🎉 Finish residual replacement for Pymc3 plots to arviz & sigma param change

Author: CloudChaoszero

examples/case_studies/BEST.ipynb

@@ -21,6 +21,8 @@
     }
    ],
    "source": [
+    "import warnings\n",
+    "\n",
     "import arviz as az\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
@@ -36,8 +38,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "warnings.filterwarnings('ignore')"
+    "warnings.filterwarnings(\"ignore\")"
    ]
   },
   {

examples/case_studies/LKJ.ipynb

@@ -40,7 +40,9 @@
    "outputs": [],
    "source": [
     "az.style.use(\"arviz-darkgrid\")\n",
+    "\n",
     "warnings.simplefilter(action=\"ignore\", category=FutureWarning)\n",
+    "\n",
     "RANDOM_SEED = 8924\n",
     "np.random.seed(3264602)  # from random.org"
    ]

examples/case_studies/factor_analysis.ipynb

@@ -40,7 +40,9 @@
    "source": [
     "%config InlineBackend.figure_format = 'retina'\n",
     "az.style.use(\"arviz-darkgrid\")\n",
+    "\n",
     "warnings.filterwarnings(\"ignore\")\n",
+    "\n",
     "np.set_printoptions(precision=3, suppress=True)\n",
     "np.random.seed(314159)"
    ]

examples/case_studies/multilevel_modeling.ipynb

@@ -76,7 +76,9 @@
     "from theano import tensor as tt\n",
     "\n",
     "print(f\"Running on PyMC3 v{pm.__version__}\")\n",
+    "\n",
     "warnings.simplefilter(action=\"ignore\", category=FutureWarning)\n",
+    "\n",
     "RANDOM_SEED = 8924\n",
     "np.random.seed(286)"
    ]

examples/case_studies/putting_workflow.ipynb

@@ -15,6 +15,7 @@
    ],
    "source": [
     "import io\n",
+    "import warnings\n",
     "\n",
     "import arviz as az\n",
     "import matplotlib.pyplot as plt\n",
@@ -33,8 +34,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "\n",
     "warnings.filterwarnings(\"ignore\")"
    ]
   },

examples/diagnostics_and_criticism/Bayes_factor.ipynb

@@ -694,7 +694,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/gaussian_processes/GP-Latent.ipynb

@@ -104,6 +104,8 @@
    },
    "outputs": [],
    "source": [
+    "import warnings\n",
+    "\n",
     "import arviz as az\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
@@ -129,8 +131,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "\n",
     "# mute future warnings from theano\n",
     "warnings.simplefilter(action=\"ignore\", category=FutureWarning)"
    ]
@@ -996,9 +996,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python (PyMC3 Dev)",
    "language": "python",
-   "name": "python3"
+   "name": "pymc3-dev"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1010,7 +1010,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/gaussian_processes/GP-MaunaLoa2.ipynb

@@ -2500,9 +2500,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "dev-pymc",
+   "display_name": "Python (PyMC3 Dev)",
    "language": "python",
-   "name": "dev-pymc"
+   "name": "pymc3-dev"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2514,7 +2514,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.11"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/gaussian_processes/GP-MeansAndCovs.ipynb

@@ -1702,9 +1702,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "pymc3",
+   "display_name": "Python (PyMC3 Dev)",
    "language": "python",
-   "name": "pymc3"
+   "name": "pymc3-dev"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1716,7 +1716,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.6"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/gaussian_processes/GP-SparseApprox.ipynb

@@ -477,9 +477,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python (PyMC3 Dev)",
    "language": "python",
-   "name": "python3"
+   "name": "pymc3-dev"
   },
   "language_info": {
    "codemirror_mode": {
@@ -491,7 +491,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.7"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/gaussian_processes/GP-TProcess.ipynb

@@ -362,7 +362,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.2"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/gaussian_processes/GP-smoothing.ipynb

