which is the version python can run best for chaospy. #89
Description
I have practised run the tutorial but when I run this tutorial then it notified I need to install Odespy package. But Now, I am using the python 3.0 while Odespy only runs on the Python 2.7. So How way to install Odespy for python 3.0 on the Window.
import chaospy as cp
import numpy as np
import odespy
#Intrusive Galerkin method
dist_a = cp.Uniform(0, 0.1)
dist_I = cp.Uniform(8, 10)
dist = cp.J(dist_a, dist_I) # joint multivariate dist
P, norms = cp.orth_ttr(2, dist, retall=True)
variable_a, variable_I = cp.variable(2)
PP = cp.outer(P, P)
E_aPP = cp.E(variable_aPP, dist)
E_IP = cp.E(variable_IP, dist)
def right_hand_side(c, x): # c' = right_hand_side(c, x)
return -np.dot(E_aPP, c)/norms # -M*c
initial_condition = E_IP/norms
solver = odespy.RK4(right_hand_side)
solver.set_initial_condition(initial_condition)
x = np.linspace(0, 10, 1000)
c = solver.solve(x)[0]
u_hat = cp.dot(P, c)
#Rosenblat transformation using point collocation
def u(x,a, I):
return Inp.exp(-ax)
dist_R = cp.J(cp.Normal(), cp.Normal())
C = [[1, 0.5], [0.5, 1]]
mu = [0, 0]
dist_Q = cp.MvNormal(mu, C)
P = cp.orth_ttr(2, dist_R)
nodes_R = dist_R.sample(2*len(P), "M")
nodes_Q = dist_Q.inv(dist_R.fwd(nodes_R))
x = np.linspace(0, 1, 100)
samples_u = [u(x, *node) for node in nodes_Q.T]
u_hat = cp.fit_regression(P, nodes_R, samples_u)
#Rosenblat transformation using pseudo spectral
def u(x,a, I):
return Inp.exp(-ax)
C = [[1,0.5],[0.5,1]]
mu = np.array([0, 0])
dist_R = cp.J(cp.Normal(), cp.Normal())
dist_Q = cp.MvNormal(mu, C)
P = cp.orth_ttr(2, dist_R)
nodes_R, weights_R = cp.generate_quadrature(3, dist_R)
nodes_Q = dist_Q.inv(dist_R.fwd(nodes_R))
weights_Q = weights_R*dist_Q.pdf(nodes_Q)/dist_R.pdf(nodes_R)
x = np.linspace(0, 1, 100)
samples_u = [u(x, *node) for node in nodes_Q.T]
u_hat = cp.fit_quadrature(P, nodes_R, weights_Q, samples_u)