uNOrswt1wV8WHhJ8PC4jWQkHapc41V1WXt+9JWnlypV+9aluOV/3BwAAR6cxY8Z4pT2fg+rTr2OK3r1usBy5P7vzWvVwzkD8cl2uzvnfb/SPhVtUWe044r54HgqTm5vrd71du7xnY/JCFQBwtCAACbQQnqc8b9myRXPnzm2wfGFhoaZPn+5Ojxkzxu/lzIdz6aWXeqWnT58ua63e+X67xr/yrbLzvd/WTxyaqfuGSLm7ax+qfR0u06NHD68ZDB988IFfffrwww/d1x07dlTv3r39qgcAAI4OmZmZXkuYp02b5rUVTX0+nv6BKspqn1ta9TrZfX2gvEqPfbpOY/48X/M25NVX3aeePXu6rzdt2qTNmzf7Ve/LL7/0Svfq1csrPXjwYFlr/f7ZsmWLV/2pU6d6fe75fAkAQCgRgARaiMmTJ3u9Tb///vtVVVXls/xDDz2k0tLaJc933XVXg/c/44wzZIxx/zRkyJAhXjMyn/j/n9T1r36jBz5erYqq2lkCMVERenr8AD09foCmPvSgO98Yo8mTJ/u8/z333OO+XrJkiVdwsT6vvfaaNmzY4E5PmTKlwfIAAODodOedd7qvt2/frueff95n2aKiIj3yyCPudO/evfW/91yjpDjvXao27SnRddOWasIzM7yela699lqf9x49erRX+qGHHjps33fs2KGXXnrJnU5ISKh3CTkAAC0RAUighUhJSdF9993nTv/www+69tpr3ftCevrLX/7i9QA7ZsyYoC2/rvH000+7A5U5O7P17uO/VnVJ7Z5Cmamt9NFtp+rCfmm65pprvE5xnDRp0iGHzXi6+uqr1b9/f3f62muv1ezZs+stO336dN1xxx3udEpKin772982+u8CAAAt1+TJk72eMR544AF99NFHh5QrKirSJZdcop07d7rzHnvsMU0+tZvm/naUfjUw45A6323e73c/LrvsMnXs2NGdfvfdd3XXXXfVezCOJK1du1ajR49WQUGBO+/Xv/510FavAAAQbsaffeR8aHRFAI1TWVmp8847T/PmzXPndenSRZMnT1bXrl21Z88ezZgxQ0uWLHF/npGRoSVLligzM7PBe59xxhn65ptv3OnDjQ0VVQ5dcP09mvPmC+48ExOvhONO08BBgzXpxK7avmWj3nvvPa+H++7du2v58uVq3bp1g/dfu3atRowYocLCQnfeOeeco9GjRystLU25ubmaPXu25s+fX9u+MZoxY4bGjRvX4L0BAMDRa+XKlRo5cqTXASujR4/Wueeeq+TkZG3YsEH/+te/tHfvXvfnU6ZM0b/+9S+v+yzZsl+PfbpWa3YWSZKqCnO185Ub3J8POHOc/jP9XWW1ia+3HzNnztSll14qh6N2dUj79u01fvx49evXT/Hx8crLy9OCBQs0e/Zsr+Xiffv21eLFiw/7vHQ4W7du9doXe+rUqV6zPgEAQfDlQ1KRa7ux5Axp9BPh7U/oNbxk0lclApBAy5Kfn69f/epXh5xwXZ+OHTtq1qxZGjp06GHLHkkActOeA7rn3yu0KrtQ+fP+oaIlH8ufIWHgwIH69NNPlZWVddiykvTNN99o4sSJXofc+BIXF6c33nhDkyZN8uveAADg6PX555/r8ssv93qR6cu4ceP0/vvv1zvb0OGw+vCHbD3zxQblZG/3CkAm9D9b7S64R+cPyNAtp3fXwMzWh9R/8803deutt3pti3M4Q4YM0ccff6wuXbr4XccXApAA0AQIQPqFJdhAC5OamqoFCxboySefVEbGocuDJOeeQTfccINWr17tV/DRX5XVDr00b6POf36BVmU7H+hTz7xe7SY9rpQuvpdUp6en66mnntLixYv9Dj5K0qhRo7RmzRpde+21SkhIqLdMVFSULrvsMq1YsYLgIwAAkOTcfmbVqlUaP368YmJi6i3TvXt3/e1vf9PMmTN9LnWOiDCaOCxL39x7pm4b1eOQzx1W+s+qXRr34iJd9rfFmrUyR+VVtTMZp0yZopUrV+qGG25QfHz9MyVr9OzZU//3f/+n7777LijBRwAAmhNmQAItWHV1tRYtWqSNGzcqNzdXqampysrK0qhRo5SYmBjUttbsLNS901fpp11Fh3x2/Yhuum9MH+Xs2KalS5cqJydHFRUVSktL04ABAzRs2DBFRAT2vqOkpETz58/X9u3btW/fPqWkpKhLly46/fTTlZycHNC9AQDA0Wv//v2aP3++srOzVVJSooyMDPXt21cnnnjiEd+rqKxSr83frNcXblFJRf0nbLdJiNHEoZm6bHiWeqTXPo+Vl5drxYoVWrt2rfbv36/y8nIlJSWpQ4cOGjZsmLp3797ovxEAEEbMgPSvEgFIAA0pPFip/5vzs978bpuqHd7/26cnxeqZCQN1Rp92YeodAABA0yssrdTbS7bpjUVblVdc/8EykjQwM0UXDe6kCwdmqF1yXBP2EADQZAhA+leJACSA+jgcVu8v26E/fbFB+0sqDvl80rAsPTD2OKXER4ehdwAAAOFXXlWtmSty9I+FW7R+d7HPchFGOrFbG40+voNG92uvzNSGl2MDAFoQApD+VSIACaCubzfu1R8/X+/e59FTVptWeuqSgRrZKy0MPQMAAGh+rLX6cUeB3v1+uz5ZlaOySkeD5ft3StZZfdrp9N7pGpzVWlGRbM0PAC0WAUj/KhGABFBjxY4CPfPFei3auO+Qz2IiI3TDad1051k9FR8TFYbeAQAANH+FByv1n1W7NGPFTi3Zsv+w5ZPiojSyZ5pO752u03unq1PrVk3QSwBA0BCA9K8SAUgAy7fl669fb9JXP+XW+/lZfdvp4QuOV7e0+k+iBgAAwKFyCg5q1socfbZ6V70rS+rTIz1Bo3q306g+6TqpWxvFRUeGuJcAgIAQgPSvEgFI4NjkcFjN25Cnv32zWUu21v92vle7RP1+bF+d1bd9E/cOAADg6JJTcFBz1uXqi7W7tWTLflU5Dv91KjYqQid1b6tRvdM1qne6eqQnyJhGfe8DAIQKAUj/KhGABI4t+SUVmr48W+8u2a7Ne0vqLZOZ2kr3nNNbFw/ppMgIHnIBAACCqbisUos37dP8X/bom5/3aMf+g37V69S6lU7vna4z+6TrtF7pahXD7EgACDsCkP5VIgAJHP2qqh1avHmfPlyerc/W7FZFVf0bo2ekxOnWUT10+YlZio3igRYAACDUrLXauq9U83/eo/k/79G3m/bpYGX1YevFRkXotF5pOvf49jqrb3ulJ8U2QW8BAIcgAOlfJQKQwNHJ4bD6YXu+e9+hvQcqfJbt3T5Rt5zeQ+MGd1Q0pzACAACETXlVtZZvzdc3PztnR67fXXzYOsZIQ7Ja6/z+GfrVwAx15CAbAGg6BCD9q0QAEjh6lFVWa+EvezVnXa7mrs9tMOhojDSqd7quPqWLzuzTjv2EAAAAmqHdhWXupdoLf9mrwoOVh60zvGuqLhzUUef3z2BmJACEGgFI/yoRgARaLofDat2uIi3auFcLN+7Vki37Ve5jeXWNtMRYXT48S5OGZymrTXwT9RQAAACBqnatcPlqXa7m/JSrzXvq38+7RoSRTu2RpktP6KTz+2ewZyQAhAIBSP8qEYAEWg6Hw2rTngNaujVf327aq2837dP+Et+zHGskxUbpvP4ddOGgjhrRo62iWGYNAADQ4m3ac8AZjFyXq+X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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 296, - "width": 656 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(linear_trace, var_names=['m'], ref_val=m, figsize=(9, 4));" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As we can see, the posterior of the regression slope `m` is underestimated, by quite lot in this example.\n", - "\n", - "Let's visualise how bad that fit is by plotting the data and posterior predictions." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 623 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "def pp_plot(x, y, trace):\n", - " fig, ax = plt.subplots(figsize=(10, 8))\n", - " # plot data\n", - " ax.plot(x, y, 'k.')\n", - " # plot posterior predicted... samples from posterior\n", - " xi = np.array([np.min(x), np.max(x)])\n", - " n_samples=1000\n", - " for n in range(n_samples):\n", - " y_ppc = xi * trace[\"m\"][n] + trace[\"c\"][n]\n", - " ax.plot(xi, y_ppc, c=\"steelblue\", alpha=0.01, rasterized=True)\n", - " # plot true\n", - " ax.plot(xi, m * xi + c, \"k\", lw=3, label=\"True\")\n", - " # plot bounds\n", - " ax.axhline(bounds[0], c='r', ls='--')\n", - " ax.axhline(bounds[1], c='r', ls='--')\n", - " ax.legend()\n", - " ax.set(xlabel=\"x\", ylabel=\"y\")\n", - " \n", - "pp_plot(xt, yt, linear_trace)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that the degree of estimation bias will depend upon a number of things, including the truncation boundaries and the measurement noise. In some situations with high measurement precision and/or little measurement noise, the estimation bias may not be very large. Otherwise, this could have a negative impact upon your research conclusions." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Truncated regression avoids this underestimate" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Truncated regression solves this problem. By using a truncated normal likelihood distribution we are explicity stating our knowledge about the generative process which gave rise to your dataset. We can impliment a [truncated regression model](https://en.wikipedia.org/wiki/Truncated_regression_model) as below." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "def truncated_regression(x, y, bounds):\n", - "\n", - " with pm.Model() as model:\n", - " m = pm.Normal(\"m\", mu=0, sd=1)\n", - " c = pm.Normal(\"c\", mu=0, sd=1)\n", - " σ = pm.HalfNormal(\"σ\", sd=1)\n", - "\n", - " y_likelihood = pm.TruncatedNormal(\n", - " \"y_likelihood\",\n", - " mu=m * x + c,\n", - " sd=σ,\n", - " observed=y,\n", - " lower=bounds[0],\n", - " upper=bounds[1],\n", - " )\n", - " \n", - " with model:\n", - " trace = pm.sample()\n", - "\n", - " return model, trace" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/pymc3/sampling.py:465: FutureWarning: In an upcoming release, pm.sample will return an `arviz.InferenceData` object instead of a `MultiTrace` by default. You can pass return_inferencedata=True or return_inferencedata=False to be safe and silence this warning.\n", - " warnings.warn(\n", - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [σ, c, m]\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " \n", - " 100.00% [8000/8000 00:04<00:00 Sampling 4 chains, 0 divergences]\n", - "
\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 13 seconds.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" - ] - } - ], - "source": [ - "# run the model on the truncated data (xt, yt)\n", - "truncated_model, truncated_trace = truncated_regression(xt, yt, bounds)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And we can check that the inferences are much better by examining the posterior distribution over our slope parameter `m`." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/benjamv/opt/anaconda3/lib/python3.8/site-packages/arviz/data/io_pymc3.py:88: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n", - " warnings.warn(\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n", - "WARNING (theano.tensor.opt): The Op erfcx does not provide a C implementation. As well as being potentially slow, this also disables loop fusion.\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 296, - "width": 656 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(truncated_trace, var_names=['m'], ref_val=m, figsize=(9, 4))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And also by doing our graphical posterior predictive checks. Looks good." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 479, - "width": 614 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pp_plot(xt, yt, truncated_trace)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Last updated: Sun Jan 24 2021\n", - "\n", - "Python implementation: CPython\n", - "Python version : 3.8.5\n", - "IPython version : 7.19.0\n", - "\n", - "pymc3 : 3.10.0\n", - "matplotlib: 3.3.2\n", - "numpy : 1.19.2\n", - "arviz : 0.11.0\n", - "\n", - "Watermark: 2.1.0\n", - "\n" - ] - } - ], - "source": [ - "%load_ext watermark\n", - "%watermark -n -u -v -iv -w" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} From 52687a0f4eab08ae82fc176fe50e5f894eafa7fa Mon Sep 17 00:00:00 2001 From: "Benjamin T. Vincent" Date: Sat, 21 May 2022 11:36:51 +0100 Subject: [PATCH 7/8] fix incorrect statement about pm.NormalMixture --- .../gaussian_mixture_model.ipynb | 179 ++++++++++-------- .../gaussian_mixture_model.myst.md | 2 +- 2 files changed, 105 insertions(+), 76 deletions(-) diff --git a/examples/mixture_models/gaussian_mixture_model.ipynb b/examples/mixture_models/gaussian_mixture_model.ipynb index 6a8d67bf0..653406747 100644 --- a/examples/mixture_models/gaussian_mixture_model.ipynb +++ b/examples/mixture_models/gaussian_mixture_model.ipynb @@ -24,7 +24,16 @@ "execution_count": 1, "id": "a0b1403f-3cec-4237-a1c7-27f1c8681cb9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "ld: unsupported tapi file type '!tapi-tbd' in YAML file '/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/lib/libSystem.tbd' for architecture x86_64\n", + "clang-12: error: linker command failed with exit code 1 (use -v to see invocation)\n" + ] + } + ], "source": [ "import arviz as az\n", "import matplotlib.pyplot as plt\n", @@ -69,7 +78,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -98,7 +107,7 @@ "id": "81691367-b709-4ed9-b472-aa83a79f456a", "metadata": {}, "source": [ - "In the PyMC model, we will estimate one $\\mu$ and one $\\sigma$ for each of the 3 clusters. Writing a Gaussian Mixture Model got significantly easier from PyMC 4.0.0b6 onwards with the introduction of `pm.NormalMixture`." + "In the PyMC model, we will estimate one $\\mu$ and one $\\sigma$ for each of the 3 clusters. Writing a Gaussian Mixture Model is very easy with the `pm.NormalMixture` distribution." ] }, { @@ -113,84 +122,84 @@ "\n", "\n", - "\n", "\n", - "\n", + "\n", "\n", - "\n", + "\n", "\n", "clustercluster (3)\n", - "\n", - "cluster (3)\n", + "\n", + "cluster (3)\n", "\n", "\n", "cluster500\n", - "\n", - "500\n", + "\n", + "500\n", "\n", - "\n", + "\n", "\n", - "w\n", - "\n", - "w\n", - "~\n", - "Dirichlet\n", + "μ\n", + "\n", + "μ\n", + "~\n", + "Normal\n", "\n", "\n", "\n", "x\n", - "\n", - "x\n", - "~\n", - "Deterministic\n", - "\n", - "\n", - "\n", - "w->x\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "μ\n", - "\n", - "μ\n", - "~\n", - "Normal\n", + "\n", + "x\n", + "~\n", + "Deterministic\n", "\n", "\n", - "\n", + "\n", "μ->x\n", - "\n", - "\n", + "\n", + "\n", "\n", "\n", - "\n", + "\n", "σ\n", - "\n", - "σ\n", - "~\n", - "HalfNormal\n", + "\n", + "σ\n", + "~\n", + "HalfNormal\n", "\n", "\n", - "\n", + "\n", "σ->x\n", - "\n", - "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "w\n", + "\n", + "w\n", + "~\n", + "Dirichlet\n", + "\n", + "\n", + "\n", + "w->x\n", + "\n", + "\n", "\n", "\n", - "\n", + "\n", "x->x\n", - "\n", - "\n", + "\n", + "\n", "\n", "\n", "\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 4, @@ -227,31 +236,51 @@ "text": [ "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", - "/Users/benjamv/opt/anaconda3/envs/pymc-dev-py39/lib/python3.9/site-packages/pymc/aesaraf.py:1005: UserWarning: The parameter 'updates' of aesara.function() expects an OrderedDict, got . Using a standard dictionary here results in non-deterministic behavior. You should use an OrderedDict if you are using Python 2.7 (collections.OrderedDict for older python), or use a list of (shared, update) pairs. Do not just convert your dictionary to this type before the call as the conversion will still be non-deterministic.\n", + "/Users/benjamv/opt/miniconda3/envs/pymc-dev-py39/lib/python3.9/site-packages/pymc/aesaraf.py:1005: UserWarning: The parameter 'updates' of aesara.function() expects an OrderedDict, got . Using a standard dictionary here results in non-deterministic behavior. You should use an OrderedDict if you are using Python 2.7 (collections.OrderedDict for older python), or use a list of (shared, update) pairs. Do not just convert your dictionary to this type before the call as the conversion will still be non-deterministic.\n", " aesara_function = aesara.function(\n", "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [μ, σ, w]\n" + "NUTS: [μ, σ, w]\n", + "ld: unsupported tapi file type '!tapi-tbd' in YAML file '/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/lib/libSystem.tbd' for architecture x86_64\n", + "clang-12: error: linker command failed with exit code 1 (use -v to see invocation)\n", + "ld: unsupported tapi file type '!tapi-tbd' in YAML file '/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/lib/libSystem.tbd' for architecture x86_64\n", + "clang-12: error: linker command failed with exit code 1 (use -v to see invocation)\n", + "ld: unsupported tapi file type '!tapi-tbd' in YAML file '/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/lib/libSystem.tbd' for architecture x86_64\n", + "clang-12: error: linker command failed with exit code 1 (use -v to see invocation)\n", + "ld: unsupported tapi file type '!tapi-tbd' in YAML file '/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/lib/libSystem.tbd' for architecture x86_64\n", + "clang-12: error: linker command failed with exit code 1 (use -v to see invocation)\n" ] }, + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/html": [ "\n", "
\n", - " \n", " \n", - " 100.00% [8000/8000 00:10<00:00 Sampling 4 chains, 0 divergences]\n", + " 100.00% [8000/8000 00:08<00:00 Sampling 4 chains, 0 divergences]\n", "
\n", " " ], @@ -266,7 +295,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 22 seconds.\n" + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 26 seconds.\n" ] } ], @@ -291,7 +320,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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" ] @@ -325,7 +354,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -386,22 +415,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "Last updated: Sun Apr 17 2022\n", + "Last updated: Sat May 21 2022\n", "\n", "Python implementation: CPython\n", - "Python version : 3.9.9\n", - "IPython version : 7.31.0\n", + "Python version : 3.9.12\n", + "IPython version : 8.2.0\n", "\n", "aesara : 2.5.1\n", "aeppl : 0.0.27\n", "xarray : 0.20.1\n", "xarray_einstats: 0.2.2\n", "\n", - "matplotlib: 3.5.0\n", + "numpy : 1.22.3\n", "arviz : 0.12.0\n", + "pandas : 1.4.2\n", + "matplotlib: 3.5.1\n", "pymc : 4.0.0b6\n", - "pandas : 1.3.5\n", - "numpy : 1.21.5\n", "\n", "Watermark: 2.3.0\n", "\n" @@ -439,7 +468,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.9" + "version": "3.9.12" } }, "nbformat": 4, diff --git a/myst_nbs/mixture_models/gaussian_mixture_model.myst.md b/myst_nbs/mixture_models/gaussian_mixture_model.myst.md index fe596b31f..ac7d211e5 100644 --- a/myst_nbs/mixture_models/gaussian_mixture_model.myst.md +++ b/myst_nbs/mixture_models/gaussian_mixture_model.myst.md @@ -56,7 +56,7 @@ x = rng.normal(loc=centers[idx], scale=sds[idx], size=ndata) plt.hist(x, 40); ``` -In the PyMC model, we will estimate one $\mu$ and one $\sigma$ for each of the 3 clusters. Writing a Gaussian Mixture Model got significantly easier from PyMC 4.0.0b6 onwards with the introduction of `pm.NormalMixture`. +In the PyMC model, we will estimate one $\mu$ and one $\sigma$ for each of the 3 clusters. Writing a Gaussian Mixture Model is very easy with the `pm.NormalMixture` distribution. ```{code-cell} ipython3 with pm.Model(coords={"cluster": range(k)}) as model: From 2b22c4d4eb47625bf9bc9f0be1d0044beb38fb00 Mon Sep 17 00:00:00 2001 From: "Benjamin T. Vincent" Date: Sat, 11 Jun 2022 14:25:36 +0100 Subject: [PATCH 8/8] batch remove pymc and pymc3 tags --- examples/case_studies/BART_introduction.ipynb | 2 +- examples/case_studies/BEST.ipynb | 2 +- examples/case_studies/binning.ipynb | 2 +- .../case_studies/blackbox_external_likelihood_numpy.ipynb | 2 +- examples/case_studies/factor_analysis.ipynb | 2 +- examples/case_studies/hierarchical_partial_pooling.ipynb | 2 +- examples/case_studies/item_response_nba.ipynb | 2 +- examples/case_studies/mediation_analysis.ipynb | 2 +- examples/case_studies/moderation_analysis.ipynb | 2 +- examples/case_studies/multilevel_modeling.ipynb | 2 +- .../case_studies/probabilistic_matrix_factorization.ipynb | 2 +- examples/case_studies/putting_workflow.ipynb | 2 +- examples/case_studies/regression_discontinuity.ipynb | 2 +- examples/case_studies/rugby_analytics.ipynb | 2 +- examples/case_studies/spline.ipynb | 2 +- examples/case_studies/wrapping_jax_function.ipynb | 2 +- examples/diagnostics_and_criticism/Bayes_factor.ipynb | 2 +- examples/diagnostics_and_criticism/sampler-stats.ipynb | 2 +- examples/gaussian_processes/GP-MaunaLoa.ipynb | 2 +- .../generalized_linear_models/GLM-binomial-regression.ipynb | 2 +- .../GLM-hierarchical-binomial-model.ipynb | 2 +- examples/generalized_linear_models/GLM-model-selection.ipynb | 2 +- .../GLM-robust-with-outlier-detection.ipynb | 2 +- .../generalized_linear_models/GLM-rolling-regression.ipynb | 2 +- examples/generalized_linear_models/GLM-simpsons-paradox.ipynb | 2 +- .../GLM-truncated-censored-regression.ipynb | 2 +- examples/howto/data_container.ipynb | 2 +- examples/howto/lasso_block_update.ipynb | 2 +- .../mixture_models/dirichlet_mixture_of_multinomials.ipynb | 2 +- examples/mixture_models/dp_mix.ipynb | 2 +- examples/mixture_models/gaussian_mixture_model.ipynb | 2 +- .../mixture_models/marginalized_gaussian_mixture_model.ipynb | 2 +- examples/samplers/SMC-ABC_Lotka-Volterra_example.ipynb | 2 +- examples/samplers/SMC2_gaussians.ipynb | 2 +- examples/survival_analysis/censored_data.ipynb | 2 +- .../Air_passengers-Prophet_with_Bayesian_workflow.ipynb | 2 +- examples/time_series/MvGaussianRandomWalk_demo.ipynb | 2 +- myst_nbs/case_studies/BART_introduction.myst.md | 2 +- myst_nbs/case_studies/BEST.myst.md | 4 ++-- myst_nbs/case_studies/binning.myst.md | 4 ++-- .../case_studies/blackbox_external_likelihood_numpy.myst.md | 4 ++-- myst_nbs/case_studies/factor_analysis.myst.md | 4 ++-- myst_nbs/case_studies/hierarchical_partial_pooling.myst.md | 4 ++-- myst_nbs/case_studies/item_response_nba.myst.md | 4 ++-- myst_nbs/case_studies/mediation_analysis.myst.md | 4 ++-- myst_nbs/case_studies/moderation_analysis.myst.md | 2 +- myst_nbs/case_studies/multilevel_modeling.myst.md | 4 ++-- .../case_studies/probabilistic_matrix_factorization.myst.md | 4 ++-- myst_nbs/case_studies/putting_workflow.myst.md | 2 +- myst_nbs/case_studies/regression_discontinuity.myst.md | 4 ++-- myst_nbs/case_studies/rugby_analytics.myst.md | 4 ++-- myst_nbs/case_studies/spline.myst.md | 2 +- myst_nbs/case_studies/wrapping_jax_function.myst.md | 2 +- myst_nbs/diagnostics_and_criticism/Bayes_factor.myst.md | 2 +- myst_nbs/diagnostics_and_criticism/sampler-stats.myst.md | 2 +- myst_nbs/gaussian_processes/GP-MaunaLoa.myst.md | 4 ++-- .../generalized_linear_models/GLM-binomial-regression.myst.md | 2 +- .../GLM-hierarchical-binomial-model.myst.md | 2 +- .../generalized_linear_models/GLM-model-selection.myst.md | 4 ++-- .../GLM-robust-with-outlier-detection.myst.md | 4 ++-- .../generalized_linear_models/GLM-rolling-regression.myst.md | 2 +- .../generalized_linear_models/GLM-simpsons-paradox.myst.md | 2 +- .../GLM-truncated-censored-regression.myst.md | 4 ++-- myst_nbs/howto/data_container.myst.md | 2 +- myst_nbs/howto/lasso_block_update.myst.md | 2 +- .../mixture_models/dirichlet_mixture_of_multinomials.myst.md | 2 +- myst_nbs/mixture_models/dp_mix.myst.md | 2 +- myst_nbs/mixture_models/gaussian_mixture_model.myst.md | 2 +- .../marginalized_gaussian_mixture_model.myst.md | 2 +- myst_nbs/samplers/SMC-ABC_Lotka-Volterra_example.myst.md | 2 +- myst_nbs/samplers/SMC2_gaussians.myst.md | 2 +- myst_nbs/survival_analysis/censored_data.myst.md | 2 +- .../Air_passengers-Prophet_with_Bayesian_workflow.myst.md | 2 +- myst_nbs/time_series/MvGaussianRandomWalk_demo.myst.md | 2 +- 74 files changed, 89 insertions(+), 89 deletions(-) diff --git a/examples/case_studies/BART_introduction.ipynb b/examples/case_studies/BART_introduction.ipynb index 936ba5b8d..906665199 100644 --- a/examples/case_studies/BART_introduction.ipynb +++ b/examples/case_studies/BART_introduction.ipynb @@ -8,7 +8,7 @@ "(BART_introduction)=\n", "# Bayesian Additive Regression Trees: Introduction\n", ":::{post} Dec 21, 2021\n", - ":tags: BART, Bayesian additive regression trees, non-parametric, regression\n", + ":tags: BART, Bayesian additive regression trees, non-parametric, regression \n", ":category: intermediate, explanation\n", ":author: Osvaldo Martin\n", ":::" diff --git a/examples/case_studies/BEST.ipynb b/examples/case_studies/BEST.ipynb index dbf924ac9..24452dd90 100644 --- a/examples/case_studies/BEST.ipynb +++ b/examples/case_studies/BEST.ipynb @@ -8,7 +8,7 @@ "# Bayesian Estimation Supersedes the T-Test\n", "\n", ":::{post} Jan 07, 2022\n", - ":tags: hypothesis testing, model comparison, pymc3.Deterministic, pymc3.Exponential, pymc3.Model, pymc3.Normal, pymc3.StudentT, pymc3.Uniform\n", + ":tags: hypothesis testing, model comparison, \n", ":category: beginner\n", ":author: Andrew Straw, Thomas Wiecki, Chris Fonnesbeck, Andrés suárez\n", ":::" diff --git a/examples/case_studies/binning.ipynb b/examples/case_studies/binning.ipynb index a42463b55..11a26428a 100644 --- a/examples/case_studies/binning.ipynb +++ b/examples/case_studies/binning.ipynb @@ -8,7 +8,7 @@ "(awkward_binning)=\n", "# Estimating parameters of a distribution from awkwardly binned data\n", ":::{post} Oct 23, 2021\n", - ":tags: binned data, case study, parameter estimation, pymc3.Bound, pymc3.Deterministic, pymc3.Gamma, pymc3.HalfNormal, pymc3.Model, pymc3.Multinomial, pymc3.Normal\n", + ":tags: binned data, case study, parameter estimation, \n", ":category: intermediate\n", ":author: Eric Ma, Benjamin T. Vincent\n", ":::" diff --git a/examples/case_studies/blackbox_external_likelihood_numpy.ipynb b/examples/case_studies/blackbox_external_likelihood_numpy.ipynb index db2bb54dc..88936d160 100644 --- a/examples/case_studies/blackbox_external_likelihood_numpy.ipynb +++ b/examples/case_studies/blackbox_external_likelihood_numpy.ipynb @@ -8,7 +8,7 @@ "# Using a \"black box\" likelihood function (numpy)\n", "\n", ":::{post} Dec 16, 2021\n", - ":tags: case study, external likelihood, pymc.Model, pymc.Normal, pymc.Potential, pymc.Uniform, pymc3.Model, pymc3.Normal, pymc3.Potential, pymc3.Uniform\n", + ":tags: case study, external likelihood, \n", ":category: beginner\n", ":author: Matt Pitkin, Jørgen Midtbø, Oriol Abril\n", ":::\n", diff --git a/examples/case_studies/factor_analysis.ipynb b/examples/case_studies/factor_analysis.ipynb index 6041100d8..9348ce2ff 100644 --- a/examples/case_studies/factor_analysis.ipynb +++ b/examples/case_studies/factor_analysis.ipynb @@ -8,7 +8,7 @@ "# Factor analysis\n", "\n", ":::{post} 19 Mar, 2022\n", - ":tags: factor analysis, matrix factorization, pca\n", + ":tags: factor analysis, matrix factorization, pca \n", ":category: advanced, how-to\n", ":author: Chris Hartl, Christopher Krapu, Oriol Abril-Pla\n", ":::" diff --git a/examples/case_studies/hierarchical_partial_pooling.ipynb b/examples/case_studies/hierarchical_partial_pooling.ipynb index 64137c52a..053d9ed02 100644 --- a/examples/case_studies/hierarchical_partial_pooling.ipynb +++ b/examples/case_studies/hierarchical_partial_pooling.ipynb @@ -7,7 +7,7 @@ "# Hierarchical Partial Pooling\n", "\n", ":::{post} Oct 07, 2021\n", - ":tags: hierarchical model, pymc.Beta, pymc.Binomial, pymc.Deterministic, pymc.Exponential, pymc.Model, pymc.Uniform, pymc3.Beta, pymc3.Binomial, pymc3.Deterministic, pymc3.Exponential, pymc3.Model, pymc3.Uniform\n", + ":tags: hierarchical model, \n", ":category: intermediate\n", ":::" ] diff --git a/examples/case_studies/item_response_nba.ipynb b/examples/case_studies/item_response_nba.ipynb index 12a867ff3..af223156e 100644 --- a/examples/case_studies/item_response_nba.ipynb +++ b/examples/case_studies/item_response_nba.ipynb @@ -8,7 +8,7 @@ "# NBA Foul Analysis with Item Response Theory\n", "\n", ":::{post} Apr 17, 2022\n", - ":tags: hierarchical model, case study, generalized linear model\n", + ":tags: hierarchical model, case study, generalized linear model \n", ":category: intermediate, tutorial\n", ":author: Austin Rochford, Lorenzo Toniazzi\n", ":::" diff --git a/examples/case_studies/mediation_analysis.ipynb b/examples/case_studies/mediation_analysis.ipynb index f4483dfb5..aa2f5d722 100644 --- a/examples/case_studies/mediation_analysis.ipynb +++ b/examples/case_studies/mediation_analysis.ipynb @@ -9,7 +9,7 @@ "# Bayesian mediation analysis\n", "\n", ":::{post} February, 2022\n", - ":tags: mediation, path analysis, regression\n", + ":tags: mediation, path analysis, regression \n", ":category: beginner\n", ":author: Benjamin T. Vincent\n", ":::\n", diff --git a/examples/case_studies/moderation_analysis.ipynb b/examples/case_studies/moderation_analysis.ipynb index bb792059f..045e7ed28 100644 --- a/examples/case_studies/moderation_analysis.ipynb +++ b/examples/case_studies/moderation_analysis.ipynb @@ -9,7 +9,7 @@ "# Bayesian moderation analysis\n", "\n", ":::{post} March, 2022\n", - ":tags: moderation, path analysis,\n", + ":tags: moderation, path analysis, \n", ":category: beginner\n", ":author: Benjamin T. Vincent\n", ":::\n", diff --git a/examples/case_studies/multilevel_modeling.ipynb b/examples/case_studies/multilevel_modeling.ipynb index 39b58de72..f25fc3a88 100644 --- a/examples/case_studies/multilevel_modeling.ipynb +++ b/examples/case_studies/multilevel_modeling.ipynb @@ -8,7 +8,7 @@ "# A Primer on Bayesian Methods for Multilevel Modeling\n", "\n", ":::{post} 27 February, 2022\n", - ":tags: hierarchical model, case study\n", + ":tags: hierarchical model, case study \n", ":category: intermediate\n", ":author: Chris Fonnesbeck, Colin Carroll, Alex Andorra, Oriol Abril, Farhan Reynaldo\n", ":::" diff --git a/examples/case_studies/probabilistic_matrix_factorization.ipynb b/examples/case_studies/probabilistic_matrix_factorization.ipynb index 3c7d35107..d4b4a0e46 100644 --- a/examples/case_studies/probabilistic_matrix_factorization.ipynb +++ b/examples/case_studies/probabilistic_matrix_factorization.ipynb @@ -7,7 +7,7 @@ "# Probabilistic Matrix Factorization for Making Personalized Recommendations\n", "\n", ":::{post} Sept 20, 2021\n", - ":tags: case study, pymc3.Model, pymc3.MvNormal, pymc3.Normal\n", + ":tags: case study, \n", ":category: intermediate\n", ":::" ] diff --git a/examples/case_studies/putting_workflow.ipynb b/examples/case_studies/putting_workflow.ipynb index c6a658ecf..b951c044e 100644 --- a/examples/case_studies/putting_workflow.ipynb +++ b/examples/case_studies/putting_workflow.ipynb @@ -8,7 +8,7 @@ "# Model building and expansion for golf putting\n", "\n", ":::{post} Apr 2, 2022\n", - ":tags: bayesian workflow, model expansion, sports\n", + ":tags: bayesian workflow, model expansion, sports \n", ":category: intermediate, how-to\n", ":author: Colin Carroll, Marco Gorelli, Oriol Abril-Pla\n", ":::\n", diff --git a/examples/case_studies/regression_discontinuity.ipynb b/examples/case_studies/regression_discontinuity.ipynb index 031abd8b3..c69362a5a 100644 --- a/examples/case_studies/regression_discontinuity.ipynb +++ b/examples/case_studies/regression_discontinuity.ipynb @@ -9,7 +9,7 @@ "# Regression discontinuity design analysis\n", "\n", ":::{post} April, 2022\n", - ":tags: regression, causal inference, quasi experimental design, counterfactuals\n", + ":tags: regression, causal inference, quasi experimental design, counterfactuals \n", ":category: beginner, explanation\n", ":author: Benjamin T. Vincent\n", ":::\n", diff --git a/examples/case_studies/rugby_analytics.ipynb b/examples/case_studies/rugby_analytics.ipynb index 4a7ede3ef..eb5e4da6e 100644 --- a/examples/case_studies/rugby_analytics.ipynb +++ b/examples/case_studies/rugby_analytics.ipynb @@ -7,7 +7,7 @@ "# A Hierarchical model for Rugby prediction\n", "\n", ":::{post} 19 Mar, 2022\n", - ":tags: hierarchical, sports\n", + ":tags: hierarchical, sports \n", ":category: intermediate, how-to\n", ":author: Peadar Coyle, Meenal Jhajharia, Oriol Abril-Pla\n", ":::" diff --git a/examples/case_studies/spline.ipynb b/examples/case_studies/spline.ipynb index 8a0567826..161fcb4a6 100644 --- a/examples/case_studies/spline.ipynb +++ b/examples/case_studies/spline.ipynb @@ -8,7 +8,7 @@ "# Splines\n", "\n", ":::{post} June 4, 2022 \n", - ":tags: patsy, regression, spline\n", + ":tags: patsy, regression, spline \n", ":category: beginner\n", ":author: Joshua Cook\n", ":::" diff --git a/examples/case_studies/wrapping_jax_function.ipynb b/examples/case_studies/wrapping_jax_function.ipynb index a8eec1212..617bf3f59 100644 --- a/examples/case_studies/wrapping_jax_function.ipynb +++ b/examples/case_studies/wrapping_jax_function.ipynb @@ -8,7 +8,7 @@ "# How to wrap a JAX function for use in PyMC\n", "\n", ":::{post} Mar 24, 2022\n", - ":tags: Aesara, hidden markov model, JAX\n", + ":tags: Aesara, hidden markov model, JAX \n", ":category: advanced, how-to\n", ":author: Ricardo Vieira\n", ":::" diff --git a/examples/diagnostics_and_criticism/Bayes_factor.ipynb b/examples/diagnostics_and_criticism/Bayes_factor.ipynb index f8dc3a735..b771b2d6f 100644 --- a/examples/diagnostics_and_criticism/Bayes_factor.ipynb +++ b/examples/diagnostics_and_criticism/Bayes_factor.ipynb @@ -7,7 +7,7 @@ "(Bayes_factor)=\n", "# Bayes Factors and Marginal Likelihood\n", ":::{post} Jun 1, 2022\n", - ":tags: Bayes Factors, model comparison\n", + ":tags: Bayes Factors, model comparison \n", ":category: beginner, explanation\n", ":author: Osvaldo Martin\n", ":::" diff --git a/examples/diagnostics_and_criticism/sampler-stats.ipynb b/examples/diagnostics_and_criticism/sampler-stats.ipynb index ae6bd214a..81a308d2c 100644 --- a/examples/diagnostics_and_criticism/sampler-stats.ipynb +++ b/examples/diagnostics_and_criticism/sampler-stats.ipynb @@ -13,7 +13,7 @@ "statistics for each generated sample.