Hello,
I am attempting to use a custom continuous probability distribution for a
probability of failure calculation via FORM, but when I try to create a
ComposedDistribution with my custom dist, the program fails with
NotImplementedError: Wrong number or type of arguments for overloaded function
'new_ComposedDistribution'.
The custom dist is defined as
class JohnsonSU(ot.PythonDistribution):
def __init__(self, gamma=1, xi=0, delta=0.5, lam=1):
super(JohnsonSU, self).__init__(1)
if np.any(delta <= 0):
raise ValueError('Delta must be >0.')
if np.any(lam <= 0):
raise ValueError('Lambda must be >0.')
self.gamma = gamma # shape 1
self.xi = xi # location
self.delta = delta # shape 2, >0
self.lam = lam # scale, >0
self.scipy_dist = st.johnsonsu(self.gamma, self.delta, loc=self.xi,
scale=self.lam)
def computeCDF(self, x):
return self.scipy_dist.cdf(x)
def computePDF(self, x):
return self.scipy_dist.pdf(x)
def computeQuantile(self, p):
return self.scipy_dist.ppf(p)
def getMean(self):
return self.scipy_dist.mean()
def getStandardDeviation(self):
return self.scipy_dist.std()
Are there additional functions that must be defined in order for the
PythonDistribution to be compatible with existing OpenTurns Distributions? Or,
is there a straightforward way that I could add arbitrary distributions to the
OpenTurns source code?
Many thanks!
Phil Fernandes P.Eng, MASc
Engineer, Reliability Assessment
-
ENBRIDGE PIPELINES INC.
TEL: 780-420-8210 | FAX: 780-420-5234
7045 Enbridge Centre, 10175 101 Street NW, Edmonton, AB, T5J 0H3
www.enbridge.com<http://www.enbridge.com/>
Integrity. Safety. Respect.
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