Fix imports.

Author: twiecki

homepy/blocks/gp.py

@@ -30,7 +30,7 @@
 import xarray as xr
 
 from pytensor import tensor as pt
-from pytensor.tensor.var import TensorVariable
+from pytensor.tensor.variable import TensorVariable
 from matplotlib import pyplot as plt
 from pandas import DataFrame, Index
 from pymc.model import Model

homepy/blocks/means.py

@@ -26,7 +26,6 @@
     BetaBinomialRV,
     BetaRV,
     BinomialRV,
-    ChiSquareRV,
     DirichletRV,
     ExponentialRV,
     GammaRV,
@@ -44,11 +43,12 @@
     NormalRV,
     ParetoRV,
     PoissonRV,
+    StudentTRV,
     TriangularRV,
     UniformRV,
     VonMisesRV,
 )
-from pytensor.tensor.var import TensorVariable
+from pytensor.tensor.variable import TensorVariable
 from pymc.distributions.continuous import (
     AsymmetricLaplaceRV,
     BetaClippedRV,
@@ -59,12 +59,12 @@
     PolyaGammaRV,
     RiceRV,
     SkewNormalRV,
-    StudentTRV,
     WaldRV,
     WeibullBetaRV,
 )
-from pymc.distributions.discrete import DiracDeltaRV, DiscreteUniformRV
-from pymc.distributions.mixture import MarginalMixtureRV
+from pymc.distributions.distribution import DiracDeltaRV
+from pymc.distributions.discrete import DiscreteUniformRV
+from pymc.distributions.mixture import MixtureRV
 from pymc.distributions.multivariate import (
     CARRV,
     DirichletMultinomialRV,
@@ -127,9 +127,8 @@ def binomial_mean(op, rv, rng, size, dtype, n, p):
     return maybe_resize(n * p, size)
 
 
-@_mean.register(ChiSquareRV)
-def chisquare_mean(op, rv, rng, size, dtype, nu):
-    return maybe_resize(nu, size)
+# Note: ChiSquared is now implemented as GammaRV in PyMC v5
+# Mean is correctly calculated through gamma_mean: Gamma(ν/2, 2) has mean (ν/2)*2 = ν
 
 
 @_mean.register(DirichletRV)
@@ -337,8 +336,8 @@ def dirac_delta_mean(op, rv, rng, size, dtype, c):
     return maybe_resize(c, size)
 
 
-@_mean.register(MarginalMixtureRV)
-def marginal_mixture_mean(op, rv, rng, weights, *components):
+@_mean.register(MixtureRV)
+def mixture_mean(op, rv, rng, weights, *components):
     ndim_supp = components[0].owner.op.ndim_supp
     weights = pt.shape_padright(weights, ndim_supp)
     mix_axis = -ndim_supp - 1

homepy/tests/blocks/test_distributions.py

@@ -30,7 +30,7 @@
     ballBackwardOp,
     ballTransform,
 )
-from pymc.tests.distributions.util import (
+from pymc.testing import (
     BaseTestDistributionRandom,
     Domain,
     Rplus,