\n", "\n", ":::{post} May 31, 2022\n", - ":tags: diagnostics\n", + ":tags: diagnostics \n", ":category: beginner\n", ":author: Meenal Jhajharia, Christian Luhmann\n", ":::" diff --git a/examples/gaussian_processes/GP-MaunaLoa.ipynb b/examples/gaussian_processes/GP-MaunaLoa.ipynb index 7ef200a69..0f77efed7 100644 --- a/examples/gaussian_processes/GP-MaunaLoa.ipynb +++ b/examples/gaussian_processes/GP-MaunaLoa.ipynb @@ -8,7 +8,7 @@ "# Gaussian Process for CO2 at Mauna Loa\n", "\n", ":::{post} April, 2022\n", - ":tags: gaussian process, CO2\n", + ":tags: gaussian process, CO2 \n", ":category: intermediate\n", ":author: Bill Engels, Chris Fonnesbeck\n", ":::" diff --git a/examples/generalized_linear_models/GLM-binomial-regression.ipynb b/examples/generalized_linear_models/GLM-binomial-regression.ipynb index 182b3d56f..1257ccc17 100644 --- a/examples/generalized_linear_models/GLM-binomial-regression.ipynb +++ b/examples/generalized_linear_models/GLM-binomial-regression.ipynb @@ -9,7 +9,7 @@ "# Binomial regression\n", "\n", ":::{post} February, 2022\n", - ":tags: binomial regression, generalized linear model, pymc.Binomial, pymc.ConstantData, pymc.Deterministic, pymc.Model, pymc.Normal, pymc3.Binomial, pymc3.ConstantData, pymc3.Deterministic, pymc3.Model, pymc3.Normal\n", + ":tags: binomial regression, generalized linear model, \n", ":category: beginner\n", ":author: Benjamin T. Vincent\n", ":::" diff --git a/examples/generalized_linear_models/GLM-hierarchical-binomial-model.ipynb b/examples/generalized_linear_models/GLM-hierarchical-binomial-model.ipynb index b96122313..d54515c90 100644 --- a/examples/generalized_linear_models/GLM-hierarchical-binomial-model.ipynb +++ b/examples/generalized_linear_models/GLM-hierarchical-binomial-model.ipynb @@ -6,7 +6,7 @@ "source": [ "# Hierarchical Binomial Model: Rat Tumor Example\n", ":::{post} Nov 11, 2021\n", - ":tags: generalized linear model, hierarchical model\n", + ":tags: generalized linear model, hierarchical model \n", ":category: intermediate\n", ":author: Demetri Pananos, Junpeng Lao, Raúl Maldonado, Farhan Reynaldo\n", ":::" diff --git a/examples/generalized_linear_models/GLM-model-selection.ipynb b/examples/generalized_linear_models/GLM-model-selection.ipynb index 7189e9e0e..481647340 100644 --- a/examples/generalized_linear_models/GLM-model-selection.ipynb +++ b/examples/generalized_linear_models/GLM-model-selection.ipynb @@ -8,7 +8,7 @@ "# GLM: Model Selection\n", "\n", ":::{post} Jan 8, 2022\n", - ":tags: cross validation, generalized linear models, loo, model comparison, pymc3.HalfCauchy, pymc3.Model, pymc3.Normal, waic\n", + ":tags: cross validation, generalized linear models, loo, model comparison, waic \n", ":category: intermediate\n", ":author: Jon Sedar, Junpeng Lao, Abhipsha Das, Oriol Abril-Pla\n", ":::" diff --git a/examples/generalized_linear_models/GLM-robust-with-outlier-detection.ipynb b/examples/generalized_linear_models/GLM-robust-with-outlier-detection.ipynb index 889b0923f..e7071bc02 100644 --- a/examples/generalized_linear_models/GLM-robust-with-outlier-detection.ipynb +++ b/examples/generalized_linear_models/GLM-robust-with-outlier-detection.ipynb @@ -8,7 +8,7 @@ "# GLM: Robust Regression using Custom Likelihood for Outlier Classification\n", "\n", ":::{post} 17 Nov, 2021\n", - ":tags: pymc3.Bernoulli, pymc3.Data, pymc3.Deterministic, pymc3.DiscreteUniform, pymc3.Exponential, pymc3.GaussianRandomWalk, pymc3.HalfNormal, pymc3.InverseGamma, pymc3.Model, pymc3.Normal, pymc3.Poisson, pymc3.Potential, pymc3.Slice, pymc3.StudentT, pymc3.Uniform, regression, robust analysis\n", + ":tags: regression, robust analysis \n", ":category: intermediate\n", ":author: Jon Sedar, Thomas Wiecki, Raul Maldonado, Oriol Abril\n", ":::\n", diff --git a/examples/generalized_linear_models/GLM-rolling-regression.ipynb b/examples/generalized_linear_models/GLM-rolling-regression.ipynb index 93618c937..e0bfe94fd 100644 --- a/examples/generalized_linear_models/GLM-rolling-regression.ipynb +++ b/examples/generalized_linear_models/GLM-rolling-regression.ipynb @@ -8,7 +8,7 @@ "# Rolling Regression\n", "\n", ":::{post} June, 2022\n", - ":tags: generalized linear model, regression\n", + ":tags: generalized linear model, regression \n", ":category: intermediate\n", ":author: Thomas Wiecki\n", ":::" diff --git a/examples/generalized_linear_models/GLM-simpsons-paradox.ipynb b/examples/generalized_linear_models/GLM-simpsons-paradox.ipynb index 1883c9145..c6536dbbf 100644 --- a/examples/generalized_linear_models/GLM-simpsons-paradox.ipynb +++ b/examples/generalized_linear_models/GLM-simpsons-paradox.ipynb @@ -8,7 +8,7 @@ "# Simpson's paradox and mixed models\n", "\n", ":::{post} March, 2022\n", - ":tags: regression, hierarchical model, linear model, multi level model, posterior predictive, Simpson's paradox\n", + ":tags: regression, hierarchical model, linear model, multi level model, posterior predictive, Simpson's paradox \n", ":category: beginner\n", ":author: Benjamin T. Vincent\n", ":::" diff --git a/examples/generalized_linear_models/GLM-truncated-censored-regression.ipynb b/examples/generalized_linear_models/GLM-truncated-censored-regression.ipynb index 33da40ea1..25503e95e 100644 --- a/examples/generalized_linear_models/GLM-truncated-censored-regression.ipynb +++ b/examples/generalized_linear_models/GLM-truncated-censored-regression.ipynb @@ -8,7 +8,7 @@ "# Bayesian regression with truncated or censored data\n", "\n", ":::{post} January, 2022\n", - ":tags: censored, censoring, generalized linear model, pymc3.Censored, pymc3.HalfNormal, pymc3.Model, pymc3.Normal, pymc3.TruncatedNormal, regression, truncated, truncation\n", + ":tags: censored, censoring, generalized linear model, regression, truncated, truncation \n", ":category: beginner\n", ":author: Benjamin T. Vincent\n", ":::\n", diff --git a/examples/howto/data_container.ipynb b/examples/howto/data_container.ipynb index 8e892f12f..4a845ccba 100644 --- a/examples/howto/data_container.ipynb +++ b/examples/howto/data_container.ipynb @@ -8,7 +8,7 @@ "# Using shared variables (`Data` container adaptation)\n", "\n", ":::{post} Dec 16, 2021\n", - ":tags: posterior predictive, predictions, pymc3.Bernoulli, pymc3.Data, pymc3.Deterministic, pymc3.HalfNormal, pymc3.Model, pymc3.Normal, shared data\n", + ":tags: posterior predictive, predictions, shared data \n", ":category: beginner\n", ":author: Juan Martin Loyola, Kavya Jaiswal, Oriol Abril\n", ":::" diff --git a/examples/howto/lasso_block_update.ipynb b/examples/howto/lasso_block_update.ipynb index 8c9e255bc..d5daeeec7 100644 --- a/examples/howto/lasso_block_update.ipynb +++ b/examples/howto/lasso_block_update.ipynb @@ -8,7 +8,7 @@ "# Lasso regression with block updating\n", "\n", ":::{post} Feb 10, 2022\n", - ":tags: pymc3.Exponential, pymc3.Laplace, pymc3.Metropolis, pymc3.Model, pymc3.Normal, pymc3.Slice, pymc3.Uniform, regression\n", + ":tags: regression \n", ":category: beginner\n", ":author: Chris Fonnesbeck, Raul Maldonado, Michael Osthege, Thomas Wiecki, Lorenzo Toniazzi\n", ":::" diff --git a/examples/mixture_models/dirichlet_mixture_of_multinomials.ipynb b/examples/mixture_models/dirichlet_mixture_of_multinomials.ipynb index 30965d36e..1b9504d87 100644 --- a/examples/mixture_models/dirichlet_mixture_of_multinomials.ipynb +++ b/examples/mixture_models/dirichlet_mixture_of_multinomials.ipynb @@ -8,7 +8,7 @@ "# Dirichlet mixtures of multinomials\n", "\n", ":::{post} Jan 8, 2022\n", - ":tags: mixture model, pymc3.Dirichlet, pymc3.DirichletMultinomial, pymc3.Lognormal, pymc3.Model, pymc3.Multinomial\n", + ":tags: mixture model, \n", ":category: advanced\n", ":author: Byron J. Smith, Abhipsha Das, Oriol Abril-Pla\n", ":::" diff --git a/examples/mixture_models/dp_mix.ipynb b/examples/mixture_models/dp_mix.ipynb index 23c1d48cc..3eeb14e2a 100644 --- a/examples/mixture_models/dp_mix.ipynb +++ b/examples/mixture_models/dp_mix.ipynb @@ -8,7 +8,7 @@ "# Dirichlet process mixtures for density estimation\n", "\n", ":::{post} Sept 16, 2021\n", - ":tags: mixture model, pymc3.Beta, pymc3.Deterministic, pymc3.Gamma, pymc3.Mixture, pymc3.Model, pymc3.Normal, pymc3.NormalMixture\n", + ":tags: mixture model, \n", ":category: advanced\n", ":author: Austin Rochford, Abhipsha Das\n", ":::" diff --git a/examples/mixture_models/gaussian_mixture_model.ipynb b/examples/mixture_models/gaussian_mixture_model.ipynb index 5c0747ca6..8c2b1b2a4 100644 --- a/examples/mixture_models/gaussian_mixture_model.ipynb +++ b/examples/mixture_models/gaussian_mixture_model.ipynb @@ -9,7 +9,7 @@ "# Gaussian Mixture Model\n", "\n", ":::{post} April, 2022\n", - ":tags: mixture model, classification\n", + ":tags: mixture model, classification \n", ":category: beginner\n", ":author: Abe Flaxman\n", ":::\n", diff --git a/examples/mixture_models/marginalized_gaussian_mixture_model.ipynb b/examples/mixture_models/marginalized_gaussian_mixture_model.ipynb index 8ba65d49b..6a8fd2db7 100644 --- a/examples/mixture_models/marginalized_gaussian_mixture_model.ipynb +++ b/examples/mixture_models/marginalized_gaussian_mixture_model.ipynb @@ -16,7 +16,7 @@ "# Marginalized Gaussian Mixture Model\n", "\n", ":::{post} Sept 18, 2021\n", - ":tags: mixture