#! /usr/bin/env python

import openturns as ot
import math as m
import os


class UniformNdPy(ot.PythonDistribution):
    def __init__(self, a=[0.0], b=[1.0]):
        super(UniformNdPy, self).__init__(len(a))
        if len(a) != len(b):
            raise ValueError("Invalid bounds")
        for i in range(len(a)):
            if a[i] > b[i]:
                raise ValueError("Invalid bounds")
        self.a = a
        self.b = b
        self.factor = 1.0
        for i in range(len(a)):
            self.factor *= b[i] - a[i]

    def getRange(self):
        return ot.Interval(self.a, self.b, [True] * len(self.a), [True] * len(self.a))

    def getRealization(self):
        X = []
        for i in range(len(self.a)):
            X.append(
                self.a[i] + (self.b[i] - self.a[i]) * ot.RandomGenerator.Generate()
            )
        return X

    def getSample(self, size):
        X = []
        for i in range(size):
            X.append(self.getRealization())
        return X

    def computeCDF(self, X):
        prod = 1.0
        for i in range(len(self.a)):
            if X[i] < self.a[i]:
                return 0.0
            prod *= min(self.b[i], X[i]) - self.a[i]
        return prod / self.factor

    def computePDF(self, X):
        for i in range(len(self.a)):
            if X[i] < self.a[i]:
                return 0.0
            if X[i] > self.b[i]:
                return 0.0
        return 1.0 / self.factor

    def getRoughness(self):
        return 42.0

    def getMean(self):
        mu = []
        for i in range(len(self.a)):
            mu.append(0.5 * (self.a[i] + self.b[i]))
        return mu

    def getStandardDeviation(self):
        stdev = []
        for i in range(len(self.a)):
            stdev.append((self.b[i] - self.a[i]) / m.sqrt(12.0))
        return stdev

    def getSkewness(self):
        return [0.0] * len(self.a)

    def getKurtosis(self):
        return [1.8] * len(self.a)

    def getMoment(self, n):
        return [-0.1 * n] * len(self.a)

    def getCentralMoment(self, n):
        return [0.0] * len(self.a)

    def computeCharacteristicFunction(self, x):
        if len(self.a) > 1:
            raise ValueError("dim>1")
        ax = self.a[0] * x
        bx = self.b[0] * x
        return (m.sin(bx) - m.sin(ax) + 1j * (m.cos(ax) - m.cos(bx))) / (bx - ax)

    def isElliptical(self):
        return (len(self.a) == 1) and (self.a[0] == -self.b[0])

    def isCopula(self):
        for i in range(len(self.a)):
            if self.a[i] != 0.0:
                return False
            if self.b[i] != 1.0:
                return False
        return True

    def getMarginal(self, indices):
        subA = []
        subB = []
        for i in indices:
            subA.append(self.a[i])
            subB.append(self.b[i])
        py_dist = UniformNdPy(subA, subB)
        return ot.Distribution(py_dist)

    def computeQuantile(self, prob, tail=False):
        p = 1.0 - prob if tail else prob
        quantile = self.a
        for i in range(len(self.a)):
            quantile[i] += p * (self.b[i] - self.a[i])
        return quantile

    def getParameter(self):
        param = list(self.a)
        param.extend(self.b)
        return param

    def getParameterDescription(self):
        paramDesc = ["a_" + str(i) for i in range(len(self.a))]
        paramDesc.extend(["b_" + str(i) for i in range(len(self.a))])
        return paramDesc

    def setParameter(self, parameter):
        dim = len(self.a)
        for i in range(dim):
            self.a[i] = parameter[i]
            self.b[i] = parameter[dim + i]


myDist = ot.Distribution(UniformNdPy([0.0] * 2, [2.0] * 2))

st = ot.Study()
fileName = "PyDIST.xml"
st.setStorageManager(ot.XMLStorageManager(fileName))

st.add("myDist", myDist)
st.save()

print("saved dist=", myDist)

dist = ot.Distribution()

st = ot.Study()
st.setStorageManager(ot.XMLStorageManager(fileName))

st.load()

st.fillObject("myDist", dist)
print("loaded dist=", dist)
os.remove(fileName)