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Add prior predictive example notebook #787

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merged 6 commits into from
Jun 28, 2024
Merged

Add prior predictive example notebook #787

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4b4a242
add prior predictive
juanitorduz Jun 27, 2024
b765b38
fix bug
juanitorduz Jun 27, 2024
280c450
rm kw
juanitorduz Jun 27, 2024
099120b
run nb
juanitorduz Jun 27, 2024
f8a5830
rm samples plot arg
juanitorduz Jun 27, 2024
16d3656
Merge branch 'main' into prior_predictive_mmm_example_nb
juanitorduz Jun 28, 2024
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8,046 changes: 4,362 additions & 3,684 deletions docs/source/notebooks/mmm/mmm_example.ipynb
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4 changes: 1 addition & 3 deletions pymc_marketing/mmm/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -293,9 +293,7 @@ def posterior_predictive(self) -> Dataset:
)
return self.idata["posterior_predictive"]

def plot_prior_predictive(
self, samples: int = 1_000, **plt_kwargs: Any
) -> plt.Figure:
def plot_prior_predictive(self, **plt_kwargs: Any) -> plt.Figure:
prior_predictive_data: az.InferenceData = self.prior_predictive

likelihood_hdi_94: DataArray = az.hdi(ary=prior_predictive_data, hdi_prob=0.94)[
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1 change: 0 additions & 1 deletion pymc_marketing/model_builder.py
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Expand Up @@ -578,7 +578,6 @@ def sample_prior_predictive(
if not hasattr(self, "model"):
self.build_model(X_pred, y_pred)

self._data_setter(X_pred, y_pred)
with self.model: # sample with new input data
prior_pred: az.InferenceData = pm.sample_prior_predictive(samples, **kwargs)
self.set_idata_attrs(prior_pred)
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7 changes: 2 additions & 5 deletions tests/mmm/test_plotting.py
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Expand Up @@ -17,10 +17,7 @@
import pytest
from matplotlib import pyplot as plt

from pymc_marketing.mmm.delayed_saturated_mmm import (
MMM,
BaseMMM,
)
from pymc_marketing.mmm.delayed_saturated_mmm import MMM, BaseMMM
from pymc_marketing.mmm.preprocessing import MaxAbsScaleTarget

seed: int = sum(map(ord, "pymc_marketing"))
Expand Down Expand Up @@ -124,7 +121,7 @@ class ToyMMM(BaseMMM, MaxAbsScaleTarget):
@pytest.mark.parametrize(
argnames="func_plot_name, kwargs_plot",
argvalues=[
("plot_prior_predictive", {"samples": 3}),
("plot_prior_predictive", {}),
("plot_posterior_predictive", {}),
("plot_posterior_predictive", {"original_scale": True}),
("plot_posterior_predictive", {"ax": plt.subplots()[1]}),
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