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Refactor missing discrete dists #4684

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merged 12 commits into from
May 13, 2021
Merged

Refactor missing discrete dists #4684

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fa0e930
Fix Uniform logp regression from #4541
ricardoV94 Apr 13, 2021
03e1df5
Refactor DiscreteUniform
ricardoV94 May 3, 2021
ea7afba
Refactor Constant
ricardoV94 May 3, 2021
2a1071d
Refactor OrderedLogistic
ricardoV94 May 3, 2021
9c40f8f
Refactor OrderedProbit
ricardoV94 May 6, 2021
5c723b3
Add missing discrete distributions to API rst
ricardoV94 May 6, 2021
ce252fa
Refactor ZeroInflatedPoisson
ricardoV94 May 6, 2021
7a7405f
Refactor ZeroInflatedBinomial
ricardoV94 May 6, 2021
43f75dd
Refactor ZeroInflatedNegativeBinomial
ricardoV94 May 6, 2021
d13e871
Update several test xfails
ricardoV94 May 6, 2021
a616e0a
Use _logp and _logcdf dispatcher in ZeroInflated* methods
ricardoV94 May 13, 2021
bc89287
Fix `check_logcdf` test regression
ricardoV94 May 13, 2021
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2 changes: 2 additions & 0 deletions docs/source/api/distributions/discrete.rst
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Expand Up @@ -15,10 +15,12 @@ Discrete
ZeroInflatedNegativeBinomial
DiscreteUniform
Geometric
HyperGeometric
Categorical
DiscreteWeibull
Constant
OrderedLogistic
OrderedProbit

.. automodule:: pymc3.distributions.discrete
:members:
2 changes: 0 additions & 2 deletions pymc3/distributions/__init__.py
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Expand Up @@ -63,7 +63,6 @@
Binomial,
Categorical,
Constant,
ConstantDist,
DiscreteUniform,
DiscreteWeibull,
Geometric,
Expand Down Expand Up @@ -138,7 +137,6 @@
"Bernoulli",
"Poisson",
"NegativeBinomial",
"ConstantDist",
"Constant",
"ZeroInflatedPoisson",
"ZeroInflatedNegativeBinomial",
Expand Down
8 changes: 5 additions & 3 deletions pymc3/distributions/continuous.py
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Expand Up @@ -253,8 +253,6 @@ class Uniform(BoundedContinuous):
def dist(cls, lower=0, upper=1, **kwargs):
lower = at.as_tensor_variable(floatX(lower))
upper = at.as_tensor_variable(floatX(upper))
# mean = (upper + lower) / 2.0
# median = self.mean
return super().dist([lower, upper], **kwargs)

def logp(value, lower, upper):
Expand All @@ -270,7 +268,11 @@ def logp(value, lower, upper):
-------
TensorVariable
"""
return bound(-at.log(upper - lower), value >= lower, value <= upper)
return bound(
at.fill(value, -at.log(upper - lower)),
value >= lower,
value <= upper,
)

def logcdf(value, lower, upper):
"""
Expand Down
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