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#! /usr/bin/env python
from __future__ import print_function
from openturns import *
import numpy as np
TESTPREAMBLE()
try:
# Check tuple / NumericalPoint conversion
t0 = (0.5, 1.5)
p0 = NumericalPoint(t0)
print("tuple", t0, "=> NumericalPoint", p0)
t1 = tuple(p0)
print("NumericalPoint", p0, "=> tuple", t1)
print("NumericalPoint", p0, "+ tuple", t0, "=> NumericalPoint", p0 + t0)
# Check list / NumericalPoint conversion
l0 = [0.5, 1.5]
p0 = NumericalPoint(l0)
print("list", l0, "=> NumericalPoint", p0)
l1 = list(p0)
print("NumericalPoint", p0, "=> list", l1)
print("NumericalPoint", p0, "+ list", l0, "=> NumericalPoint", p0 + l0)
# Check sequence protocol for NumericalPoint
for x in p0:
print("value", x)
x0 = p0[0]
p0[0] = x0
if x0 not in p0:
raise ValueError("NumericalPoint badly implements __contains__()")
# Check array / NumericalPoint conversion
a0 = np.array((0.5, 1.5))
p0 = NumericalPoint(a0)
print("array", a0, "=> NumericalPoint", p0)
a1 = np.array(p0)
print("NumericalPoint", p0, "=> array", a1)
print("NumericalPoint", p0, "+ array", a0, "=> NumericalPoint", p0 + a0)
print("array", a0, "+ NumericalPoint", p0, "=> array", a0 + p0)
# See ticket #423
m0 = np.array([[1, 1], [2, 2], [3, 3]])
try:
p0 = NumericalPoint(m0)
print(p0)
except:
print(
'Conversion from 2d-array => NumericalPoint failed (as expected :)')
# Check tuple / NumericalSample conversion
t0 = ((1., 2.), (3., 4.))
s0 = NumericalSample(t0)
print("tuple", t0, "=> NumericalSample", s0)
t0 = ([1., 2.], [3., 4.])
s0 = NumericalSample(t0)
print("tuple", t0, "=> NumericalSample", s0)
t1 = tuple(s0)
print("NumericalSample", s0, "=> tuple", t1)
# Check list / NumericalSample conversion
l0 = [[1., 2.], [3., 4.]]
s0 = NumericalSample(l0)
print("list", l0, "=> NumericalSample", s0)
l0 = [(1., 2.), (3., 4.)]
s0 = NumericalSample(l0)
print("list", l0, "=> NumericalSample", s0)
l1 = list(s0)
print("NumericalSample", s0, "=> list", l1)
# Check array / NumericalSample conversion
a0 = np.array(((1., 2.), (3., 4.)))
s0 = NumericalSample(a0)
print("array", a0, "=> NumericalSample", s0)
a1 = np.array(s0)
print("NumericalSample", s0, "=> array", a1)
# Check tuple / NumericalMathFunction interoperability
F = NumericalMathFunction(
('E', 'F', 'L', 'I'), ('d',), ('-F*L^3/(3.*E*I)',))
t0 = (1., 2., 3., 4.)
print("NumericalPoint", F(t0), "= F( tuple", t0, ")")
# Check list / NumericalMathFunction interoperability
l0 = [1., 2., 3., 4.]
print("NumericalPoint", F(l0), "= F( list", l0, ")")
# Check array / NumericalMathFunction interoperability
a0 = np.array((1., 2., 3., 4.))
print("NumericalPoint", F(a0), "= F( array", a0, ")")
a1 = np.array(((1., 2., 3., 4.), (5., 6., 7., 8.)))
print("NumericalSample", F(a1), "= F( array", a1, ")")
# Check Python function / NumericalMathFunction interoperability
def aFunc(x):
return [x[0] + x[1] + x[2] + x[3]]
PYNMF = PythonFunction(4, 1, aFunc)
print("NumericalPoint", PYNMF(t0), "= PYNMF( tuple", t0, ")")
print("NumericalPoint", PYNMF(l0), "= PYNMF( list", l0, ")")
print("NumericalPoint", PYNMF(a0), "= PYNMF( array", a0, ")")
print("NumericalSample", PYNMF(a1), "= PYNMF( array", a1, ")")
# Check 2-d array which nested dim is size=1 / NumericalMathFunction
# interoperability
def aFunc2(x):
return [2.0 * x[0]]
PYNMF = PythonFunction(1, 1, aFunc2)
a0 = np.array(([1.]))
print("NumericalPoint", PYNMF(a0), "= PYNMF( array", a0, ")")
a1 = np.array(([1.], [2.], [3.]))
print("NumericalSample", PYNMF(a1), "= PYNMF( array", a1, ")")
# Check tuple / Indices conversion
t0 = (1, 2)
i0 = Indices(t0)
print("tuple", t0, "=> Indices", i0)
t1 = tuple(i0)
print("Indices", i0, "=> tuple", tuple([int(x) for x in t0]))
# Check list / Indices conversion
l0 = [3, 4, 5]
i0 = Indices(l0)
print("list", l0, "=> Indices", i0)
l1 = list(i0)
print("Indices", i0, "=> list", [int(x) for x in l1])
# check Indices typemap
sample = Normal(3).getSample(10)
print(sample.getDescription())
marginal = sample.getMarginal((0, 2))
print(marginal.getDescription())
marginal = sample.getMarginal([0, 2])
print(marginal.getDescription())
# Check tuple / Description conversion
t0 = ('blob', 'zou')
i0 = Description(t0)
print("tuple", t0, "=> Description", i0)
t1 = tuple(i0)
print("Description", i0, "=> tuple", t1)
# Check list / Description conversion
l0 = ['blob', 'zou']
i0 = Description(l0)
print("list", l0, "=> Description", i0)
l1 = list(i0)
print("Description", i0, "=> list", l1)
# array / Description conversion
a0 = np.array(('x0', 'x1', 'x2'))
d0 = Description(a0)
print("array", a0, "=> Description", d0)
a1 = np.array(d0)
print("Description", d0, "=> array", a1)
# check Description typemap
sample.setDescription(('x0', 'x1', 'x2'))
print(sample.getDescription())
sample.setDescription(('y0', 'y1', 'y2'))
print(sample.getDescription())
sample.setDescription(np.array(('z0', 'z1', 'z2')))
print(sample.getDescription())
# Check Matrix tuple constructor
t0 = (1., 2., 3., 4.)
m0 = Matrix(2, 2, t0)
print("tuple", t0, "=> Matrix", m0)
m0 = SquareMatrix(2, t0)
print("tuple", t0, "=> SquareMatrix", m0)
m0 = SymmetricMatrix(2, t0)
print("tuple", t0, "=> SymmetricMatrix", m0)
m0 = Tensor(2, 2, 1, t0)
print("tuple", t0, "=> Tensor", m0)
m0 = SymmetricTensor(2, 1, t0)
print("tuple", t0, "=> SymmetricTensor", m0)
m0 = CorrelationMatrix(2, t0)
print("tuple", t0, "=> CorrelationMatrix", m0)
m0 = CovarianceMatrix(2, t0)
print("tuple", t0, "=> CovarianceMatrix", m0)
t0c = (1. + 3.j, 2. - 5.j, 3. + 7.j, 4. - 9.j)
m0 = ComplexMatrix(2, 2, t0)
print("tuple", t0, "=> ComplexMatrix", m0)
m0 = ComplexMatrix(2, 2, t0c)
print("tuple", t0c, "=> ComplexMatrix", m0)
m0 = SquareComplexMatrix(2, t0)
print("tuple", t0, "=> SquareComplexMatrix", m0)
m0 = SquareComplexMatrix(2, t0c)
print("tuple", t0c, "=> SquareComplexMatrix", m0)
# Check Matrix list constructor
l0 = [1., 2., 3., 4.]
m0 = Matrix(2, 2, l0)
print("list", l0, "=> Matrix", m0)
m0 = SquareMatrix(2, l0)
print("list", l0, "=> SquareMatrix", m0)
m0 = SymmetricMatrix(2, l0)
print("list", l0, "=> SymmetricMatrix", m0)
m0 = Tensor(2, 2, 1, l0)
print("list", l0, "=> Tensor", m0)
m0 = SymmetricTensor(2, 1, l0)
print("list", l0, "=> SymmetricTensor", m0)
m0 = CorrelationMatrix(2, l0)
print("list", l0, "=> CorrelationMatrix", m0)
m0 = CovarianceMatrix(2, l0)
print("list", l0, "=> CovarianceMatrix", m0)
l0c = [1. + 3.j, 2. - 5.j, 3. + 7.j, 4. - 9.j]
m0 = ComplexMatrix(2, 2, l0)
print("list", l0, "=> ComplexMatrix", m0)
m0 = ComplexMatrix(2, 2, l0c)
print("list", l0c, "=> ComplexMatrix", m0)
m0 = SquareComplexMatrix(2, l0)
print("list", l0, "=> SquareComplexMatrix", m0)
m0 = SquareComplexMatrix(2, l0c)
print("list", l0c, "=> SquareComplexMatrix", m0)
# Check Matrix 1-d array constructor
a0 = np.array((1., 2., 3., 4.))
