Replacing PyMC3 plots w/ Arviz plots & sigma Param change [Part 5]

examples/mixture_models/gaussian_mixture_model.ipynb

@@ -18,7 +18,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Fri 12 Jun 2020 07:12:54 PM UTC\r\n",
+      "Fri 12 Jun 2020 07:12:54 PM UTC\n",
       "Running on PyMC3 v3.9.0\n"
      ]
     }
@@ -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\"]);"
    ]
   },
   {
@@ -434,7 +434,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.7"
+   "version": "3.8.5"
   },
   "latex_envs": {
    "bibliofile": "biblio.bib",

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"
    ]
   },
@@ -144,7 +144,7 @@
     "        sigma = pm.HalfCauchy(\"sigma\", 1)\n",
     "        vmax = pm.Lognormal(\"vmax\", 0, 1)\n",
     "        K_S = pm.Lognormal(\"K_S\", 0, 1)\n",
-    "        s0 = pm.Normal(\"red_0\", mu=10, sd=2)\n",
+    "        s0 = pm.Normal(\"red_0\", mu=10, sigma=2)\n",
     "\n",
     "        y_hat = pm.ode.DifferentialEquation(\n",
     "            func=Chem.reaction, times=times, n_states=len(y0_true), n_theta=len(theta_true)\n",
@@ -153,8 +153,8 @@
     "        red_hat = y_hat.T[0][red]\n",
     "        blue_hat = y_hat.T[1][blue]\n",
     "\n",
-    "        Y_red = pm.Normal(\"Y_red\", mu=red_hat, sd=sigma, observed=y_obs_1)\n",
-    "        Y_blue = pm.Normal(\"Y_blue\", mu=blue_hat, sd=sigma, observed=y_obs_2)\n",
+    "        Y_red = pm.Normal(\"Y_red\", mu=red_hat, sigma=sigma, observed=y_obs_1)\n",
+    "        Y_blue = pm.Normal(\"Y_blue\", mu=blue_hat, sigma=sigma, observed=y_obs_2)\n",
     "\n",
     "    return pmodel\n",
     "\n",
@@ -353,9 +353,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python (PyMC3 Dev)",
    "language": "python",
-   "name": "python3"
+   "name": "pymc3-dev"
   },
   "language_info": {
    "codemirror_mode": {
@@ -367,7 +367,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,