experiment submodule

Author: drbenvincent

causalpy/__init__.py

@@ -18,27 +18,27 @@
 from causalpy.version import __version__
 
 from .data import load_data
-from .exp_inverse_propensity_weighting import InversePropensityWeighting
-from .expt_diff_in_diff import DifferenceInDifferences
-from .expt_instrumental_variable import InstrumentalVariable
-from .expt_prepostfit import InterruptedTimeSeries, SyntheticControl
-from .expt_prepostnegd import PrePostNEGD
-from .expt_regression_discontinuity import RegressionDiscontinuity
-from .expt_regression_kink import RegressionKink
+from .experiments.diff_in_diff import DifferenceInDifferences
+from .experiments.instrumental_variable import InstrumentalVariable
+from .experiments.inverse_propensity_weighting import InversePropensityWeighting
+from .experiments.prepostfit import InterruptedTimeSeries, SyntheticControl
+from .experiments.prepostnegd import PrePostNEGD
+from .experiments.regression_discontinuity import RegressionDiscontinuity
+from .experiments.regression_kink import RegressionKink
 
 az.style.use("arviz-darkgrid")
 
 __all__ = [
-    "InterruptedTimeSeries",
-    "SyntheticControl",
+    "__version__",
     "DifferenceInDifferences",
-    "PrePostNEGD",
-    "RegressionDiscontinuity",
-    "RegressionKink",
     "InstrumentalVariable",
+    "InterruptedTimeSeries",
     "InversePropensityWeighting",
+    "load_data",
+    "PrePostNEGD",
     "pymc_models",
+    "RegressionDiscontinuity",
+    "RegressionKink",
     "skl_models",
-    "load_data",
-    "__version__",
+    "SyntheticControl",
 ]

causalpy/experiments/__init__.py

@@ -0,0 +1,13 @@
+#   Copyright 2024 The PyMC Labs Developers
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use this file except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.

causalpy/expt_diff_in_diff.py renamed to causalpy/experiments/diff_in_diff.py

@@ -23,11 +23,12 @@
     DataException,
     FormulaException,
 )
-from causalpy.experiments import ExperimentalDesign
 from causalpy.pymc_models import PyMCModel
 from causalpy.skl_models import ScikitLearnModel
 from causalpy.utils import _is_variable_dummy_coded, convert_to_string
 
+from .experiments import ExperimentalDesign
+
 
 class DifferenceInDifferences(ExperimentalDesign):
     """A class to analyse data from Difference in Difference settings.

causalpy/experiments.py renamed to causalpy/experiments/experiments.py

@@ -23,7 +23,7 @@
 from sklearn.linear_model import LinearRegression as sk_lin_reg
 
 from causalpy.custom_exceptions import DataException
-from causalpy.experiments import ExperimentalDesign
+from .experiments import ExperimentalDesign
 
 
 class InstrumentalVariable(ExperimentalDesign):

causalpy/expt_instrumental_variable.py renamed to causalpy/experiments/instrumental_variable.py

@@ -24,10 +24,8 @@
 from sklearn.linear_model import LinearRegression as sk_lin_reg
 
 from causalpy.custom_exceptions import DataException
-from causalpy.experiments import ExperimentalDesign
 
-# from causalpy.pymc_models import PyMCModel
-# from causalpy.utils import round_num
+from .experiments import ExperimentalDesign
 
 
 class InversePropensityWeighting(ExperimentalDesign):
@@ -372,7 +370,8 @@ def weighted_percentile(self, data, weights, perc):
         """
         perc : percentile in [0-1]!
         """
-        assert 0 <= perc <= 1
+        if not (0 <= perc <= 1):
+            raise ValueError("Percentile must be between 0 and 1.")
         ix = np.argsort(data)
         data = data[ix]  # sort data
         weights = weights[ix]  # sort weights

causalpy/exp_inverse_propensity_weighting.py renamed to causalpy/experiments/inverse_propensity_weighting.py

@@ -22,10 +22,11 @@
 from patsy import build_design_matrices, dmatrices
 
 from causalpy.custom_exceptions import BadIndexException
-from causalpy.experiments import ExperimentalDesign
 from causalpy.pymc_models import PyMCModel
 from causalpy.skl_models import ScikitLearnModel
 
+from .experiments import ExperimentalDesign
+
 
 class PrePostFit(ExperimentalDesign):
     """

causalpy/expt_prepostfit.py renamed to causalpy/experiments/prepostfit.py

@@ -22,11 +22,12 @@
 from causalpy.custom_exceptions import (
     DataException,
 )
-from causalpy.experiments import ExperimentalDesign
 from causalpy.pymc_models import PyMCModel
 from causalpy.skl_models import ScikitLearnModel
 from causalpy.utils import _is_variable_dummy_coded, round_num
 
+from .experiments import ExperimentalDesign
+
 
 class PrePostNEGD(ExperimentalDesign):
     """

causalpy/expt_prepostnegd.py renamed to causalpy/experiments/prepostnegd.py

@@ -21,7 +21,7 @@
 import pandas as pd
 from patsy import build_design_matrices, dmatrices
 
-from causalpy.experiments import ExperimentalDesign
+from .experiments import ExperimentalDesign
 from causalpy.pymc_models import PyMCModel
 from causalpy.skl_models import ScikitLearnModel
 from causalpy.utils import convert_to_string

causalpy/expt_regression_discontinuity.py renamed to causalpy/experiments/regression_discontinuity.py

@@ -22,7 +22,7 @@
 import pandas as pd
 from patsy import build_design_matrices, dmatrices
 
-from causalpy.experiments import ExperimentalDesign
+from .experiments import ExperimentalDesign
 from causalpy.utils import round_num
 from causalpy.custom_exceptions import (
     DataException,