Import renaming

Author: fonnesbeck

.github/workflows/pypi.yml

@@ -28,18 +28,18 @@ jobs:
             cd test-sdist
             python -m venv venv-sdist
             venv-sdist/bin/python -m pip install numpy
-            venv-sdist/bin/python -m pip install ../dist/pymc_experimental*.tar.gz
+            venv-sdist/bin/python -m pip install ../dist/pymc_extras*.tar.gz
             echo "Checking import and version number (on release)"
-            venv-sdist/bin/python -c "import pymc_experimental as pmx; assert pmx.__version__ == '${{ github.ref_name }}'[1:] if '${{ github.ref_type }}' == 'tag' else True; print(pmx.__version__)"
+            venv-sdist/bin/python -c "import pymc as pmx; assert pmx.__version__ == '${{ github.ref_name }}'[1:] if '${{ github.ref_type }}' == 'tag' else True; print(pmx.__version__)"
             cd ..
       - name: Check the bdist installs and imports
         run: |
               mkdir -p test-bdist
               cd test-bdist
               python -m venv venv-bdist
-              venv-bdist/bin/python -m pip install ../dist/pymc_experimental*.whl
+              venv-bdist/bin/python -m pip install ../dist/pymc*.whl
               echo "Checking import and version number (on release)"
-              venv-bdist/bin/python -c "import pymc_experimental as pmx; assert pmx.__version__ == '${{ github.ref_name }}'[1:] if '${{ github.ref_type }}' == 'tag' else pmx.__version__; print(pmx.__version__)"
+              venv-bdist/bin/python -c "import pymc as pmx; assert pmx.__version__ == '${{ github.ref_name }}'[1:] if '${{ github.ref_type }}' == 'tag' else pmx.__version__; print(pmx.__version__)"
               cd ..
       - uses: actions/upload-artifact@v3
         with:

docs/index.rst

@@ -1,4 +1,4 @@
-PyMC experimental
+PyMC Extras
 ===================================================
 |Tests|
 |Coverage|
@@ -35,7 +35,7 @@ For the development version, you can install directly from GitHub:
 
 Contributing
 ============
-We welcome contributions from interested individuals or groups! For information about contributing to PyMC experimental check out our instructions, policies, and guidelines `here <https://github.com/pymc-devs/pymc-extras/blob/main/CONTRIBUTING.md>`_.
+We welcome contributions from interested individuals or groups! For information about contributing to PyMC Extras check out our instructions, policies, and guidelines `here <https://github.com/pymc-devs/pymc-extras/blob/main/CONTRIBUTING.md>`_.
 
 Contributors
 ============

pymc_extras/distributions/continuous.py

@@ -261,7 +261,7 @@ class Chi:
     --------
     .. code-block:: python
         import pymc as pm
-        from pymc_experimental.distributions import Chi
+        from pymc_extras.distributions import Chi
 
         with pm.Model():
             x = Chi('x', nu=1)

pymc_extras/distributions/multivariate/r2d2m2cp.py

@@ -302,7 +302,7 @@ def R2D2M2CP(
 
     .. code-block:: python
 
-        import pymc_experimental as pmx
+        import pymc_extras as pmx
         import pymc as pm
         import numpy as np
         X = np.random.randn(10, 3)

pymc_extras/distributions/timeseries.py

@@ -109,7 +109,7 @@ class DiscreteMarkovChain(Distribution):
     .. code-block:: python
 
         import pymc as pm
-        import pymc_experimental as pmx
+        import pymc_extras as pmx
 
         with pm.Model() as markov_chain:
             P = pm.Dirichlet("P", a=[1, 1, 1], size=(3,))

pymc_extras/inference/laplace.py

@@ -40,7 +40,7 @@
 from pymc.util import get_default_varnames
 from scipy import stats
 
-from pymc_experimental.inference.find_map import (
+from pymc_extras.inference.find_map import (
     GradientBackend,
     _unconstrained_vector_to_constrained_rvs,
     find_MAP,
@@ -505,7 +505,7 @@ def fit_laplace(
 
     Examples
     --------
-    >>> from pymc_experimental.inference.laplace import fit_laplace
+    >>> from pymc_extras.inference.laplace import fit_laplace
     >>> import numpy as np
     >>> import pymc as pm
     >>> import arviz as az

pymc_extras/linearmodel.py

@@ -2,7 +2,7 @@
 import pandas as pd
 import pymc as pm
 
-from pymc_experimental.model_builder import ModelBuilder
+from pymc_extras.model_builder import ModelBuilder
 
 
 class LinearModel(ModelBuilder):

pymc_extras/model/marginal/marginal_model.py

@@ -73,7 +73,7 @@ class MarginalModel(Model):
     .. code-block:: python
 
         import pymc as pm
-        from pymc_experimental import MarginalModel
+        from pymc_extras import MarginalModel
 
         with MarginalModel() as m:
             p = pm.Beta("p", 1, 1)
@@ -364,7 +364,7 @@ def recover_marginals(
         .. code-block:: python
 
             import pymc as pm
-            from pymc_experimental import MarginalModel
+            from pymc_extras import MarginalModel
 
             with MarginalModel() as m:
                 p = pm.Beta("p", 1, 1)

pymc_extras/model/transforms/autoreparam.py

@@ -24,6 +24,7 @@
 from pymc.pytensorf import toposort_replace
 from pytensor.graph.basic import Apply, Variable
 from pytensor.tensor.random.op import RandomVariable
+from pymc_extras.model.transforms.autoreparam import vip_reparametrize
 
 _log = logging.getLogger("pmx")
 
@@ -342,7 +343,7 @@ def vip_reparametrize(
 
     .. code-block:: python
 
-        from pymc_experimental.model.transforms.autoreparam import vip_reparametrize
+        from pymc_extras.model.transforms.autoreparam import vip_reparametrize
         Reparam_eight, vip = vip_reparametrize(Centered_eight, ["theta"])
 
         with Reparam_eight:

pymc_extras/printing.py

@@ -94,7 +94,7 @@ def model_table(
         import numpy as np
         import pymc as pm
 
-        from pymc_experimental.printing import model_table
+        from pymc_extras.printing import model_table
 
         coords = {"subject": range(20), "param": ["a", "b"]}
         with pm.Model(coords=coords) as m: