Use proper package name

pyproject.toml

@@ -28,13 +28,12 @@ dependencies = ["numpy>=2.0", "pytensor>=2.32.0"]
 test = ["pytest", "pytest-cov"]
 
 [tool.flit.module]
-name = "distributions"
+name = "pytensor_distributions"
 
 [project.urls]
-source = "https://github.com/pymc-devs/distributions"
-tracker = "https://github.com/pymc-devs/distributions/issues"
-documentation = "https://distributions.readthedocs.io"
-funding = "https://opencollective.com/pymc"
+source = "https://github.com/pymc-devs/pytensor-distributions"
+tracker = "https://github.com/pymc-devs/pytensor-distributions/issues"
+documentation = "https://pytensor-distributions.readthedocs.io"
 
 
 [tool.pydocstyle]
@@ -47,7 +46,7 @@ addopts = [
     "--strict-markers",
     "--strict-config",
     "--color=yes",
-    "--cov=distributions",
+    "--cov=pytensor_distributions",
     "--cov=tests",
     "--cov-report=term-missing",
 ]
@@ -78,9 +77,9 @@ ignore = [
 
 [tool.ruff.lint.per-file-ignores]
 "docs/source/**/*.ipynb" = ["D", "E", "F", "I", "NPY", "PL", "TID", "UP", "W"]
-"distributions/__init__.py" = ["I", "F401", "E402", "F403"]
-"distributions/tests/**/*" = ["D", "PLR2004", "TID252"]
-"distributions/tests/**/*.ipynb" = ["E", "F"]
+"pytensor_distributions/__init__.py" = ["I", "F401", "E402", "F403"]
+"pytensor_distributions/tests/**/*" = ["D", "PLR2004", "TID252"]
+"pytensor_distributions/tests/**/*.ipynb" = ["E", "F"]
 
 [tool.ruff.lint.pydocstyle]
 convention = "numpy"

distributions/__init__.py → pytensor_distributions/__init__.py

@@ -1,3 +1,3 @@
 """PyTensor powered distributions."""
 
-__version__ = "0.1.0"
+__version__ = "0.1.1"

distributions/asymmetriclaplace.py → pytensor_distributions/asymmetriclaplace.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(mu, b, kappa):

distributions/bernoulli.py → pytensor_distributions/bernoulli.py

@@ -1,7 +1,7 @@
 import pytensor.tensor as pt
 from pytensor.tensor.xlogx import xlogx
 
-from distributions.helper import cdf_bounds, ppf_bounds_disc
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_disc
 
 
 def mean(p):

distributions/beta.py → pytensor_distributions/beta.py

@@ -3,7 +3,7 @@
 from pytensor.tensor.special import betaln
 from pytensor.tensor.xlogx import xlogy0
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(alpha, beta):

distributions/betabinomial.py → pytensor_distributions/betabinomial.py

@@ -1,7 +1,7 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, discrete_entropy
-from distributions.optimization import find_ppf_discrete
+from pytensor_distributions.helper import cdf_bounds, discrete_entropy
+from pytensor_distributions.optimization import find_ppf_discrete
 
 
 def mean(n, alpha, beta):

distributions/betascaled.py → pytensor_distributions/betascaled.py

@@ -3,7 +3,7 @@
 from pytensor.tensor.special import betaln
 from pytensor.tensor.xlogx import xlogy0
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(alpha, beta, lower, upper):

distributions/binomial.py → pytensor_distributions/binomial.py

@@ -1,8 +1,8 @@
 import pytensor.tensor as pt
 from pytensor.tensor.xlogx import xlogy0
 
-from distributions.helper import cdf_bounds, discrete_entropy
-from distributions.optimization import find_ppf_discrete
+from pytensor_distributions.helper import cdf_bounds, discrete_entropy
+from pytensor_distributions.optimization import find_ppf_discrete
 
 
 def mean(n, p):

distributions/categorical.py → pytensor_distributions/categorical.py

@@ -1,7 +1,7 @@
 import pytensor.tensor as pt
 from pytensor.tensor.xlogx import xlogx
 
