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Replacing PyMC3 plots w/ Arviz plots & sigma Param change [Part 2] #26

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Merged
merged 5 commits into from
Mar 8, 2021
Merged

Replacing PyMC3 plots w/ Arviz plots & sigma Param change [Part 2] #26

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6f1a2a2
:art: Update plots from pymc to arviz dependencies & replace param sd…
CloudChaoszero Jan 19, 2021
fd1e946
Use return_inference to get proper Notebook output and change param v…
CloudChaoszero Feb 5, 2021
e666460
unstage multilevel_modeling
CloudChaoszero Feb 6, 2021
810dd7a
:art: Remove Warning Ignores and re-run files
CloudChaoszero Feb 8, 2021
05ab6b3
:art: Remove Warning Ignores and re-run files
CloudChaoszero Feb 8, 2021
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260 changes: 107 additions & 153 deletions examples/case_studies/BEST.ipynb
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4 changes: 3 additions & 1 deletion examples/case_studies/LKJ.ipynb
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Expand Up @@ -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"
]
Expand Down Expand Up @@ -716,7 +718,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "pymc3-dev",
"display_name": "Python (PyMC3 Dev)",
"language": "python",
"name": "pymc3-dev"
},
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10 changes: 5 additions & 5 deletions examples/case_studies/blackbox_external_likelihood.ipynb
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Expand Up @@ -320,7 +320,7 @@
" trace = pm.sample(ndraws, tune=nburn, discard_tuned_samples=True)\n",
"\n",
"# plot the traces\n",
"_ = pm.traceplot(trace, lines={\"m\": mtrue, \"c\": ctrue})\n",
"_ = az.plot_trace(trace, lines={\"m\": mtrue, \"c\": ctrue})\n",
"\n",
"# put the chains in an array (for later!)\n",
"samples_pymc3 = np.vstack((trace[\"m\"], trace[\"c\"])).T"
Expand Down Expand Up @@ -616,7 +616,7 @@
" trace = pm.sample(ndraws, tune=nburn, discard_tuned_samples=True)\n",
"\n",
"# plot the traces\n",
"_ = pm.traceplot(trace, lines={\"m\": mtrue, \"c\": ctrue})\n",
"_ = az.plot_trace(trace, lines={\"m\": mtrue, \"c\": ctrue})\n",
"\n",
"# put the chains in an array (for later!)\n",
"samples_pymc3_2 = np.vstack((trace[\"m\"], trace[\"c\"])).T"
Expand Down Expand Up @@ -644,12 +644,12 @@
" theta = tt.as_tensor_variable([m, c])\n",
"\n",
" # use a Normal distribution\n",
" pm.Normal(\"likelihood\", mu=(m * x + c), sd=sigma, observed=data)\n",
" pm.Normal(\"likelihood\", mu=(m * x + c), sigma=sigma, observed=data)\n",
"\n",
" trace = pm.sample(ndraws, tune=nburn, discard_tuned_samples=True)\n",
"\n",
"# plot the traces\n",
"_ = pm.traceplot(trace, lines={\"m\": mtrue, \"c\": ctrue})\n",
"_ = az.plot_trace(trace, lines={\"m\": mtrue, \"c\": ctrue})\n",
"\n",
"# put the chains in an array (for later!)\n",
"samples_pymc3_3 = np.vstack((trace[\"m\"], trace[\"c\"])).T"
Expand Down Expand Up @@ -832,7 +832,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.2"
"version": "3.8.5"
}
},
"nbformat": 4,
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10 changes: 5 additions & 5 deletions examples/case_studies/conditional-autoregressive-model.ipynb
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Expand Up @@ -122,7 +122,7 @@
"\n",
"The classical `WinBUGS` implementation (more information [here](http://glau.ca/?p=340)):\n",
"\n",
"```\n",
"```python\n",
"model\n",
"{\n",
" for (i in 1 : regions) {\n",
Expand Down Expand Up @@ -2717,7 +2717,7 @@
}
],
"source": [
"summary2 = pm.summary(infdata2)\n",
"summary2 = az.summary(infdata2)\n",
"summary2[summary2[\"r_hat\"] > 1.05]"
]
},
Expand Down Expand Up @@ -3004,7 +3004,7 @@
"Note that in the node $\\phi \\sim \\mathcal{N}(0, [D_\\tau (I - \\alpha B)]^{-1})$, we are computing the log-likelihood for a multivariate Gaussian distribution, which might not scale well in high-dimensions. We can take advantage of the fact that the covariance matrix here $[D_\\tau (I - \\alpha B)]^{-1}$ is **sparse**, and there are faster ways to compute its log-likelihood. \n",
"\n",
"For example, a more efficient sparse representation of the CAR in `Stan`:\n",
"```\n",
"```python\n",
"functions {\n",
" /**\n",
" * Return the log probability of a proper conditional autoregressive (CAR) prior \n",
Expand Down Expand Up @@ -3040,7 +3040,7 @@
" - tau * (phit_D * phi - alpha * (phit_W * phi)));\n",
" }\n",
"}\n",
"```\n",
"```python\n",
"with the data transformed in the model:\n",
"```\n",
"transformed data {\n",
Expand Down Expand Up @@ -3500,7 +3500,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
"version": "3.8.5"
}
},
"nbformat": 4,
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169 changes: 61 additions & 108 deletions examples/case_studies/factor_analysis.ipynb
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38 changes: 22 additions & 16 deletions examples/case_studies/hierarchical_partial_pooling.ipynb
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18 changes: 8 additions & 10 deletions examples/case_studies/log-gaussian-cox-process.ipynb
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Expand Up @@ -320,7 +320,7 @@
"outputs": [],
"source": [
"with pm.Model() as lgcp_model:\n",
" mu = pm.Normal(\"mu\", sd=3)\n",
" mu = pm.Normal(\"mu\", sigma=3)\n",
" rho = pm.Uniform(\"rho\", lower=25, upper=200)\n",
" cov_scale = pm.Exponential(\"cov_scale\", lam=1)\n",
"\n",
Expand Down Expand Up @@ -601,9 +601,7 @@
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"scrolled": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -773,7 +771,7 @@
"n_centroids = centroids.shape[0]\n",
"\n",
"with pm.Model() as mark_model:\n",
" mu = pm.Normal(\"mu\", sd=3)\n",
" mu = pm.Normal(\"mu\", sigma=3)\n",
" rho = pm.Uniform(\"rho\", lower=25, upper=200)\n",
"\n",
" cov_scale = pm.Exponential(\"scale\", lam=1)\n",
Expand Down Expand Up @@ -809,14 +807,14 @@
"outputs": [],
"source": [
"with mark_model:\n",
" alpha = pm.Normal(\"alpha\", sd=10.0)\n",
" beta = pm.Normal(\"beta\", sd=5)\n",
" alpha = pm.Normal(\"alpha\", sigma=10.0)\n",
" beta = pm.Normal(\"beta\", sigma=5)\n",
" eps_sd = pm.HalfCauchy(\"eps_sd\", beta=1.0)\n",
"\n",
" marks = pm.Normal(\n",
" \"marks\",\n",
" mu=alpha + beta * intensity[n_centroids::],\n",
" sd=eps_sd,\n",
" sigma=eps_sd,\n",
" shape=n,\n",
" observed=data[\"marks\"].values,\n",
" )"
Expand Down Expand Up @@ -1037,7 +1035,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.2"
"version": "3.8.5"
},
"toc": {
"base_numbering": 1,
Expand All @@ -1054,5 +1052,5 @@
}
},
"nbformat": 4,
"nbformat_minor": 2
"nbformat_minor": 4
}
11 changes: 3 additions & 8 deletions examples/case_studies/multilevel_modeling.ipynb
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Expand Up @@ -76,7 +76,9 @@
"from theano import tensor as tt\n",
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@MarcoGorelli MarcoGorelli Feb 5, 2021 •
edited
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Did you save the notebooks after having re-run them? The watermarks still show old "last updated" dates