model, pymc3.Dirichlet, pymc3.Gamma, pymc3.Model, pymc3.Normal, pymc3.NormalMixture\n", + ":tags: mixture model, \n", ":category: intermediate\n", ":::" ] diff --git a/examples/samplers/SMC-ABC_Lotka-Volterra_example.ipynb b/examples/samplers/SMC-ABC_Lotka-Volterra_example.ipynb index d824eef87..afe778668 100644 --- a/examples/samplers/SMC-ABC_Lotka-Volterra_example.ipynb +++ b/examples/samplers/SMC-ABC_Lotka-Volterra_example.ipynb @@ -7,7 +7,7 @@ "(ABC_introduction)=\n", "# Approximate Bayesian Computation\n", ":::{post} May 31, 2022\n", - ":tags: SMC, ABC\n", + ":tags: SMC, ABC \n", ":category: beginner, explanation\n", ":::" ] diff --git a/examples/samplers/SMC2_gaussians.ipynb b/examples/samplers/SMC2_gaussians.ipynb index 77a73bef9..373924688 100644 --- a/examples/samplers/SMC2_gaussians.ipynb +++ b/examples/samplers/SMC2_gaussians.ipynb @@ -7,7 +7,7 @@ "# Sequential Monte Carlo\n", "\n", ":::{post} Oct 19, 2021\n", - ":tags: SMC\n", + ":tags: SMC \n", ":category: beginner\n", ":::" ] diff --git a/examples/survival_analysis/censored_data.ipynb b/examples/survival_analysis/censored_data.ipynb index 2c82a3d9c..46ec8c019 100644 --- a/examples/survival_analysis/censored_data.ipynb +++ b/examples/survival_analysis/censored_data.ipynb @@ -8,7 +8,7 @@ "# Censored Data Models\n", "\n", ":::{post} May, 2022\n", - ":tags: censoring, survival analysis\n", + ":tags: censoring, survival analysis \n", ":category: intermediate, how-to\n", ":author: Luis Mario Domenzain\n", ":::" diff --git a/examples/time_series/Air_passengers-Prophet_with_Bayesian_workflow.ipynb b/examples/time_series/Air_passengers-Prophet_with_Bayesian_workflow.ipynb index 9cc5c48c7..128ce436e 100644 --- a/examples/time_series/Air_passengers-Prophet_with_Bayesian_workflow.ipynb +++ b/examples/time_series/Air_passengers-Prophet_with_Bayesian_workflow.ipynb @@ -8,7 +8,7 @@ "# Air passengers - Prophet-like model\n", "\n", ":::{post} April, 2022\n", - ":tags: time series, prophet\n", + ":tags: time series, prophet \n", ":category: intermediate\n", ":author: Marco Gorelli, Danh Phan\n", ":::" diff --git a/examples/time_series/MvGaussianRandomWalk_demo.ipynb b/examples/time_series/MvGaussianRandomWalk_demo.ipynb index 9aed57dd8..16accb234 100644 --- a/examples/time_series/MvGaussianRandomWalk_demo.ipynb +++ b/examples/time_series/MvGaussianRandomWalk_demo.ipynb @@ -7,7 +7,7 @@ "source": [ "# Multivariate Gaussian Random Walk\n", ":::{post} Sep 25, 2021\n", - ":tags: linear model, pymc3.HalfNormal, pymc3.LKJCholeskyCov, pymc3.Model, pymc3.MvGaussianRandomWalk, pymc3.Normal, regression, time series\n", + ":tags: linear model, regression, time series \n", ":category: beginner\n", ":::" ] diff --git a/myst_nbs/case_studies/BART_introduction.myst.md b/myst_nbs/case_studies/BART_introduction.myst.md index fa4a8628d..58400a484 100644 --- a/myst_nbs/case_studies/BART_introduction.myst.md +++ b/myst_nbs/case_studies/BART_introduction.myst.md @@ -14,7 +14,7 @@ kernelspec: (BART_introduction)= # Bayesian Additive Regression Trees: Introduction :::{post} Dec 21, 2021 -:tags: BART, Bayesian additive regression trees, non-parametric, regression +:tags: BART, Bayesian additive regression trees, non-parametric, regression :category: intermediate, explanation :author: Osvaldo Martin ::: diff --git a/myst_nbs/case_studies/BEST.myst.md b/myst_nbs/case_studies/BEST.myst.md index e8b41fd4a..fe90f6405 100644 --- a/myst_nbs/case_studies/BEST.myst.md +++ b/myst_nbs/case_studies/BEST.myst.md @@ -15,7 +15,7 @@ kernelspec: # Bayesian Estimation Supersedes the T-Test :::{post} Jan 07, 2022 -:tags: hypothesis testing, model comparison, pymc3.Deterministic, pymc3.Exponential, pymc3.Model, pymc3.Normal, pymc3.StudentT, pymc3.Uniform +:tags: hypothesis testing, model comparison, :category: beginner :author: Andrew Straw, Thomas Wiecki, Chris Fonnesbeck, Andrés suárez ::: @@ -124,7 +124,7 @@ with model: az.plot_kde(rng.exponential(scale=30, size=10000), fill_kwargs={"alpha": 0.5}); ``` -Since PyMC parametrizes the Student-T in terms of precision, rather than standard deviation, we must transform the standard deviations before specifying our likelihoods. +Since PyMC parametrizes the Student-T in terms of precision, rather than standard deviation, we must transform the standard deviations before specifying our likelihoods. ```{code-cell} ipython3 with model: diff --git a/myst_nbs/case_studies/binning.myst.md b/myst_nbs/case_studies/binning.myst.md index 4b6595910..23bcb7db9 100644 --- a/myst_nbs/case_studies/binning.myst.md +++ b/myst_nbs/case_studies/binning.myst.md @@ -14,7 +14,7 @@ kernelspec: (awkward_binning)= # Estimating parameters of a distribution from awkwardly binned data :::{post} Oct 23, 2021 -:tags: binned data, case study, parameter estimation, pymc3.Bound, pymc3.Deterministic, pymc3.Gamma, pymc3.HalfNormal, pymc3.Model, pymc3.Multinomial, pymc3.Normal +:tags: binned data, case study, parameter estimation, :category: intermediate :author: Eric Ma, Benjamin T. Vincent ::: @@ -843,7 +843,7 @@ ax[1, 0].set(xlim=(0, 50), xlabel="BMI", ylabel="observed frequency", title="Sam ### Model specification -This is a variation of Example 3 above. The only changes are: +This is a variation of Example 3 above. The only changes are: - update the probability distribution to match our target (the Gumbel distribution) - ensure we specify priors for our target distribution, appropriate given our domain knowledge. diff --git a/myst_nbs/case_studies/blackbox_external_likelihood_numpy.myst.md b/myst_nbs/case_studies/blackbox_external_likelihood_numpy.myst.md index e999cc478..2ee5ccb0f 100644 --- a/myst_nbs/case_studies/blackbox_external_likelihood_numpy.myst.md +++ b/myst_nbs/case_studies/blackbox_external_likelihood_numpy.myst.md @@ -15,7 +15,7 @@ kernelspec: # Using a "black box" likelihood function (numpy) :::{post} Dec 16, 2021 -:tags: case study, external likelihood, pymc.Model, pymc.Normal, pymc.Potential, pymc.Uniform, pymc3.Model, pymc3.Normal, pymc3.Potential, pymc3.Uniform +:tags: case study, external likelihood, :category: beginner :author: Matt Pitkin, Jørgen Midtbø, Oriol Abril ::: @@ -447,7 +447,7 @@ with test_model: print(f'Gradient returned by PyMC "Normal" distribution: {grad_vals_pymc}') ``` -We could also do some profiling to compare performance between implementations. The {ref}`profiling` notebook shows how to do it. +We could also do some profiling to compare performance between implementations. The {ref}`profiling` notebook shows how to do it. +++ diff --git a/myst_nbs/case_studies/factor_analysis.myst.md b/myst_nbs/case_studies/factor_analysis.myst.md index 45b17bcf0..c45cb0d9e 100644 --- a/myst_nbs/case_studies/factor_analysis.myst.md +++ b/myst_nbs/case_studies/factor_analysis.myst.md @@ -18,7 +18,7 @@ substitutions: # Factor analysis :::{post} 19 Mar, 2022 -:tags: factor analysis, matrix factorization, pca +:tags: factor analysis, matrix factorization, pca :category: advanced, how-to :author: Chris Hartl, Christopher Krapu, Oriol Abril-Pla ::: @@ -136,7 +136,7 @@ for i in trace.posterior.chain.values: plt.legend(ncol=4, loc="upper center", fontsize=12, frameon=True), plt.xlabel("Sample"); ``` -Each chain appears to have a different sample mean and we can also see that there is a great deal of autocorrelation across chains, manifest as long-range trends over sampling iterations. Some of the chains may have divergences as well, lending further evidence to the claim that using MCMC for this model as shown is suboptimal. +Each chain appears to have a different sample mean and we can also see that there is a great deal of autocorrelation across chains, manifest as long-range trends over sampling iterations. Some of the chains may have divergences as well, lending further evidence to the claim that using MCMC for this model as shown is suboptimal. One of the primary drawbacks for this model formulation is its lack of identifiability. With this model representation, only the product $WF$ matters for the likelihood of $X$, so $P(X|W, F) = P(X|W\Omega, \Omega^{-1}F)$ for any invertible matrix $\Omega$. While the priors on $W$ and $F$ constrain $|\Omega|$ to be neither too large or too small, factors and loadings can still be rotated, reflected, and/or permuted *without changing the model likelihood*. Expect it to happen between runs of the sampler, or even for the parametrization to "drift" within run, and to produce the highly autocorrelated $W$ traceplot above. diff --git a/myst_nbs/case_studies/hierarchical_partial_pooling.myst.md b/myst_nbs/case_studies/hierarchical_partial_pooling.myst.md index 46e8438a6..44bb2a1ad 100644 --- a/myst_nbs/case_studies/hierarchical_partial_pooling.myst.md +++ b/myst_nbs/case_studies/hierarchical_partial_pooling.myst.md @@ -14,7 +14,7 @@ kernelspec: # Hierarchical Partial Pooling :::{post} Oct 07, 2021 -:tags: hierarchical model, pymc.Beta, pymc.Binomial, pymc.Deterministic, pymc.Exponential, pymc.Model, pymc.Uniform, pymc3.Beta, pymc3.Binomial, pymc3.Deterministic, pymc3.Exponential, pymc3.Model, pymc3.Uniform +:tags: hierarchical model, :category: intermediate ::: @@ -24,7 +24,7 @@ Suppose you are tasked with estimating baseball batting skills for several playe So, suppose a player came to bat only 4 times, and never hit the ball. Are they a bad player? -As a disclaimer, the author of this notebook assumes little to non-existent knowledge about baseball and its rules. The number of times at bat in his entire life is around "4". +As a disclaimer, the author of this notebook assumes little to non-existent knowledge about baseball and its rules. The number of times at bat in his entire life is around "4". ## Data diff --git a/myst_nbs/case_studies/item_response_nba.myst.md b/myst_nbs/case_studies/item_response_nba.myst.md index c07b68c3c..402b8f25e 100644 --- a/myst_nbs/case_studies/item_response_nba.myst.md +++ b/myst_nbs/case_studies/item_response_nba.myst.md @@ -15,7 +15,7 @@ kernelspec: # NBA