#! /usr/bin/env python

from __future__ import print_function
from openturns import *

TESTPREAMBLE()

try:
    matrix1 = CovarianceMatrix(2)
    print("matrix1 (default)=" + repr(matrix1))
    matrix1[0, 0] = 1.0
    matrix1[1, 0] = 0.5
    matrix1[1, 1] = 1.0
    print("matrix1 (initialized)=" + repr(matrix1))

    pt = NumericalPoint()
    pt.add(5.0)
    pt.add(0.0)
    print("pt=", repr(pt))

    result = NumericalPoint()
    result = matrix1.solveLinearSystem(pt)
    print("result=" + repr(result))

    determinant = matrix1.computeDeterminant()
    print("determinant=%.6f" % determinant)

    ev = NumericalScalarCollection(2)
    ev = matrix1.computeEigenValues()
    print("ev=" + repr(ev))

    if matrix1.isPositiveDefinite():
        isSPD = "true"
    else:
        isSPD = "false"
    print("isSPD=", isSPD)

    matrix2 = matrix1.computeCholesky()
    print("matrix2=" + repr(matrix2))

    b = Matrix(2, 3)
    b[0, 0] = 5.0
    b[1, 0] = 0.0
    b[0, 1] = 10.0
    b[1, 1] = 1.0
    b[0, 2] = 15.0
    b[1, 2] = 2.0
    result2 = matrix1.solveLinearSystem(b, True)
    print("result2=" + repr(result2))

except:
    import sys
    print("t_CovarianceMatrixLapack_std.py",
          sys.exc_info()[0], sys.exc_info()[1])