Source code for pymultifit.distributions.backend.errorHandling

"""Created on Dec 09 02:28:10 2024"""

neg_message = "cannot be negative."


[docs] class BaseDistributionError(Exception): """Base class for distribution-related errors.""" pass
[docs] class DegreeOfFreedomError(BaseDistributionError): """Raised when the degree of freedom is a float instead of int.""" def __init__(self): super().__init__(r"DOF can only be integer, N+")
[docs] class InvalidUniformParameters(BaseDistributionError): """Raised when the parameters of uniform distributions are not valid.""" def __init__(self): super().__init__("High < Low, invalid parameter selection.")
[docs] class NegativeAlphaError(BaseDistributionError): """Raised when the alpha parameter value is negative.""" def __init__(self): super().__init__(f"Alpha {neg_message}.")
[docs] class NegativeAmplitudeError(BaseDistributionError): """Raised when the amplitude is negative.""" def __init__(self): super().__init__(f"Amplitude {neg_message}")
[docs] class NegativeBetaError(BaseDistributionError): """Raised when the beta parameter value is negative.""" def __init__(self): super().__init__(f"Beta {neg_message}")
[docs] class NegativeRateError(BaseDistributionError): """Raised when the value of rate parameter is negative.""" def __init__(self): super().__init__(f"Rate {neg_message}")
[docs] class NegativeScaleError(BaseDistributionError): """Raised when the value of scale parameter is negative.""" def __init__(self, parameter='scale'): super().__init__(f"{parameter.capitalize()} {neg_message}")
[docs] class NegativeShapeError(BaseDistributionError): """Raised when the value of shape parameter is negative.""" def __init__(self): super().__init__(f"Shape {neg_message}")
[docs] class NegativeStandardDeviationError(BaseDistributionError): """Raised when the standard deviation is negative.""" def __init__(self): super().__init__(f"Standard deviation {neg_message}")
[docs] class NegativeVarianceError(BaseDistributionError): """Raised when the variance value is negative.""" def __init__(self): super().__init__("Variance cannot be negative.")
[docs] class XOutOfRange(BaseDistributionError): """Raised when the x value is out of range for the distribution.""" def __init__(self): super().__init__("X out of range.")