/usr/lib/openturns/examples/t_MergeRandomAndConstantInput.py is in openturns-examples 0.15-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | #! /usr/bin/env python
from openturns import *
TESTPREAMBLE()
try :
# External code. This code has an input vector of dimension 4, namely (p0, p1, p2, p3).
externalCode = NumericalMathFunction("poutre")
dim = externalCode.getInputDimension()
# The external code will be connected to 2 independent random variables X0 and X1 and one deterministic variable X2 with the following scheme:
# X2->p0
# X0->p1
# X1->p2
# X0->p3
# It means that (p0, p1, p2, p3) = A.(X0, X1) + b with:
# A = [0 0] b = [X2]
# [1 0] [ 0]
# [0 1] [ 0]
# [1 0] [ 0]
# Here we build the linear function x -> A.x + b
stochasticDimension = 2
# UnsignedLong deterministicDimension(1)
A = Matrix(dim, stochasticDimension)
A[1, 0] = 1
A[2, 1] = 1
A[3, 0] = 1
b = NumericalPoint(dim, 0)
X2 = 50.0
b[0] = X2
center = NumericalPoint(stochasticDimension , 0.0)
connect = LinearNumericalMathFunction(center, b, A)
connect.setName("connect")
# We are now ready to build the resulting code externalCode(connect()) #
finalCode = NumericalMathFunction(externalCode, connect)
# Check if it worked #
x = NumericalPoint(connect.getInputDimension())
x[0] = 5
x[1] = 10
print "finalCode(x)=", repr(finalCode(x) )
xRef = NumericalPoint(dim)
xRef[0] = X2
xRef[1] = x[0]
xRef[2] = x[1]
xRef[3] = x[0]
print "ref=", repr(externalCode(xRef))
except :
import sys
print "t_MergeRandomAndConstantInput.py", sys.exc_type, sys.exc_value
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