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Fix FutureError warning, which requires pymc>=5.14.0 #325

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Merged
drbenvincent merged 1 commit into from
May 5, 2024
Merged

Fix FutureError warning, which requires pymc>=5.14.0 #325

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12 changes: 6 additions & 6 deletions causalpy/pymc_models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,8 +41,8 @@ class ModelBuilder(pm.Model):
>>> class MyToyModel(ModelBuilder):
... def build_model(self, X, y, coords):
... with self:
... X_ = pm.MutableData(name="X", value=X)
... y_ = pm.MutableData(name="y", value=y)
... X_ = pm.Data(name="X", value=X)
... y_ = pm.Data(name="y", value=y)
... beta = pm.Normal("beta", mu=0, sigma=1, shape=X_.shape[1])
... sigma = pm.HalfNormal("sigma", sigma=1)
... mu = pm.Deterministic("mu", pm.math.dot(X_, beta))
Expand Down Expand Up @@ -190,8 +190,8 @@ def build_model(self, X, y, coords):
with self:
self.add_coords(coords)
n_predictors = X.shape[1]
X = pm.MutableData("X", X, dims=["obs_ind", "coeffs"])
y = pm.MutableData("y", y[:, 0], dims="obs_ind")
X = pm.Data("X", X, dims=["obs_ind", "coeffs"])
y = pm.Data("y", y[:, 0], dims="obs_ind")
# TODO: There we should allow user-specified priors here
beta = pm.Dirichlet("beta", a=np.ones(n_predictors), dims="coeffs")
# beta = pm.Dirichlet(
Expand Down Expand Up @@ -245,8 +245,8 @@ def build_model(self, X, y, coords):
"""
with self:
self.add_coords(coords)
X = pm.MutableData("X", X, dims=["obs_ind", "coeffs"])
y = pm.MutableData("y", y[:, 0], dims="obs_ind")
X = pm.Data("X", X, dims=["obs_ind", "coeffs"])
y = pm.Data("y", y[:, 0], dims="obs_ind")
beta = pm.Normal("beta", 0, 50, dims="coeffs")
sigma = pm.HalfNormal("sigma", 1)
mu = pm.Deterministic("mu", pm.math.dot(X, beta), dims="obs_ind")
Expand Down
4 changes: 2 additions & 2 deletions causalpy/tests/test_pymc_models.py
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Expand Up @@ -22,8 +22,8 @@ def build_model(self, X, y, coords):
This is a basic 1-variable linear regression model for use in tests.
"""
with self:
X_ = pm.MutableData(name="X", value=X)
y_ = pm.MutableData(name="y", value=y)
X_ = pm.Data(name="X", value=X)
y_ = pm.Data(name="y", value=y)
beta = pm.Normal("beta", mu=0, sigma=1, shape=X_.shape[1])
sigma = pm.HalfNormal("sigma", sigma=1)
mu = pm.Deterministic("mu", pm.math.dot(X_, beta))
Expand Down
2 changes: 1 addition & 1 deletion pyproject.toml
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Expand Up @@ -34,7 +34,7 @@ dependencies = [
"numpy<1.26.0",
"pandas",
"patsy",
"pymc>=5.0.0",
"pymc>=5.14.0",
"scikit-learn>=1",
"scipy",
"seaborn>=0.11.2",
Expand Down