@@ -585,9 +585,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python (PyMC3 Dev)",
    "language": "python",
-   "name": "python3"
+   "name": "pymc3-dev"
   },
   "language_info": {
    "codemirror_mode": {
@@ -599,7 +599,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.7"
+   "version": "3.8.5"
   },
   "latex_envs": {
    "bibliofile": "biblio.bib",

examples/generalized_linear_models/GLM-hierarchical-binominal-model.ipynb

@@ -21,6 +21,8 @@
     }
    ],
    "source": [
+    "import warnings\n",
+    "\n",
     "import arviz as az\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
@@ -41,8 +43,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "\n",
     "warnings.filterwarnings(\"ignore\")"
    ]
   },

examples/generalized_linear_models/GLM-linear.ipynb

@@ -87,6 +87,8 @@
     }
    ],
    "source": [
+    "import warnings\n",
+    "\n",
     "import arviz as az\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
@@ -103,8 +105,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "\n",
     "warnings.filterwarnings(\"ignore\")"
    ]
   },

examples/generalized_linear_models/GLM-logistic.ipynb

@@ -29,6 +29,8 @@
     }
    ],
    "source": [
+    "import warnings\n",
+    "\n",
     "from collections import OrderedDict\n",
     "from time import time\n",
     "\n",
@@ -53,8 +55,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "\n",
     "warnings.filterwarnings(\"ignore\")"
    ]
   },

examples/generalized_linear_models/GLM-model-selection.ipynb

@@ -21,6 +21,8 @@
     }
    ],
    "source": [
+    "import warnings\n",
+    "\n",
     "from collections import OrderedDict\n",
     "\n",
     "import arviz as az\n",
@@ -41,8 +43,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "\n",
     "warnings.filterwarnings(\"ignore\")"
    ]
   },

examples/generalized_linear_models/GLM-robust-with-outlier-detection.ipynb

@@ -143,8 +143,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "\n",
     "warnings.filterwarnings(\"ignore\")"
    ]
   },

examples/mixture_models/gaussian_mixture_model.ipynb

@@ -218,7 +218,7 @@
     }
    ],
    "source": [
-    "pm.traceplot(tr, var_names=[\"p\", \"sd\", \"means\"]);"
+    "az.plot_trace(tr, var_names=[\"p\", \"sd\", \"means\"]);"
    ]
   },
   {
@@ -259,7 +259,7 @@
    ],
    "source": [
     "# take a look at traceplot for some model parameters\n",
-    "pm.plots.traceplot(tr[::5], var_names=[\"p\", \"sd\", \"means\"]);"
+    "az.plot_trace(tr[::5], var_names=[\"p\", \"sd\", \"means\"]);"
    ]
   },
   {
@@ -293,7 +293,7 @@
    ],
    "source": [
     "# I prefer autocorrelation plots for serious confirmation of MCMC convergence\n",
-    "pm.autocorrplot(tr[::5], var_names=[\"sd\"]);"
+    "az.plot_autocorr(tr[::5], var_names=[\"sd\"]);"
    ]
   },
   {

examples/mixture_models/marginalized_gaussian_mixture_model.ipynb

@@ -606,22 +606,6 @@
     "%load_ext watermark\n",
     "%watermark -n -u -v -iv -w"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "papermill": {
-     "duration": 0.04472,
-     "end_time": "2020-12-20T20:58:55.101908",
-     "exception": false,
-     "start_time": "2020-12-20T20:58:55.057188",
-     "status": "completed"
-    },
-    "tags": []
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

examples/ode_models/ODE_API_shapes_and_benchmarking.ipynb

@@ -29,6 +29,7 @@
    "source": [
     "import logging\n",
     "\n",
+    "import arviz\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import pymc3 as pm\n",
@@ -40,7 +41,6 @@
     "# this notebook show DEBUG log messages\n",
     "logging.getLogger(\"pymc3\").setLevel(logging.DEBUG)\n",
     "\n",
-    "import arviz\n",
     "import IPython.display"
    ]
   },

examples/ode_models/ODE_with_manual_gradients.ipynb

@@ -6,6 +6,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import warnings\n",
+    "\n",
     "import arviz as az\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
@@ -24,8 +26,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import warnings\n",
-    "\n",
     "warnings.filterwarnings(\"ignore\", category=FutureWarning)"
    ]
   },

examples/pymc3_howto/lasso_block_update.ipynb

@@ -41,7 +41,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "warnings.filterwarnings(\"ignore\", category=DeprecationWarning)"
+    "warnings.filterwarnings(\"ignore\")"
    ]
   },
   {