-from distributions.helper import cdf_bounds, ppf_bounds_disc
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_disc
 
 
 def _normalize_p(p):

distributions/cauchy.py → pytensor_distributions/cauchy.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(alpha, beta):

distributions/chisquared.py → pytensor_distributions/chisquared.py

@@ -1,7 +1,7 @@
 import pytensor.tensor as pt
 from pytensor.tensor.xlogx import xlogy0
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(nu):

distributions/dirichlet.py → pytensor_distributions/dirichlet.py

@@ -1,7 +1,7 @@
 import pytensor.tensor as pt
 from pytensor.tensor.math import gammaln
 
-from distributions import beta
+from pytensor_distributions import beta
 
 
 def mean(alpha):

distributions/dirichletmultinomial.py → pytensor_distributions/dirichletmultinomial.py

@@ -2,7 +2,7 @@
 import pytensor.tensor as pt
 from pytensor.tensor.math import gammaln
 
-from distributions import betabinomial
+from pytensor_distributions import betabinomial
 
 
 def mean(n, a):

distributions/discreteuniform.py → pytensor_distributions/discreteuniform.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, discrete_entropy, ppf_bounds_disc
+from pytensor_distributions.helper import cdf_bounds, discrete_entropy, ppf_bounds_disc
 
 
 def mean(lower, upper):

distributions/discreteweibull.py → pytensor_distributions/discreteweibull.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import (
+from pytensor_distributions.helper import (
     cdf_bounds,
     discrete_entropy,
     discrete_kurtosis,

distributions/exgaussian.py → pytensor_distributions/exgaussian.py

@@ -1,9 +1,9 @@
 import pytensor.tensor as pt
 
-from distributions.helper import continuous_entropy, logdiffexp
-from distributions.normal import logcdf as normal_logcdf
-from distributions.normal import logpdf as normal_logpdf
-from distributions.optimization import find_ppf
+from pytensor_distributions.helper import continuous_entropy, logdiffexp
+from pytensor_distributions.normal import logcdf as normal_logcdf
+from pytensor_distributions.normal import logpdf as normal_logpdf
+from pytensor_distributions.optimization import find_ppf
 
 
 def mean(mu, sigma, nu):

distributions/exponential.py → pytensor_distributions/exponential.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(lam):

distributions/gamma.py → pytensor_distributions/gamma.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(alpha, beta):

distributions/geometric.py → pytensor_distributions/geometric.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, ppf_bounds_disc
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_disc
 
 
 def mean(p):

distributions/gumbel.py → pytensor_distributions/gumbel.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(mu, beta):

distributions/halfcauchy.py → pytensor_distributions/halfcauchy.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(beta):

distributions/halfnormal.py → pytensor_distributions/halfnormal.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(sigma):

distributions/halfstudentt.py → pytensor_distributions/halfstudentt.py

@@ -2,10 +2,10 @@
 from pytensor.tensor.math import betaincinv
 from pytensor.tensor.special import betaln
 
-from distributions.halfnormal import cdf as halfnormal_cdf
-from distributions.halfnormal import entropy as halfnormal_entropy
-from distributions.halfnormal import logpdf as halfnormal_logpdf
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.halfnormal import cdf as halfnormal_cdf
+from pytensor_distributions.halfnormal import entropy as halfnormal_entropy
+from pytensor_distributions.halfnormal import logpdf as halfnormal_logpdf
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(nu, sigma):

distributions/hypergeometric.py → pytensor_distributions/hypergeometric.py

@@ -1,7 +1,7 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, discrete_entropy
-from distributions.optimization import find_ppf_discrete
+from pytensor_distributions.helper import cdf_bounds, discrete_entropy
+from pytensor_distributions.optimization import find_ppf_discrete
 
 
 def _support_lower(N, k, n):

distributions/inversegamma.py → pytensor_distributions/inversegamma.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(alpha, beta):

