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MarcoGorelliMarcoGorelli
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CLN, STYLE fix imports in gp-maunaloa until rugby analytics (#4079)
* fix gp-maunaloa until rugby analytics * move %env after imports
1 parent 3159da7 commit 9b1f3e5

10 files changed

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-34
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‎docs/source/notebooks/GP-MaunaLoa.ipynb

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@@ -383,10 +383,10 @@
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"import pymc3 as pm\n",
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"import theano.tensor as tt\n",
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"\n",
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"from bokeh.plotting import figure, show\n",
387-
"from bokeh.models import BoxAnnotation, Span, Label, Legend\n",
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"from bokeh.io import output_notebook\n",
387+
"from bokeh.models import BoxAnnotation, Label, Legend, Span\n",
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"from bokeh.palettes import brewer\n",
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"from bokeh.plotting import figure, show\n",
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"\n",
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"output_notebook()"
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]

‎docs/source/notebooks/GP-MaunaLoa2.ipynb

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@@ -1550,9 +1550,10 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"from datetime import datetime as dt\n",
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"import time\n",
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"\n",
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"from datetime import datetime as dt\n",
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"\n",
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"\n",
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"def toYearFraction(date):\n",
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" date = pd.to_datetime(date)\n",

‎docs/source/notebooks/GP-TProcess.ipynb

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@@ -40,11 +40,11 @@
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}
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],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import pymc3 as pm\n",
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"import theano.tensor as tt\n",
45-
"import numpy as np\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline"
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]
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},
@@ -298,6 +298,7 @@
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"source": [
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"fig = plt.figure(figsize=(12,5)); ax = fig.gca()\n",
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"from pymc3.gp.util import plot_gp_dist\n",
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"\n",
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"plot_gp_dist(ax, np.square(pred_samples[\"f_pred\"]), X_new);\n",
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"plt.plot(X, np.square(f_true), \"dodgerblue\", lw=3, label=\"True f\");\n",
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"plt.plot(X, y, 'ok', ms=3, alpha=0.5, label=\"Observed data\");\n",

‎docs/source/notebooks/ODE_API_shapes_and_benchmarking.ipynb

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@@ -17,6 +17,7 @@
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"os.environ[\"THEANO_FLAGS\"] = \"floatX=float64\""
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]
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},
@@ -27,14 +28,15 @@
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"outputs": [],
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"source": [
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"import logging\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
32-
"from scipy.integrate import odeint\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
33+
"import numpy as np\n",
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"import pymc3 as pm\n",
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"import theano\n",
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"import theano.tensor as tt\n",
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"\n",
38+
"from scipy.integrate import odeint\n",
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"\n",
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"# this notebook show DEBUG log messages\n",
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"logging.getLogger('pymc3').setLevel(logging.DEBUG)\n",
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"\n",
@@ -318,6 +320,7 @@
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"outputs": [],
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"source": [
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"from theano import d3viz\n",
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"\n",
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"d3viz.d3viz(model.logpt, 'ODE_API_shapes_and_benchmarking.html')"
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]
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},

‎docs/source/notebooks/ODE_with_manual_gradients.ipynb

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@@ -6,12 +6,13 @@
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"metadata": {},
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"outputs": [],
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"source": [
9-
"from scipy.integrate import odeint\n",
10-
"import numpy as np\n",
11-
"import theano \n",
12-
"from theano import *\n",
139
"import matplotlib.pyplot as plt\n",
10+
"import numpy as np\n",
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"import pymc3 as pm\n",
12+
"import theano\n",
13+
"\n",
14+
"from scipy.integrate import odeint\n",
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"from theano import *\n",
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"\n",
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"THEANO_FLAGS='optimizer=fast_compile'"
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]
@@ -657,6 +658,7 @@
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],
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"source": [
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"import pandas as pd\n",
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"\n",
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"summary = pm.summary(trace)\n",
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"STAN_mus = [0.549, 0.028, 0.797, 0.024, 33.960, 5.949, 0.248, 0.252]\n",
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"STAN_sds = [0.065, 0.004, 0.091, 0.004, 2.909, 0.533, 0.045, 0.044]\n",
@@ -856,8 +858,10 @@
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"outputs": [],
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"source": [
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"import theano.tensor as tt\n",
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"\n",
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"from theano.compile.ops import as_op\n",
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"\n",
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"\n",
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"@as_op(itypes=[tt.dscalar,tt.dscalar,tt.dscalar], otypes=[tt.dmatrix])\n",
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"def th_forward_model(param1,param2,param3):\n",
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" \n",

‎docs/source/notebooks/hierarchical_partial_pooling.ipynb

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@@ -53,6 +53,7 @@
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"import pandas as pd\n",
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"import pymc3 as pm\n",
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"import theano.tensor as tt\n",
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"\n",
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"%matplotlib inline"
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]
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},

‎docs/source/notebooks/lasso_block_update.ipynb

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@@ -20,9 +20,10 @@
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"outputs": [],
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"source": [
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"%matplotlib inline\n",
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"import numpy as np\n",
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"\n",
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"from matplotlib.pylab import *\n",
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"from pymc3 import * \n",
25-
"import numpy as np \n",
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"from pymc3 import *\n",
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"\n",
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"d = np.random.normal(size=(3, 30))\n",
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"d1 = d[0] + 4\n",

