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pymc-devs · Aug 26, 2024 · 27accc9 · 27accc9
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diff --git a/notebooks/Making a Custom Statespace Model.ipynb b/notebooks/Making a Custom Statespace Model.ipynb
@@ -19,13 +19,13 @@
     "\n",
     "numpyro.set_host_device_count(4)\n",
     "\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
     "import arviz as az\n",
-    "\n",
-    "from pymc_experimental.statespace.core.statespace import PyMCStateSpace\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pymc as pm\n",
     "import pytensor.tensor as pt\n",
-    "import pymc as pm"
+    "\n",
+    "from pymc_experimental.statespace.core.statespace import PyMCStateSpace"
    ]
   },
   {
@@ -1092,7 +1092,7 @@
    ],
    "source": [
     "az.plot_posterior(\n",
-    "    idata, var_names=[\"ar_params\", \"sigma_x\"], ref_val=true_ar.tolist() + [true_sigma_x]\n",
+    "    idata, var_names=[\"ar_params\", \"sigma_x\"], ref_val=[*true_ar.tolist(), true_sigma_x]\n",
     ");"
    ]
   },
@@ -1169,13 +1169,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from pymc_experimental.statespace.models.utilities import make_default_coords\n",
     "from pymc_experimental.statespace.utils.constants import (\n",
-    "    ALL_STATE_DIM,\n",
     "    ALL_STATE_AUX_DIM,\n",
-    "    OBS_STATE_DIM,\n",
+    "    ALL_STATE_DIM,\n",
     "    SHOCK_DIM,\n",
     ")\n",
-    "from pymc_experimental.statespace.models.utilities import make_default_coords\n",
     "\n",
     "\n",
     "class AutoRegressiveThree(PyMCStateSpace):\n",

diff --git a/notebooks/SARMA Example.ipynb b/notebooks/SARMA Example.ipynb
@@ -31,20 +31,19 @@
     "\n",
     "numpyro.set_host_device_count(8)\n",
     "\n",
-    "import pymc as pm\n",
-    "from pytensor import tensor as pt\n",
-    "\n",
     "import arviz as az\n",
-    "import statsmodels.api as sm\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import pandas as pd\n",
-    "from scipy import stats\n",
+    "import pymc as pm\n",
+    "import statsmodels.api as sm\n",
     "\n",
-    "import pymc_experimental.statespace as pmss\n",
+    "from pymc.model.transform.optimization import freeze_dims_and_data\n",
+    "from pytensor import tensor as pt\n",
     "from pytensor.link.jax.dispatch import jax_funcify\n",
     "from pytensor.tensor.nlinalg import KroneckerProduct\n",
-    "from pymc.model.transform.optimization import freeze_dims_and_data\n",
+    "\n",
+    "import pymc_experimental.statespace as pmss\n",
     "\n",
     "\n",
     "@jax_funcify.register(KroneckerProduct)\n",
@@ -2582,8 +2581,8 @@
    "source": [
     "fig, ax = plt.subplots()\n",
     "post = az.extract(post_pred).map(np.exp)\n",
-    "hdi = az.hdi(post_pred.map(np.exp))[f\"predicted_posterior_observed\"]\n",
-    "post[f\"predicted_posterior_observed\"].isel(observed_state=0).mean(dim=\"sample\").plot.line(\n",
+    "hdi = az.hdi(post_pred.map(np.exp))[\"predicted_posterior_observed\"]\n",
+    "post[\"predicted_posterior_observed\"].isel(observed_state=0).mean(dim=\"sample\").plot.line(\n",
     "    x=\"time\", ax=ax, add_legend=False, label=\"Posterior Mean, Predicted\"\n",
     ")\n",
     "ax.fill_between(\n",

diff --git a/notebooks/Structural Timeseries Modeling.ipynb b/notebooks/Structural Timeseries Modeling.ipynb
@@ -22,17 +22,18 @@
     "import sys\n",
     "\n",
     "sys.path.append(\"..\")\n",
-    "from pymc_experimental.statespace import structural as st\n",
-    "from pymc_experimental.statespace.utils.constants import SHORT_NAME_TO_LONG, MATRIX_NAMES\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pymc as pm\n",
     "import arviz as az\n",
-    "import pytensor\n",
-    "import pytensor.tensor as pt\n",
+    "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import pandas as pd\n",
+    "import pymc as pm\n",
+    "import pytensor.tensor as pt\n",
+    "\n",
     "from patsy import dmatrix\n",
     "\n",
+    "from pymc_experimental.statespace import structural as st\n",
+    "from pymc_experimental.statespace.utils.constants import SHORT_NAME_TO_LONG\n",
+    "\n",
     "plt.rcParams.update(\n",
     "    {\n",
     "        \"figure.figsize\": (14, 4),\n",
@@ -61,15 +62,14 @@
    },
    "outputs": [],
    "source": [
-    "from pymc_experimental.statespace.filters.kalman_filter import StandardFilter\n",
-    "from pymc_experimental.statespace.filters.kalman_smoother import KalmanSmoother\n",
+    "from pymc.pytensorf import compile_pymc, inputvars\n",
+    "\n",
     "from pymc_experimental.statespace.filters.distributions import LinearGaussianStateSpace\n",
-    "from pymc.pytensorf import inputvars, compile_pymc\n",
     "\n",
     "\n",
     "def make_numpy_function(mod):\n",
     "    mod = mod.build(verbose=False)\n",
-    "    data = pt.matrix(\"data\", shape=(None, 1))\n",
+    "    pt.matrix(\"data\", shape=(None, 1))\n",
     "    steps = pt.iscalar(\"steps\")\n",
     "    x0, _, c, d, T, Z, R, H, Q = mod._unpack_statespace_with_placeholders()\n",
     "    sequence_names = [x.name for x in [c, d] if x.ndim == 2]\n",

diff --git a/notebooks/VARMAX Example.ipynb b/notebooks/VARMAX Example.ipynb
@@ -14,21 +14,21 @@
     "\n",
     "numpyro.set_host_device_count(8)\n",
     "\n",
+    "import sys\n",
+    "\n",
+    "import arviz as az\n",
+    "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
-    "import statsmodels.api as sm\n",
     "import pandas as pd\n",
-    "\n",
     "import pymc as pm\n",
     "import pytensor.tensor as pt\n",
-    "import arviz as az\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "import sys\n",
+    "import statsmodels.api as sm\n",
     "\n",
     "sys.path.append(\"..\")\n",
-    "import pymc_experimental.statespace as pmss\n",
     "import re\n",
     "\n",
+    "import pymc_experimental.statespace as pmss\n",
+    "\n",
     "config = {\n",
     "    \"figure.figsize\": [12.0, 4.0],\n",
     "    \"figure.dpi\": 72.0 * 2,\n",
@@ -679,7 +679,7 @@
     "    new_labels = []\n",
     "    for label in axis.yaxis.get_majorticklabels():\n",
     "        old_text = \"[\" + label.get_text().split(\"[\")[-1]\n",
-    "        labels = eval(re.sub(\"([\\d\\w]+)\", '\"\\g<1>\"', old_text))\n",
+    "        labels = eval(re.sub(r\"([\\d\\w]+)\", r'\"\\g<1>\"', old_text))\n",
     "        lag, other_var = labels\n",
     "        new_text = f\"L{lag}.{other_var}\"\n",
     "        new_labels.append(new_text)\n",