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Implement sampling for v2 prior distributions #461

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Merged
dweindl merged 1 commit into from
Dec 4, 2025
Merged

Implement sampling for v2 prior distributions #461

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27 changes: 22 additions & 5 deletions petab/v1/distributions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -508,6 +508,9 @@ def _cdf_untransformed_untruncated(self, x) -> np.ndarray | float:
def _ppf_untransformed_untruncated(self, q) -> np.ndarray | float:
return cauchy.ppf(q, loc=self._loc, scale=self._scale)

def _sample(self, shape=None) -> np.ndarray | float:
return cauchy.rvs(loc=self._loc, scale=self._scale, size=shape)

@property
def loc(self) -> float:
"""The location parameter of the underlying distribution."""
Expand Down Expand Up @@ -541,14 +544,16 @@ class ChiSquare(Distribution):

def __init__(
self,
dof: int,
dof: int | float,
trunc: tuple[float, float] | None = None,
log: bool | float = False,
):
if not dof.is_integer() or dof < 1:
raise ValueError(
f"`dof' must be a positive integer, but was `{dof}'."
)
if isinstance(dof, float):
if not dof.is_integer() or dof < 1:
raise ValueError(
f"`dof' must be a positive integer, but was `{dof}'."
)
dof = int(dof)

self._dof = dof
super().__init__(log=log, trunc=trunc)
Expand All @@ -565,6 +570,9 @@ def _cdf_untransformed_untruncated(self, x) -> np.ndarray | float:
def _ppf_untransformed_untruncated(self, q) -> np.ndarray | float:
return chi2.ppf(q, df=self._dof)

def _sample(self, shape=None) -> np.ndarray | float:
return chi2.rvs(df=self._dof, size=shape)

@property
def dof(self) -> int:
"""The degrees of freedom parameter."""
Expand Down Expand Up @@ -602,6 +610,9 @@ def _cdf_untransformed_untruncated(self, x) -> np.ndarray | float:
def _ppf_untransformed_untruncated(self, q) -> np.ndarray | float:
return expon.ppf(q, scale=self._scale)

def _sample(self, shape=None) -> np.ndarray | float:
return expon.rvs(scale=self._scale, size=shape)

@property
def scale(self) -> float:
"""The scale parameter of the underlying distribution."""
Expand Down Expand Up @@ -650,6 +661,9 @@ def _cdf_untransformed_untruncated(self, x) -> np.ndarray | float:
def _ppf_untransformed_untruncated(self, q) -> np.ndarray | float:
return gamma.ppf(q, a=self._shape, scale=self._scale)

def _sample(self, shape=None) -> np.ndarray | float:
return gamma.rvs(a=self._shape, scale=self._scale, size=shape)

@property
def shape(self) -> float:
"""The shape parameter of the underlying distribution."""
Expand Down Expand Up @@ -700,6 +714,9 @@ def _cdf_untransformed_untruncated(self, x) -> np.ndarray | float:
def _ppf_untransformed_untruncated(self, q) -> np.ndarray | float:
return rayleigh.ppf(q, scale=self._scale)

def _sample(self, shape=None) -> np.ndarray | float:
return rayleigh.rvs(scale=self._scale, size=shape)

@property
def scale(self) -> float:
"""The scale parameter of the underlying distribution."""
Expand Down
5 changes: 5 additions & 0 deletions tests/v1/test_distributions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,11 @@
Normal(2, 1, log=10),
Laplace(1, 2, trunc=(1, 2)),
Laplace(1, 0.5, log=True, trunc=(0.5, 8)),
Cauchy(2, 1),
ChiSquare(4),
Exponential(1),
Gamma(3, 5),
Rayleigh(3),
],
)
def test_sample_matches_pdf(distribution):
Expand Down