Source code for pymultifit.distributions.arcSine_d

"""Created on Aug 14 02:02:42 2024"""

from .backend import errorHandling as erH, BaseDistribution
from .utilities_d import arc_sine_pdf_, arc_sine_cdf_, arc_sine_log_pdf_, arc_sine_log_cdf_


[docs] class ArcSineDistribution(BaseDistribution): r""" Class for ArcSine distribution. .. note:: The :class:`ArcSineDistribution` is a special case of the :class:`~pymultifit.distributions.beta_d.BetaDistribution`, * :math:`\alpha_\text{beta} = 0.5`, * :math:`\lambda_\text{beta} = 0.5`. :param amplitude: The amplitude of the PDF. Defaults to 1.0. Ignored if **normalize** is ``True``. :type amplitude: float, optional :param loc: The location parameter, :math:`-` shifting. Defaults to 0.0. :type loc: float, optional :param scale: The scale parameter, for shifting. Defaults to 1.0. :type scale: float, optional :param normalize: If ``True``, the distribution is normalized so that the total area under the PDF equals 1. Defaults to ``False``. :type normalize: bool, optional :raise NegativeAmplitudeError: If the provided value of amplitude is negative. :raise NegativeScaleError: If the provided value of scale is negative. :example: Importing libraries .. literalinclude:: ../../../examples/basic/arcSine.py :language: python :linenos: :lineno-start: 3 :lines: 3-7 Generating the ArcSine distribution with ``pyMultiFit`` and ``scipy``. .. literalinclude:: ../../../examples/basic/arcSine.py :language: python :linenos: :lineno-start: 9 :lines: 9-12 Plotting **PDF** and **CDF** .. literalinclude:: ../../../examples/basic/arcSine.py :language: python :linenos: :lineno-start: 14 :lines: 14-27 .. image:: ../../../images/arcsine_example.png :alt: ArcSine distribution :align: center """ def __init__(self, amplitude: float = 1., loc: float = 0.0, scale: float = 1.0, normalize: bool = False): if not normalize and amplitude <= 0: raise erH.NegativeAmplitudeError() if scale < 0: raise erH.NegativeScaleError() self.amplitude = 1 if normalize else amplitude self.loc = loc self.scale = scale self.norm = normalize
[docs] def pdf(self, x): return arc_sine_pdf_(x, amplitude=self.amplitude, loc=self.loc, scale=self.scale, normalize=self.norm)
[docs] def logpdf(self, x): return arc_sine_log_pdf_(x, amplitude=self.amplitude, loc=self.loc, scale=self.scale, normalize=self.norm)
[docs] def cdf(self, x): return arc_sine_cdf_(x, amplitude=self.amplitude, loc=self.loc, scale=self.scale, normalize=self.norm)
[docs] def logcdf(self, x): return arc_sine_log_cdf_(x, amplitude=self.amplitude, loc=self.loc, scale=self.scale, normalize=self.norm)
[docs] @classmethod def scipy_like(cls, loc: float = 0.0, scale: float = 1.0): """ Instantiate ArcSineDistribution with scipy parameterization. Parameters ---------- loc: float, optional The location parameter. Defaults to 0.0. scale: float, optional The scale parameter. Defaults to 1.0. Returns ------- ArcSineDistribution An instance of normalized ArcSineDistribution. """ return cls(loc=loc, scale=scale, normalize=True)
[docs] def stats(self): s_, l_ = self.scale, self.loc mean_ = (s_ * 0.5) + l_ median_ = (s_ * 0.5) + l_ variance_ = (1 / 8) * s_**2 return {'mean': mean_, 'median': median_, 'mode': None, 'variance': variance_, 'std': variance_**0.5}