Foul Analysis with Item Response Theory :::{post} Apr 17, 2022 -:tags: hierarchical model, case study, generalized linear model +:tags: hierarchical model, case study, generalized linear model :category: intermediate, tutorial :author: Austin Rochford, Lorenzo Toniazzi ::: @@ -465,7 +465,7 @@ else: ``` These plots suggest that scoring high in `theta` does not correlate with high or low scores in `b`. Moreover, with a little knowledge of NBA basketball, one can visually note that a higher score in `b` is expected from players playing center or forward rather than guards or point guards. -Given the last observation, we decide to plot a histogram for the occurrence of different positions for top disadvantaged (`theta`) and committing (`b`) players. Interestingly, we see below that the largest share of best disadvantaged players are guards, meanwhile, the largest share of best committing players are centers (and at the same time a very small share of guards). +Given the last observation, we decide to plot a histogram for the occurrence of different positions for top disadvantaged (`theta`) and committing (`b`) players. Interestingly, we see below that the largest share of best disadvantaged players are guards, meanwhile, the largest share of best committing players are centers (and at the same time a very small share of guards). ```{code-cell} ipython3 :tags: [] diff --git a/myst_nbs/case_studies/mediation_analysis.myst.md b/myst_nbs/case_studies/mediation_analysis.myst.md index c7c8f60d7..e64528a42 100644 --- a/myst_nbs/case_studies/mediation_analysis.myst.md +++ b/myst_nbs/case_studies/mediation_analysis.myst.md @@ -15,7 +15,7 @@ kernelspec: # Bayesian mediation analysis :::{post} February, 2022 -:tags: mediation, path analysis, regression +:tags: mediation, path analysis, regression :category: beginner :author: Benjamin T. Vincent ::: @@ -206,7 +206,7 @@ As we can see, the posterior distributions over the direct effects are near-iden +++ ## Parameter estimation versus hypothesis testing -This notebook has focused on the approach of Bayesian parameter estimation. For many situations this is entirely sufficient, and more information can be found in {cite:t}`yuan2009bayesian`. It will tell us, amongst other things, what our posterior beliefs are in the direct effects, indirect effects, and total effects. And we can use those posterior beliefs to conduct posterior predictive checks to visually check how well the model accounts for the data. +This notebook has focused on the approach of Bayesian parameter estimation. For many situations this is entirely sufficient, and more information can be found in {cite:t}`yuan2009bayesian`. It will tell us, amongst other things, what our posterior beliefs are in the direct effects, indirect effects, and total effects. And we can use those posterior beliefs to conduct posterior predictive checks to visually check how well the model accounts for the data. However, depending upon the use case it may be preferable to test hypotheses about the presence or absence of an indirect effect ($x \rightarrow m \rightarrow y$) for example. In this case, it may be more appropriate to take a more explicit hypothesis testing approach to see examine the relative credibility of the mediation model as compared to a simple direct effect model (i.e. $y_i = \mathrm{Normal}(i_{Y*} + c \cdot x_i, \sigma_{Y*})$). Readers are referred to {cite:t}`nuijten2015default` for a hypothesis testing approach to Bayesian mediation models and to {cite:t}`kruschke2011bayesian` for more information on parameter estimation versus hypothesis testing. diff --git a/myst_nbs/case_studies/moderation_analysis.myst.md b/myst_nbs/case_studies/moderation_analysis.myst.md index 4b1ea20a6..a8b78233c 100644 --- a/myst_nbs/case_studies/moderation_analysis.myst.md +++ b/myst_nbs/case_studies/moderation_analysis.myst.md @@ -15,7 +15,7 @@ kernelspec: # Bayesian moderation analysis :::{post} March, 2022 -:tags: moderation, path analysis, +:tags: moderation, path analysis, :category: beginner :author: Benjamin T. Vincent ::: diff --git a/myst_nbs/case_studies/multilevel_modeling.myst.md b/myst_nbs/case_studies/multilevel_modeling.myst.md index 00191cdd6..642042040 100644 --- a/myst_nbs/case_studies/multilevel_modeling.myst.md +++ b/myst_nbs/case_studies/multilevel_modeling.myst.md @@ -15,7 +15,7 @@ kernelspec: # A Primer on Bayesian Methods for Multilevel Modeling :::{post} 27 February, 2022 -:tags: hierarchical model, case study +:tags: hierarchical model, case study :category: intermediate :author: Chris Fonnesbeck, Colin Carroll, Alex Andorra, Oriol Abril, Farhan Reynaldo ::: @@ -1053,7 +1053,7 @@ az.summary(contextual_effect_trace, var_names=["g"], round_to=2) So we might infer from this that counties with higher proportions of houses without basements tend to have higher baseline levels of radon. This seems to be new, as up to this point we saw that `floor` was *negatively* associated with radon levels. But remember this was at the household-level: radon tends to be higher in houses with basements. But at the county-level it seems that the less basements on average in the county, the more radon. So it's not that contradictory. What's more, the estimate for $\gamma_2$ is quite uncertain and overlaps with zero, so it's possible that the relationship is not that strong. And finally, let's note that $\gamma_2$ estimates something else than uranium's effect, as this is already taken into account by $\gamma_1$ -- it answers the question "once we know uranium level in the county, is there any value in learning about the proportion of houses without basements?". -All of this is to say that we shouldn't interpret this causally: there is no credible mechanism by which a basement (or absence thereof) *causes* radon emissions. More probably, our causal graph is missing something: a confounding variable, one that influences both basement construction and radon levels, is lurking somewhere in the dark... Perhaps is it the type of soil, which might influence what type of structures are built *and* the level of radon? Maybe adding this to our model would help with causal inference. +All of this is to say that we shouldn't interpret this causally: there is no credible mechanism by which a basement (or absence thereof) *causes* radon emissions. More probably, our causal graph is missing something: a confounding variable, one that influences both basement construction and radon levels, is lurking somewhere in the dark... Perhaps is it the type of soil, which might influence what type of structures are built *and* the level of radon? Maybe adding this to our model would help with causal inference. +++ diff --git a/myst_nbs/case_studies/probabilistic_matrix_factorization.myst.md b/myst_nbs/case_studies/probabilistic_matrix_factorization.myst.md index 114a29f4c..9fc9d1b28 100644 --- a/myst_nbs/case_studies/probabilistic_matrix_factorization.myst.md +++ b/myst_nbs/case_studies/probabilistic_matrix_factorization.myst.md @@ -14,7 +14,7 @@ kernelspec: # Probabilistic Matrix Factorization for Making Personalized Recommendations :::{post} Sept 20, 2021 -:tags: case study, pymc3.Model, pymc3.MvNormal, pymc3.Normal +:tags: case study, :category: intermediate ::: @@ -721,7 +721,7 @@ print("Improvement from MAP: %.5f" % (pmf_map_rmse - final_test_rmse) print("Improvement from Mean of Means: %.5f" % (baselines["mom"] - final_test_rmse)) ``` -We have some interesting results here. As expected, our MCMC sampler provides lower error on the training set. However, it seems it does so at the cost of overfitting the data. This results in a decrease in test RMSE as compared to the MAP, even though it is still much better than our best baseline. So why might this be the case? Recall that we used point estimates for our precision parameters $\alpha_U$ and $\alpha_V$ and we chose a fixed precision $\alpha$. It is quite likely that by doing this, we constrained our posterior in a way that biased it towards the training data. In reality, the variance in the user ratings and the movie ratings is unlikely to be equal to the means of sample variances we used. Also, the most reasonable observation precision $\alpha$ is likely different as well. +We have some interesting results here. As expected, our MCMC sampler provides lower error on the training set. However, it seems it does so at the cost of overfitting the data. This results in a decrease in test RMSE as compared to the MAP, even though it is still much better than our best baseline. So why might this be the case? Recall that we used point estimates for our precision parameters $\alpha_U$ and $\alpha_V$ and we chose a fixed precision $\alpha$. It is quite likely that by doing this, we constrained our posterior in a way that biased it towards the training data. In reality, the variance in the user ratings and the movie ratings is unlikely to be equal to the means of sample variances we used. Also, the most reasonable observation precision $\alpha$ is likely different as well. +++ diff --git a/myst_nbs/case_studies/putting_workflow.myst.md b/myst_nbs/case_studies/putting_workflow.myst.md index ed7187c14..c78ab9438 100644 --- a/myst_nbs/case_studies/putting_workflow.myst.md +++ b/myst_nbs/case_studies/putting_workflow.myst.md @@ -18,7 +18,7 @@ substitutions: # Model building and expansion for golf putting :::{post} Apr 2, 2022 -:tags: bayesian workflow, model expansion, sports +:tags: bayesian workflow, model expansion, sports :category: intermediate, how-to :author: Colin Carroll, Marco Gorelli, Oriol Abril-Pla ::: diff --git a/myst_nbs/case_studies/regression_discontinuity.myst.md b/myst_nbs/case_studies/regression_discontinuity.myst.md index 940692df0..4a8f585d9 100644 --- a/myst_nbs/case_studies/regression_discontinuity.myst.md +++ b/myst_nbs/case_studies/regression_discontinuity.myst.md @@ -16,7 +16,7 @@ kernelspec: # Regression discontinuity design analysis :::{post} April, 2022 -:tags: regression, causal inference, quasi experimental design, counterfactuals +:tags: regression, causal inference, quasi experimental design, counterfactuals :category: beginner, explanation :author: Benjamin T. Vincent ::: @@ -219,7 +219,7 @@ The blue shaded region shows the 95% credible region of the expected value of th The orange shaded region shows the 95% credible region of the expected value of the post-test measurement for a range of possible pre-test measures in the case of treatment. -Both are actually very interesting as examples of counterfactual inference. We did not observe any units that were untreated below the threshold, nor any treated units above the threshold. But assuming our model is a good description of reality, we can ask the counterfactual questions "What if a unit above the threshold was treated?" and "What if a unit below the threshold was treated?" +Both are actually very interesting as examples of counterfactual inference. We did not observe any units that were untreated below the threshold, nor any treated units above the threshold. But assuming our model is a good description of reality, we can ask the counterfactual questions "What if a unit above the threshold was treated?" and "What if a unit below the threshold was treated?" +++ diff --git a/myst_nbs/case_studies/rugby_analytics.myst.md b/myst_nbs/case_studies/rugby_analytics.myst.md index a5e645958..a316ec6bc 100644 --- a/myst_nbs/case_studies/rugby_analytics.myst.md +++ b/myst_nbs/case_studies/rugby_analytics.myst.md @@ -16,7 +16,7 @@ substitutions: # A Hierarchical model for Rugby prediction :::{post} 19 Mar, 2022 -:tags: hierarchical, sports +:tags: hierarchical, sports :category: intermediate, how-to :author: Peadar Coyle, Meenal Jhajharia, Oriol Abril-Pla ::: @@ -468,7 +468,7 @@ We see according to this model that Ireland finishes with the most points about > As an Irish rugby fan - I like this model. However it indicates some problems with shrinkage, and bias. Since recent form suggests England will win. -Nevertheless the point of this model was to illustrate how a Hierarchical model could be applied to a sports analytics problem, and illustrate the power of PyMC. +Nevertheless the point of this model was to illustrate how a Hierarchical model could be applied to a sports analytics problem, and illustrate the power of PyMC. +++ diff --git a/myst_nbs/case_studies/spline.myst.md b/myst_nbs/case_studies/spline.myst.md index 237d53c92..f13abc8ad 100644 --- a/myst_nbs/case_studies/spline.myst.md +++ b/myst_nbs/case_studies/spline.myst.md @@ -15,7 +15,7 @@ kernelspec: # Splines :::{post} June 4, 2022 -:tags: patsy, regression, spline +:tags: patsy, regression, spline :category: beginner :author: Joshua Cook ::: diff --git a/myst_nbs/case_studies/wrapping_jax_function.myst.md b/myst_nbs/case_studies/wrapping_jax_function.myst.md index 077320d35..add11f1c0 100644 --- a/myst_nbs/case_studies/wrapping_jax_function.myst.md +++ b/myst_nbs/case_studies/wrapping_jax_function.myst.md @@ -17,7 +17,7 @@ substitutions: # How to wrap a JAX function for use in PyMC :::{post} Mar 24, 2022 -:tags: Aesara, hidden markov model, JAX +:tags: Aesara, hidden markov model, JAX :category: advanced, how-to :author: Ricardo Vieira ::: diff --git a/myst_nbs/diagnostics_and_criticism/Bayes_factor.myst.md b/myst_nbs/diagnostics_and_criticism/Bayes_factor.myst.md index 2df4b4f34..095c49353 100644 --- a/myst_nbs/diagnostics_and_criticism/Bayes_factor.myst.md +++ b/myst_nbs/diagnostics_and_criticism/Bayes_factor.myst.md @@ -14,7 +14,7 @@ kernelspec: (Bayes_factor)= # Bayes Factors and Marginal Likelihood :::{post} Jun 1, 2022 -:tags: Bayes Factors, model comparison +:tags: Bayes Factors, model comparison :category: beginner, explanation :author: Osvaldo Martin ::: diff --git a/myst_nbs/diagnostics_and_criticism/sampler-stats.myst.md b/myst_nbs/diagnostics_and_criticism/sampler-stats.myst.md index ef18c9d38..ad69e24ea 100644 --- a/myst_nbs/diagnostics_and_criticism/sampler-stats.myst.md +++ b/myst_nbs/diagnostics_and_criticism/sampler-stats.myst.md @@ -21,7 +21,7 @@ sampler is doing. For this purpose some samplers export statistics for each generated sample. :::{post} May 31, 2022 -:tags: diagnostics +:tags: diagnostics :category: beginner :author: Meenal Jhajharia, Christian Luhmann ::: diff --git a/myst_nbs/gaussian_processes/GP-MaunaLoa.myst.md b/myst_nbs/gaussian_processes/GP-MaunaLoa.myst.md index 10b729bb2..0e8f2a827 100644 --- a/myst_nbs/gaussian_processes/GP-MaunaLoa.myst.md +++ b/myst_nbs/gaussian_processes/GP-MaunaLoa.myst.md @@ -17,7 +17,7 @@ substitutions: # Gaussian Process for CO2 at Mauna Loa :::{post} April, 2022 -:tags: gaussian process, CO2 +:tags: gaussian process, CO2 :category: intermediate :author: Bill Engels, Chris Fonnesbeck ::: @@ -32,7 +32,7 @@ This Gaussian Process (GP) example shows how to: +++ -Since the late 1950's, the Mauna Loa observatory has been taking regular measurements of atmospheric CO$_2$. In the late 1950's Charles Keeling invented a accurate way to measure atmospheric CO$_2$ concentration. +Since the late 1950's, the Mauna Loa observatory has been taking regular measurements of atmospheric CO$_2$. In the late 1950's Charles Keeling invented a accurate way to measure atmospheric CO$_2$ concentration. Since then, CO$_2$ measurements have been recorded nearly continuously at the Mauna Loa observatory. Check out last hours measurement result [here](https://www.co2.earth/daily-co2). ![](http://sites.gsu.edu/geog1112/files/2014/07/MaunaLoaObservatory_small-2g29jvt.png) diff --git a/myst_nbs/generalized_linear_models/GLM-binomial-regression.myst.md b/myst_nbs/generalized_linear_models/GLM-binomial-regression.myst.md index 32db103b7..a8bdf8bd5 100644 --- a/myst_nbs/generalized_linear_models/GLM-binomial-regression.myst.md +++ b/myst_nbs/generalized_linear_models/GLM-binomial-regression.myst.md @@ -15,7 +15,7 @@ kernelspec: # Binomial regression :::{post} February, 2022 -:tags: binomial regression, generalized linear model, pymc.Binomial, pymc.ConstantData, pymc.Deterministic, pymc.Model, pymc.Normal, pymc3.Binomial, pymc3.ConstantData, pymc3.Deterministic, pymc3.Model, pymc3.Normal +:tags: binomial regression, generalized linear model, :category: beginner :author: Benjamin T. Vincent ::: diff --git a/myst_nbs/generalized_linear_models/GLM-hierarchical-binomial-model.myst.md b/myst_nbs/generalized_linear_models/GLM-hierarchical-binomial-model.myst.md index 375eff3bf..73c9bdba0 100644 --- a/myst_nbs/generalized_linear_models/GLM-hierarchical-binomial-model.myst.md +++ b/myst_nbs/generalized_linear_models/GLM-hierarchical-binomial-model.myst.md @@ -13,7 +13,7 @@ kernelspec: # Hierarchical Binomial Model: Rat Tumor Example :::{post} Nov 11, 2021 -:tags: generalized linear model, hierarchical model +:tags: generalized linear model, hierarchical model :category: intermediate :author: Demetri Pananos, Junpeng Lao, Raúl Maldonado, Farhan Reynaldo ::: diff --git a/myst_nbs/generalized_linear_models/GLM-model-selection.myst.md b/myst_nbs/generalized_linear_models/GLM-model-selection.myst.md index 9a721fbd1..05f136850 100644 --- a/myst_nbs/generalized_linear_models/GLM-model-selection.myst.md +++ b/myst_nbs/generalized_linear_models/GLM-model-selection.myst.md @@ -15,7 +15,7 @@ kernelspec: # GLM: Model Selection :::{post} Jan 8, 2022 -:tags: cross validation, generalized linear models, loo, model comparison, pymc3.HalfCauchy, pymc3.Model, pymc3.Normal, waic +:tags: cross validation, generalized linear models, loo, model comparison, waic :category: intermediate :author: Jon Sedar, Junpeng Lao, Abhipsha Das, Oriol Abril-Pla ::: @@ -45,7 +45,7 @@ plt.rcParams["figure.constrained_layout.use"] = False ``` ## Introduction -A fairly minimal reproducible example of Model Selection using WAIC, and LOO as currently implemented in PyMC3. +A fairly minimal reproducible example of Model Selection using WAIC, and LOO as currently implemented in PyMC3. This example creates two toy datasets under linear and quadratic models, and then tests the fit of a range of polynomial linear models upon those datasets by using Widely Applicable Information Criterion (WAIC), and leave-one-out (LOO) cross-validation using Pareto-smoothed importance sampling (PSIS). diff --git a/myst_nbs/generalized_linear_models/GLM-robust-with-outlier-detection.myst.md b/myst_nbs/generalized_linear_models/GLM-robust-with-outlier-detection.myst.md index 8def99cb3..8e422c8d5 100644 --- a/myst_nbs/generalized_linear_models/GLM-robust-with-outlier-detection.myst.md +++ b/myst_nbs/generalized_linear_models/GLM-robust-with-outlier-detection.myst.md @@ -17,7 +17,7 @@ substitutions: # GLM: Robust Regression using Custom Likelihood for Outlier Classification :::{post} 17 Nov, 2021 -:tags: pymc3.Bernoulli, pymc3.Data, pymc3.Deterministic, pymc3.DiscreteUniform, pymc3.Exponential, pymc3.GaussianRandomWalk, pymc3.HalfNormal, pymc3.InverseGamma, pymc3.Model, pymc3.Normal, pymc3.Poisson, pymc3.Potential, pymc3.Slice, pymc3.StudentT, pymc3.Uniform, regression, robust analysis +:tags: regression, robust analysis :category: intermediate :author: Jon Sedar, Thomas Wiecki, Raul Maldonado, Oriol Abril ::: @@ -613,7 +613,7 @@ _ = az.plot_trace(trc_hogg, var_names=rvs, compact=False); + However, at `target_accept = 0.9` (and increasing `tune` from 5000 to 10000), the traces exhibit fewer divergences and appear slightly better behaved. + The traces for the inlier model `beta` parameters, and for outlier model parameter `y_est_out` (the mean) look reasonably converged + The traces for outlier model param `y_sigma_out` (the additional pooled variance) occasionally go a bit wild -+ It's interesting that `frac_outliers` is so dispersed: that's quite a flat distribution: suggests that there are a few datapoints where their inlier/outlier status is subjective ++ It's interesting that `frac_outliers` is so dispersed: that's quite a