/usr/include/openturns/swig/Distribution.i is in libopenturns-dev 1.9-5.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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// do not pass argument by reference, return it as tuple item
%typemap(in, numinputs=0) OT::Point & marginalProb ($*ltype temp) %{ temp = OT::Point(); $1 = &temp; %}
%typemap(argout) OT::Point & marginalProb %{ $result = SWIG_Python_AppendOutput($result, SWIG_NewPointerObj(new OT::Point(*$1), SWIG_TypeQuery("OT::Point *"), SWIG_POINTER_OWN | 0 )); %}
OT::Interval OT::DistributionImplementation::computeMinimumVolumeInterval(const OT::Scalar prob, OT::Point & marginalProb) const;
OT::Interval OT::DistributionImplementation::computeBilateralConfidenceInterval(const OT::Scalar prob, OT::Point & marginalProb) const;
OT::Interval OT::DistributionImplementation::computeUnilateralConfidenceInterval(const OT::Scalar prob, const OT::Bool tail, OT::Point & marginalProb) const;
%typemap(in, numinputs=0) OT::Point & threshold ($*ltype temp) %{ temp = OT::Point(); $1 = &temp; %}
%typemap(argout) OT::Point & threshold %{ $result = SWIG_Python_AppendOutput($result, SWIG_NewPointerObj(new OT::Point(*$1), SWIG_TypeQuery("OT::Point *"), SWIG_POINTER_OWN | 0 )); %}
OT::LevelSet OT::DistributionImplementation::computeMinimumVolumeLevelSet(const OT::Scalar prob, OT::Point & threshold) const;
%{
#include "openturns/Distribution.hxx"
#include "openturns/PythonDistribution.hxx"
%}
%include Distribution_doc.i
%pythoncode %{
from openturns.typ import Interval
class PythonDistribution(object):
"""
Allow to override Distribution from Python.
Parameters
----------
dim : positive int
the distribution dimension
"""
def __init__(self, dim=0):
self.__dim = dim
def __str__(self):
return 'PythonDistribution -> #%d' % self.__dim
def __repr__(self):
return self.__str__()
def getDimension(self):
return self.__dim
def computeCDF(self, X):
raise RuntimeError('You must define a method computeCDF(x) -> cdf, where cdf is a float')
class SciPyDistribution(PythonDistribution):
"""
Allow to override Distribution from a scipy distribution.
Parameters
----------
dist : a scipy.stats distribution
the distribution to wrap
"""
def __init__(self, dist):
super(SciPyDistribution, self).__init__(1)
if dist.__class__.__name__ != 'rv_frozen':
raise TypeError('Argument is not a scipy distribution')
self._dist = dist
# compute range
lb = dist.ppf(0.)
ub = dist.ppf(1.)
flb = lb != float('-inf')
fub = ub != float('+inf')
self.__range = Interval([lb], [ub])
self.__range.setFiniteLowerBound([int(flb)])
self.__range.setFiniteUpperBound([int(fub)])
def getRange(self):
return self.__range
def getRealization(self):
rvs = self._dist.rvs()
return [rvs]
def getSample(self, size):
rvs = self._dist.rvs(size)
return rvs.reshape(size, 1)
def computePDF(self, X):
pdf = self._dist.pdf(X[0])
return pdf
def computeCDF(self, X):
cdf = self._dist.cdf(X[0])
return cdf
def getMean(self):
mean = float(self._dist.stats('m'))
return [mean]
def getStandardDeviation(self):
var = float(self._dist.stats('v'))
std = var ** 0.5
return [std]
def getSkewness(self):
skewness = float(self._dist.stats('s'))
return [skewness]
def getKurtosis(self):
kurtosis = float(self._dist.stats('k'))
return [kurtosis]
def getMoment(self, n):
moment = self._dist.moment(n)
return [moment]
%}
%include UncertaintyModelCopulaCollection.i
OTTypedInterfaceObjectHelper(Distribution)
OTTypedCollectionInterfaceObjectHelper(Distribution)
%ignore OT::Distribution::pow;
%ignore OT::Distribution::setWeight;
%ignore OT::Distribution::getWeight;
%include openturns/Distribution.hxx
namespace OT {
%extend Distribution {
Distribution(const Distribution & other)
{
return new OT::Distribution(other);
}
Distribution(PyObject * pyObj)
{
return new OT::Distribution( new OT::PythonDistribution( pyObj ) );
}
Distribution __add__ (Scalar s)
{
return *self + s;
}
Distribution __radd__ (Scalar s)
{
return *self + s;
}
Distribution __sub__(Scalar s)
{
return *self - s;
}
Distribution __rsub__(Scalar s)
{
return (*self * (-1.0)) + s;
}
Distribution __mul__(Scalar s)
{
return (*self) * s;
}
Distribution __rmul__(Scalar s)
{
return (*self) * s;
}
Distribution __div__(Scalar s)
{
return (*self) / s;
}
#if SWIG_VERSION < 0x030011
Distribution __truediv__(Scalar s) { return (*self) / s; }
#endif
} // class Distribution
} // namespace OT
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