Added uniform product distribution (9dfa99bb) · Commits · Coriander Violet Pines / pysamplespace

CHANGELOG.md

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		@@ -14,7 +14,9 @@ v1.0.2
		* Fixed documentation typo
		* Improved PyPI info

		XXXXXX
		v1.0.3
		------
		* Markdown cleanup
		* Minor code cleanup
		* Updated dependency versions
		* Added uniform product distribution

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		@@ -91,6 +91,8 @@ Continuous distributions

		.. automethod:: RepeatableRandomSequence.triangular

		.. automethod:: RepeatableRandomSequence.uniformproduct

		.. automethod:: RepeatableRandomSequence.gauss

		.. automethod:: RepeatableRandomSequence.gausspair

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		@@ -15,6 +15,7 @@ __all__ = [
		'ZipfMandelbrot',
		'Gamma',
		'Triangular',
		'UniformProduct',
		'LogNormal',
		'Exponential',
		'VonMises',
		@@ -484,6 +485,59 @@ class Triangular(Distribution):
		return result


		class UniformProduct(Distribution):
		r"""Represents a distribution whose values are the product of N
		uniformly distributed variables.

		This distribution has the following PDF

		.. math::

		\text{P}(x) =
		\begin{cases}
		\frac{(-1)^{n-1} log^{n-1}(x)}{(n - 1)!} &
		\text{for } x \in [0, 1) \\
		0 & \text{otherwise}
		\end{cases}
		"""

		def __init__(self, n: int):
		super().__init__()
		if n < 1:
		raise ValueError('n must be at least 1.')
		self._n: int = n

		@property
		def n(self) -> int:
		"""Read-only property for the number of uniformly distributed
		variables to multiply."""
		return self._n

		def sample(self, rand) -> float:
		func = getattr(rand,
		'uniformproduct',
		lambda n:
		self._impl(rand, n))
		return func(self._n)

		def as_list(self) -> List:
		return [self.__class__.__name__.casefold(),
		self._n]

		def as_dict(self) -> Dict:
		return {
		'distribution': self.__class__.__name__.casefold(),
		'n': self._n
		}

		@staticmethod
		def _impl(rand, n: int) -> float:
		result: float = 1.0
		for _ in range(n):
		result *= rand.random()
		return result


		class LogNormal(Distribution):
		r"""Represents a log-normal distribution with parameters
		`mu` and `sigma`.

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		@@ -723,6 +723,32 @@ class RepeatableRandomSequence(object):
		low, high = high, low
		return low + (high - low) * sqrt(u * c)

		def uniformproduct(self, n: int) -> float:
		r"""Sample from a distribution whose values are the product of N
		uniformly distributed variables.

		This distribution has the following PDF

		.. math::

		\text{P}(x) =
		\begin{cases}
		\frac{(-1)^{n-1} log^{n-1}(x)}{(n - 1)!} &
		\text{for } x \in [0, 1) \\
		0 & \text{otherwise}
		\end{cases}

		Raises:
		ValueError: if `n` is not at least 1.
		"""
		if n < 1:
		raise ValueError('n must be at least 1.')
		result: float = 1.0
		with self.cascade():
		for _ in range(n):
		result *= self.random()
		return result

		def chance(self, p: float) -> bool:
		"""Returns ``True`` with probability `p`, else ``False``.