m0 = Matrix(2, 2, a0)
print("array", a0, "=> Matrix", m0)
m0 = SquareMatrix(2, a0)
print("array", a0, "=> SquareMatrix", m0)
m0 = SymmetricMatrix(2, a0)
print("array", a0, "=> SymmetricMatrix", m0)
m0 = Tensor(2, 2, 1, a0)
print("array", a0, "=> Tensor", m0)
m0 = SymmetricTensor(2, 1, a0)
print("array", a0, "=> SymmetricTensor", m0)
m0 = CorrelationMatrix(2, a0)
print("array", a0, "=> CorrelationMatrix", m0)
m0 = CovarianceMatrix(2, a0)
print("array", a0, "=> CovarianceMatrix", m0)
a0c = np.array((1. + 3j, 2. - 5j, 3. - 7j, 4. + 9j))
m0 = ComplexMatrix(2, 2, a0)
print("array", a0, "=> ComplexMatrix", m0)
m0 = ComplexMatrix(2, 2, a0c)
print("array", a0c, "=> ComplexMatrix", m0)
m0 = SquareComplexMatrix(2, a0)
print("array", a0, "=> SquareComplexMatrix", m0)
m0 = SquareComplexMatrix(2, a0c)
print("array", a0c, "=> SquareComplexMatrix", m0)
# check array / Matrix conversion
a0 = np.array(((1., 2.), (3., 4.), (5., 6.)))
m0 = Matrix(a0)
print("array", a0, "=> Matrix", m0)
a1 = np.array(m0)
print("Matrix", m0, "=> array", a1)
a0 = np.array(((1., 2.), (3., 4.)))
m0 = SquareMatrix(a0)
print("array", a0, "=> SquareMatrix", m0)
a1 = np.array(m0)
print("SquareMatrix", m0, "=> array", a1)
a0 = np.array(((1., 2.), (0., 4.)))
m0 = TriangularMatrix(a0)
print("array", a0, "=> TriangularMatrix", m0)
a1 = np.array(m0)
print("TriangularMatrix", m0, "=> array", a1)
a0 = np.array(((1., 2.), (2., 4.)))
m0 = SymmetricMatrix(a0)
print("array", a0, "=> SymmetricMatrix", m0)
a1 = np.array(m0)
print("SymmetricMatrix", m0, "=> array", a1)
a0 = np.array(
(((1., 2.), (3., 4.), (5., 6.)), ((7., 8.), (9., 10.), (11., 12.)),
((13., 14.), (15., 16.), (17., 18.)), ((19., 20.), (21., 22.), (23., 24.))))
m0 = Tensor(a0)
print("array", a0, "=> Tensor", m0)
a1 = np.array(m0)
print("Tensor", m0, "=> array", a1)
a0 = np.array((((1., 2.), (3., 4.)), ((3., 4.), (7., 8.))))
m0 = SymmetricTensor(a0)
print("array", a0, "=> SymmetricTensor", m0)
a1 = np.array(m0)
print("SymmetricTensor", m0, "=> array", a1)
a0 = np.array(((2., 1.), (1., 2.)))
m0 = CovarianceMatrix(a0)
print("array", a0, "=> CovarianceMatrix", m0)
a1 = np.array(m0)
print("CovarianceMatrix", m0, "=> array", a1)
a0 = np.array(((1., 0.5), (0.5, 1.)))
m0 = CorrelationMatrix(a0)
print("array", a0, "=> CorrelationMatrix", m0)
a1 = np.array(m0)
print("CorrelationMatrix", m0, "=> array", a1)
a0 = np.array(((1. + 3j, 2. - 5j, 3. + 7j), (4. - 9j, 5. + 11j, 6. - 13j)))
m0 = ComplexMatrix(a0)
print("array", a0, "=> ComplexMatrix", m0)
a1 = np.array(m0)
print("ComplexMatrix", m0, "=> array", a1)
a0 = np.array(((1. + 3j, 2. - 5j), (3. + 7j, 4. - 9j)))
m0 = SquareComplexMatrix(a0)
print("array", a0, "=> SquareComplexMatrix", m0)
a1 = np.array(m0)
print("SquareComplexMatrix", m0, "=> array", a1)
a0 = np.array(((1. + 3j, 0.), (3. + 7j, 4. - 9j)))
m0 = TriangularComplexMatrix(a0)
print("array", a0, "=> TriangularComplexMatrix", m0)
a1 = np.array(m0)
print("TriangularComplexMatrix", m0, "=> array", a1)
a0 = np.array(((1. + 3j, 2. - 5j), (2. + 5j, 4. - 9j)))
m0 = HermitianMatrix(a0)
print("array", a0, "=> HermitianMatrix", m0)
a1 = np.array(m0)
print("HermitianMatrix", m0, "=> array", a1)
# check np.matrix / Matrix conversion
a0 = np.matrix(((1., 2.), (3., 4.), (5., 6.)))
m0 = Matrix(a0)
print("matrix", a0, "=> Matrix", m0)
a1 = np.array(m0)
print("Matrix", m0, "=> matrix", a1)
a0 = np.matrix(
((1. + 3j, 2. - 5j, 3. + 7j), (4. - 9j, 5. + 11j, 6. - 13j)))
m0 = ComplexMatrix(a0)
print("matrix", a0, "=> ComplexMatrix", m0)
a1 = np.array(m0)
print("ComplexMatrix", m0, "=> matrix", a1)
except:
import sys
import traceback
traceback.print_exc(file=sys.stdout)
|