flat distribution: suggests that there are a few datapoints where their inlier/outlier status is subjective + Indeed as Thomas noted in his v2.0 Notebook, because we're explicitly modeling the latent label (inlier/outlier) as binary choice the sampler could have a problem - rewriting this model into a marginal mixture model would be better. +++ diff --git a/myst_nbs/generalized_linear_models/GLM-rolling-regression.myst.md b/myst_nbs/generalized_linear_models/GLM-rolling-regression.myst.md index 08bbe89c1..3b0667ebb 100644 --- a/myst_nbs/generalized_linear_models/GLM-rolling-regression.myst.md +++ b/myst_nbs/generalized_linear_models/GLM-rolling-regression.myst.md @@ -15,7 +15,7 @@ kernelspec: # Rolling Regression :::{post} June, 2022 -:tags: generalized linear model, regression +:tags: generalized linear model, regression :category: intermediate :author: Thomas Wiecki ::: diff --git a/myst_nbs/generalized_linear_models/GLM-simpsons-paradox.myst.md b/myst_nbs/generalized_linear_models/GLM-simpsons-paradox.myst.md index c793944fc..b186d7849 100644 --- a/myst_nbs/generalized_linear_models/GLM-simpsons-paradox.myst.md +++ b/myst_nbs/generalized_linear_models/GLM-simpsons-paradox.myst.md @@ -15,7 +15,7 @@ kernelspec: # Simpson's paradox and mixed models :::{post} March, 2022 -:tags: regression, hierarchical model, linear model, multi level model, posterior predictive, Simpson's paradox +:tags: regression, hierarchical model, linear model, multi level model, posterior predictive, Simpson's paradox :category: beginner :author: Benjamin T. Vincent ::: diff --git a/myst_nbs/generalized_linear_models/GLM-truncated-censored-regression.myst.md b/myst_nbs/generalized_linear_models/GLM-truncated-censored-regression.myst.md index ff5afef7b..1f38861e5 100644 --- a/myst_nbs/generalized_linear_models/GLM-truncated-censored-regression.myst.md +++ b/myst_nbs/generalized_linear_models/GLM-truncated-censored-regression.myst.md @@ -15,7 +15,7 @@ kernelspec: # Bayesian regression with truncated or censored data :::{post} January, 2022 -:tags: censored, censoring, generalized linear model, pymc3.Censored, pymc3.HalfNormal, pymc3.Model, pymc3.Normal, pymc3.TruncatedNormal, regression, truncated, truncation +:tags: censored, censoring, generalized linear model, regression, truncated, truncation :category: beginner :author: Benjamin T. Vincent ::: @@ -356,7 +356,7 @@ This brings an end to our guide on truncated and censored data and truncated and ## Further topics It is also possible to treat the bounds as unknown latent parameters. If these are not known exactly and it is possible to fomulate a prior over these bounds, then it would be possible to infer what the bounds are. This could be argued as overkill however - depending on your data analysis context it may be entirely sufficient to extract 'good enough' point estimates of the bounds in order to get reasonable regression estimates. -The censored regression model presented above takes one particular approach, and there are others. For example, it did not attempt to infer posterior beliefs over the true latent `y` values of the censored data. It is possible to build censored regression models which do impute these censored `y` values, but we did not address that here as the topic of [imputation](https://en.wikipedia.org/wiki/Imputation_(statistics)) deserves its own focused treatment. The PyMC {ref}`censored_data` example also covers this topic, with a particular {ref}`example model to impute censored data `. +The censored regression model presented above takes one particular approach, and there are others. For example, it did not attempt to infer posterior beliefs over the true latent `y` values of the censored data. It is possible to build censored regression models which do impute these censored `y` values, but we did not address that here as the topic of [imputation](https://en.wikipedia.org/wiki/Imputation_(statistics)) deserves its own focused treatment. The PyMC {ref}`censored_data` example also covers this topic, with a particular {ref}`example model to impute censored data `. +++ diff --git a/myst_nbs/howto/data_container.myst.md b/myst_nbs/howto/data_container.myst.md index 7b380783e..8c67811e0 100644 --- a/myst_nbs/howto/data_container.myst.md +++ b/myst_nbs/howto/data_container.myst.md @@ -15,7 +15,7 @@ kernelspec: # Using shared variables (`Data` container adaptation) :::{post} Dec 16, 2021 -:tags: posterior predictive, predictions, pymc3.Bernoulli, pymc3.Data, pymc3.Deterministic, pymc3.HalfNormal, pymc3.Model, pymc3.Normal, shared data +:tags: posterior predictive, predictions, shared data :category: beginner :author: Juan Martin Loyola, Kavya Jaiswal, Oriol Abril ::: diff --git a/myst_nbs/howto/lasso_block_update.myst.md b/myst_nbs/howto/lasso_block_update.myst.md index 5aa47ea25..2bbd83671 100644 --- a/myst_nbs/howto/lasso_block_update.myst.md +++ b/myst_nbs/howto/lasso_block_update.myst.md @@ -15,7 +15,7 @@ kernelspec: # Lasso regression with block updating :::{post} Feb 10, 2022 -:tags: pymc3.Exponential, pymc3.Laplace, pymc3.Metropolis, pymc3.Model, pymc3.Normal, pymc3.Slice, pymc3.Uniform, regression +:tags: regression :category: beginner :author: Chris Fonnesbeck, Raul Maldonado, Michael Osthege, Thomas Wiecki, Lorenzo Toniazzi ::: diff --git a/myst_nbs/mixture_models/dirichlet_mixture_of_multinomials.myst.md b/myst_nbs/mixture_models/dirichlet_mixture_of_multinomials.myst.md index 47ce4864f..51a15e64a 100644 --- a/myst_nbs/mixture_models/dirichlet_mixture_of_multinomials.myst.md +++ b/myst_nbs/mixture_models/dirichlet_mixture_of_multinomials.myst.md @@ -15,7 +15,7 @@ kernelspec: # Dirichlet mixtures of multinomials :::{post} Jan 8, 2022 -:tags: mixture model, pymc3.Dirichlet, pymc3.DirichletMultinomial, pymc3.Lognormal, pymc3.Model, pymc3.Multinomial +:tags: mixture model, :category: advanced :author: Byron J. Smith, Abhipsha Das, Oriol Abril-Pla ::: diff --git a/myst_nbs/mixture_models/dp_mix.myst.md b/myst_nbs/mixture_models/dp_mix.myst.md index 11c070b94..e97d5af6b 100644 --- a/myst_nbs/mixture_models/dp_mix.myst.md +++ b/myst_nbs/mixture_models/dp_mix.myst.md @@ -15,7 +15,7 @@ kernelspec: # Dirichlet process mixtures for density estimation :::{post} Sept 16, 2021 -:tags: mixture model, pymc3.Beta, pymc3.Deterministic, pymc3.Gamma, pymc3.Mixture, pymc3.Model, pymc3.Normal, pymc3.NormalMixture +:tags: mixture model, :category: advanced :author: Austin Rochford, Abhipsha Das ::: diff --git a/myst_nbs/mixture_models/gaussian_mixture_model.myst.md b/myst_nbs/mixture_models/gaussian_mixture_model.myst.md index 0d04e8f35..1546f2d5b 100644 --- a/myst_nbs/mixture_models/gaussian_mixture_model.myst.md +++ b/myst_nbs/mixture_models/gaussian_mixture_model.myst.md @@ -15,7 +15,7 @@ kernelspec: # Gaussian Mixture Model :::{post} April, 2022 -:tags: mixture model, classification +:tags: mixture model, classification :category: beginner :author: Abe Flaxman ::: diff --git a/myst_nbs/mixture_models/marginalized_gaussian_mixture_model.myst.md b/myst_nbs/mixture_models/marginalized_gaussian_mixture_model.myst.md index 0dc30dc44..0ed1504df 100644 --- a/myst_nbs/mixture_models/marginalized_gaussian_mixture_model.myst.md +++ b/myst_nbs/mixture_models/marginalized_gaussian_mixture_model.myst.md @@ -16,7 +16,7 @@ kernelspec: # Marginalized Gaussian Mixture Model :::{post} Sept 18, 2021 -:tags: mixture model, pymc3.Dirichlet, pymc3.Gamma, pymc3.Model, pymc3.Normal, pymc3.NormalMixture +:tags: mixture model, :category: intermediate ::: diff --git a/myst_nbs/samplers/SMC-ABC_Lotka-Volterra_example.myst.md b/myst_nbs/samplers/SMC-ABC_Lotka-Volterra_example.myst.md index e81ebca59..236ce5e3b 100644 --- a/myst_nbs/samplers/SMC-ABC_Lotka-Volterra_example.myst.md +++ b/myst_nbs/samplers/SMC-ABC_Lotka-Volterra_example.myst.md @@ -14,7 +14,7 @@ kernelspec: (ABC_introduction)= # Approximate Bayesian Computation :::{post} May 31, 2022 -:tags: SMC, ABC +:tags: SMC, ABC :category: beginner, explanation ::: diff --git a/myst_nbs/samplers/SMC2_gaussians.myst.md b/myst_nbs/samplers/SMC2_gaussians.myst.md index 6e4dc18f3..8d9b02910 100644 --- a/myst_nbs/samplers/SMC2_gaussians.myst.md +++ b/myst_nbs/samplers/SMC2_gaussians.myst.md @@ -14,7 +14,7 @@ kernelspec: # Sequential Monte Carlo :::{post} Oct 19, 2021 -:tags: SMC +:tags: SMC :category: beginner ::: diff --git a/myst_nbs/survival_analysis/censored_data.myst.md b/myst_nbs/survival_analysis/censored_data.myst.md index 029581afc..90b7c9793 100644 --- a/myst_nbs/survival_analysis/censored_data.myst.md +++ b/myst_nbs/survival_analysis/censored_data.myst.md @@ -15,7 +15,7 @@ kernelspec: # Censored Data Models :::{post} May, 2022 -:tags: censoring, survival analysis +:tags: censoring, survival analysis :category: intermediate, how-to :author: Luis Mario Domenzain ::: diff --git a/myst_nbs/time_series/Air_passengers-Prophet_with_Bayesian_workflow.myst.md b/myst_nbs/time_series/Air_passengers-Prophet_with_Bayesian_workflow.myst.md index 2dda3b1ae..1a7ec7fc4 100644 --- a/myst_nbs/time_series/Air_passengers-Prophet_with_Bayesian_workflow.myst.md +++ b/myst_nbs/time_series/Air_passengers-Prophet_with_Bayesian_workflow.myst.md @@ -15,7 +15,7 @@ kernelspec: # Air passengers - Prophet-like model :::{post} April, 2022 -:tags: time series, prophet +:tags: time series, prophet :category: intermediate :author: Marco Gorelli, Danh Phan ::: diff --git a/myst_nbs/time_series/MvGaussianRandomWalk_demo.myst.md b/myst_nbs/time_series/MvGaussianRandomWalk_demo.myst.md index 8f2ba4d40..77b375a46 100644 --- a/myst_nbs/time_series/MvGaussianRandomWalk_demo.myst.md +++ b/myst_nbs/time_series/MvGaussianRandomWalk_demo.myst.md @@ -13,7 +13,7 @@ kernelspec: # Multivariate Gaussian Random Walk :::{post} Sep 25, 2021 -:tags: linear model, pymc3.HalfNormal, pymc3.LKJCholeskyCov, pymc3.Model, pymc3.MvGaussianRandomWalk, pymc3.Normal, regression, time series +:tags: linear model, regression, time series :category: beginner :::