distributions/kumaraswamy.py → pytensor_distributions/kumaraswamy.py

@@ -1,7 +1,7 @@
 import pytensor.tensor as pt
 from pytensor.tensor.xlogx import xlogy0
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont, sf_bounds
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont, sf_bounds
 
 
 def mean(a, b):

distributions/laplace.py → pytensor_distributions/laplace.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(mu, b):

distributions/logistic.py → pytensor_distributions/logistic.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(mu, s):

distributions/logitnormal.py → pytensor_distributions/logitnormal.py

@@ -1,11 +1,11 @@
 import numpy as np
 import pytensor.tensor as pt
 
-from distributions.helper import (
+from pytensor_distributions.helper import (
     cdf_bounds,
     ppf_bounds_cont,
 )
-from distributions.normal import ppf as normal_ppf
+from pytensor_distributions.normal import ppf as normal_ppf
 
 
 def _logit(x):

distributions/loglogistic.py → pytensor_distributions/loglogistic.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(alpha, beta):

distributions/lognormal.py → pytensor_distributions/lognormal.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(mu, sigma):

distributions/moyal.py → pytensor_distributions/moyal.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(mu, sigma):

distributions/mvstudentt.py → pytensor_distributions/mvstudentt.py

@@ -2,7 +2,7 @@
 import pytensor.tensor as pt
 from pytensor.tensor.math import gammaln
 
-from distributions.mvnormal import quaddist_chol
+from pytensor_distributions.mvnormal import quaddist_chol
 
 
 def mean(nu, mu, cov):

distributions/negativebinomial.py → pytensor_distributions/negativebinomial.py

@@ -1,8 +1,8 @@
 import pytensor.tensor as pt
 from pytensor.tensor.xlogx import xlogy0
 
-from distributions.helper import cdf_bounds, discrete_entropy, sf_bounds
-from distributions.optimization import find_ppf_discrete
+from pytensor_distributions.helper import cdf_bounds, discrete_entropy, sf_bounds
+from pytensor_distributions.optimization import find_ppf_discrete
 
 
 def mean(n, p):

distributions/normal.py → pytensor_distributions/normal.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(mu, sigma):

distributions/optimization.py → pytensor_distributions/optimization.py

@@ -2,7 +2,7 @@
 
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont, ppf_bounds_disc
+from pytensor_distributions.helper import ppf_bounds_cont, ppf_bounds_disc
 
 
 def find_ppf(q, lower, upper, cdf, *params):

distributions/pareto.py → pytensor_distributions/pareto.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import ppf_bounds_cont
+from pytensor_distributions.helper import ppf_bounds_cont
 
 
 def mean(alpha, m):

distributions/poisson.py → pytensor_distributions/poisson.py

@@ -1,8 +1,8 @@
 import pytensor.tensor as pt
 from pytensor.tensor.xlogx import xlogy0
 
-from distributions.helper import cdf_bounds, discrete_entropy, sf_bounds
-from distributions.optimization import find_ppf_discrete
+from pytensor_distributions.helper import cdf_bounds, discrete_entropy, sf_bounds
+from pytensor_distributions.optimization import find_ppf_discrete
 
 
 def mean(mu):

distributions/rice.py → pytensor_distributions/rice.py

@@ -1,14 +1,14 @@
 import pytensor.tensor as pt
 
-from distributions.helper import (
+from pytensor_distributions.helper import (
     cdf_bounds,
     continuous_entropy,
     continuous_kurtosis,
     continuous_mode,
     continuous_skewness,
     marcum_q1_complement,
 )
-from distributions.optimization import find_ppf
+from pytensor_distributions.optimization import find_ppf
 
 
 def _laguerre_half(q):

distributions/scaledinversechisquared.py → pytensor_distributions/scaledinversechisquared.py

@@ -1,6 +1,6 @@
 import pytensor.tensor as pt
 
-from distributions.helper import cdf_bounds, ppf_bounds_cont
+from pytensor_distributions.helper import cdf_bounds, ppf_bounds_cont
 
 
 def mean(nu, tau2):