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Removing unnecessary comp_shape from class NormalMixture #7098

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Merged
merged 1 commit into from
Mar 25, 2024
Merged

Removing unnecessary comp_shape from class NormalMixture #7098

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12 changes: 4 additions & 8 deletions pymc/distributions/mixture.py
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Original file line number Diff line number Diff line change
Expand Up @@ -524,10 +524,6 @@ class NormalMixture:
the component standard deviations
tau : tensor_like of float
the component precisions
comp_shape : shape of the Normal component
notice that it should be different than the shape
of the mixture distribution, with the last axis representing
the number of components.

Notes
-----
Expand All @@ -554,16 +550,16 @@ class NormalMixture:
y = pm.NormalMixture("y", w=weights, mu=μ, sigma=σ, observed=data)
"""

def __new__(cls, name, w, mu, sigma=None, tau=None, comp_shape=(), **kwargs):
def __new__(cls, name, w, mu, sigma=None, tau=None, **kwargs):
_, sigma = get_tau_sigma(tau=tau, sigma=sigma)

return Mixture(name, w, Normal.dist(mu, sigma=sigma, size=comp_shape), **kwargs)
return Mixture(name, w, Normal.dist(mu, sigma=sigma), **kwargs)

@classmethod
def dist(cls, w, mu, sigma=None, tau=None, comp_shape=(), **kwargs):
def dist(cls, w, mu, sigma=None, tau=None, **kwargs):
_, sigma = get_tau_sigma(tau=tau, sigma=sigma)

return Mixture.dist(w, Normal.dist(mu, sigma=sigma, size=comp_shape), **kwargs)
return Mixture.dist(w, Normal.dist(mu, sigma=sigma), **kwargs)


def _zero_inflated_mixture(*, name, nonzero_p, nonzero_dist, **kwargs):
Expand Down
9 changes: 2 additions & 7 deletions tests/distributions/test_mixture.py
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Original file line number Diff line number Diff line change
Expand Up @@ -820,10 +820,8 @@ def test_normal_mixture_nd(self, seeded_test, nd, ncomp):
mus = Normal("mus", shape=comp_shape)
taus = Gamma("taus", alpha=1, beta=1, shape=comp_shape)
ws = Dirichlet("ws", np.ones(ncomp), shape=(ncomp,))
mixture0 = NormalMixture("m", w=ws, mu=mus, tau=taus, shape=nd, comp_shape=comp_shape)
obs0 = NormalMixture(
"obs", w=ws, mu=mus, tau=taus, comp_shape=comp_shape, observed=observed
)
mixture0 = NormalMixture("m", w=ws, mu=mus, tau=taus, shape=nd)
obs0 = NormalMixture("obs", w=ws, mu=mus, tau=taus, observed=observed)

with Model() as model1:
mus = Normal("mus", shape=comp_shape)
Expand Down Expand Up @@ -867,7 +865,6 @@ def ref_rand(size, w, mu, sigma):
"mu": Domain([[0.05, 2.5], [-5.0, 1.0]], edges=(None, None)),
"sigma": Domain([[1, 1], [1.5, 2.0]], edges=(None, None)),
},
extra_args={"comp_shape": 2},
size=1000,
ref_rand=ref_rand,
)
Expand All @@ -878,7 +875,6 @@ def ref_rand(size, w, mu, sigma):
"mu": Domain([[-5.0, 1.0, 2.5]], edges=(None, None)),
"sigma": Domain([[1.5, 2.0, 3.0]], edges=(None, None)),
},
extra_args={"comp_shape": 3},
size=1000,
ref_rand=ref_rand,
)
Expand All @@ -902,7 +898,6 @@ def test_scalar_components(self):
w=np.ones(npop) / npop,
mu=mus,
sigma=1e-5,
comp_shape=(nd, npop),
shape=nd,
)
z = Categorical("z", p=np.ones(npop) / npop, shape=nd)
Expand Down