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@MarcoGorelli MarcoGorelli Feb 5, 2021 •
edited
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If there's nothing to be updated in this notebook, then perhaps it could be unstaged?

git fetch upstream
git checkout upstream/main -- examples/case_studies/multilevel_modeling.ipynb
git add examples/case_studies/multilevel_modeling.ipynb
git commit -m 'unstage multilevel_modeling'
git push

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Acknowledged. Thanks for the snippet!

"\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)"
]
Expand Down Expand Up @@ -8531,13 +8533,6 @@
"%load_ext watermark\n",
"%watermark -n -u -v -iv -w"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand All @@ -8557,7 +8552,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.9"
"version": "3.8.5"
}
},
"nbformat": 4,
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2 changes: 1 addition & 1 deletion examples/case_studies/probabilistic_matrix_factorization.ipynb
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Expand Up @@ -1649,7 +1649,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.7"
"version": "3.8.5"
}
},
"nbformat": 4,
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556 changes: 274 additions & 282 deletions examples/case_studies/putting_workflow.ipynb
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6 changes: 3 additions & 3 deletions examples/case_studies/rugby_analytics.ipynb
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Expand Up @@ -1499,9 +1499,9 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "pymc-dev",
"display_name": "Python (PyMC3 Dev)",
"language": "python",
"name": "pymc-dev"
"name": "pymc3-dev"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -1513,7 +1513,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.2"
"version": "3.8.5"
}
},
"nbformat": 4,
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185 changes: 97 additions & 88 deletions examples/case_studies/stochastic_volatility.ipynb
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