‎docs/source/notebooks/lda-advi-aevb.ipynb

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@@ -36,27 +36,31 @@
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],
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"source": [
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"%matplotlib inline\n",
39-
"import sys, os\n",
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"# unfortunately I was not able to run it on GPU due to overflow problems\n",
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"%env THEANO_FLAGS=device=cpu,floatX=float64\n",
42-
"import theano\n",
39+
"import os\n",
40+
"import sys\n",
4341
"\n",
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"from collections import OrderedDict\n",
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"from copy import deepcopy\n",
46-
"import numpy as np\n",
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"from time import time\n",
48-
"from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\n",
49-
"from sklearn.datasets import fetch_20newsgroups\n",
45+
"\n",
5046
"import matplotlib.pyplot as plt\n",
47+
"import numpy as np\n",
48+
"import pymc3 as pm\n",
5149
"import seaborn as sns\n",
52-
"from theano import shared\n",
50+
"import theano\n",
5351
"import theano.tensor as tt\n",
54-
"from theano.sandbox.rng_mrg import MRG_RandomStreams\n",
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"\n",
56-
"import pymc3 as pm\n",
57-
"from pymc3 import math as pmmath\n",
5853
"from pymc3 import Dirichlet\n",
54+
"from pymc3 import math as pmmath\n",
5955
"from pymc3.distributions.transforms import t_stick_breaking\n",
56+
"from sklearn.datasets import fetch_20newsgroups\n",
57+
"from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
58+
"from theano import shared\n",
59+
"from theano.sandbox.rng_mrg import MRG_RandomStreams\n",
60+
"\n",
61+
"# unfortunately I was not able to run it on GPU due to overflow problems\n",
62+
"%env THEANO_FLAGS=device=cpu,floatX=float64\n",
63+
"\n",
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"plt.style.use('seaborn-darkgrid')"
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]
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},

‎docs/source/notebooks/normalizing_flows_overview.ipynb

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@@ -23,13 +23,14 @@
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"outputs": [],
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"source": [
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"%matplotlib inline\n",
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"from collections import Counter\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
27-
"import seaborn as sns\n",
28-
"import pymc3 as pm\n",
2929
"import numpy as np\n",
30+
"import pymc3 as pm\n",
31+
"import seaborn as sns\n",
3032
"import theano\n",
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"import theano.tensor as tt\n",
32-
"from collections import Counter\n",
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"\n",
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"pm.set_tt_rng(42)\n",
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"np.random.seed(42)"
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"outputs": [],
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"source": [
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"from pymc3.distributions.dist_math import bound\n",
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"\n",
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"\n",
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"def cust_logp(z):\n",
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" #return bound(-pot1(z), z>-5, z<5)\n",
397400
" return -pot1(z)\n",
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"metadata": {},
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"outputs": [],
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"source": [
651-
"from collections import defaultdict, OrderedDict\n",
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"from collections import OrderedDict, defaultdict\n",
652655
"from itertools import count\n",
653656
"\n",
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"\n",
654658
"@theano.configparser.change_flags(compute_test_value='off')\n",
655659
"def get_tracker(inference):\n",
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" numbers = defaultdict(count)\n",

‎docs/source/notebooks/rugby_analytics.ipynb

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@@ -44,14 +44,19 @@
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"\n",
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"import numpy as np\n",
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"import pandas as pd\n",
47+
"\n",
4748
"try:\n",
4849
" from StringIO import StringIO\n",
4950
"except ImportError:\n",
5051
" from io import StringIO\n",
51-
"import pymc3 as pm, theano.tensor as tt\n",
52+
"\n",
5253
"import matplotlib.pyplot as plt\n",
53-
"from matplotlib.ticker import StrMethodFormatter\n",
54+
"import pymc3 as pm\n",
5455
"import seaborn as sns\n",
56+
"import theano.tensor as tt\n",
57+
"\n",
58+
"from matplotlib.ticker import StrMethodFormatter\n",
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"\n",
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"%matplotlib inline"
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]
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},
@@ -349,7 +354,7 @@
349354
" \n",
350355
" .plot(kind='bar', title='Average magnitude of scores difference Six Nations', yerr=df_all.groupby('year')['difference'].std())\n",
351356
" .set_ylabel('Average (abs) point difference'));\n",
352-
" \n"
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" "
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]
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},
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{
@@ -512,7 +517,7 @@
512517
" .rename_axis(\"Home_Team\")\n",
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" .plot(kind='bar', rot=0, legend=False)\n",
514519
" .set_ylabel('Score difference Home team and away team')\n",
515-
");\n"
520+
");"
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]
517522
},
518523
{
@@ -545,7 +550,7 @@
545550
" .rename_axis(\"Away_Team\")\n",
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" .plot(kind='bar', rot=0, legend=False)\n",
547552
" .set_ylabel('Score difference Home team and away team')\n",
548-
");\n"
553+
");"
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]
550555
},
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{

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