# # This file is part of OpenVSIP. It is made available under the # license contained in the accompanying LICENSE.BSD file. from vsip import vector from vsip import matrix from vsip.selgen.generation import ramp from vsip.math.matvec import dot, prod import numpy as np from numpy import array as A v1 = ramp(float, 0, 1, 8) v2 = ramp(float, 1, 2, 8) d = dot(v1, v2) assert d == np.dot(A(v1), A(v2)) v1 = vector(array=np.arange(4, dtype=float)) m1 = matrix(array=np.arange(16, dtype=float).reshape(4,4)) m2 = matrix(array=np.arange(16, dtype=float).reshape(4,4)) # vector * matrix v3 = prod(v1, m1) assert (A(v3) == np.tensordot(A(v1), A(m1), (0, 0))).all() # matrix * vector v3 = prod(m1, v1) assert (A(v3) == np.tensordot(A(m1), A(v1), (1, 0))).all() # matrix * matrix m3 = prod(m1, m2) assert (A(m3) == np.tensordot(A(m1), A(m2), (1, 0))).all()
from vsip import matrix from vsip.math.solvers import svd from vsip.math.matvec import prod, trans import numpy as np A = matrix(array=[[1., 2., 3.], [4., 5., 6.]]) M, N = A.rows(), A.cols() print A svd = svd(float, M, N, svd.uvfull, svd.uvfull) s = svd.decompose(A) S = matrix(float, M, N) S.diag()[:] = s U = svd.u(0, M - 1) V = svd.v(0, N - 1) C = prod(prod(U, S), trans(V)) print C assert np.isclose(C, A).all()
# Copyright (c) 2013 Stefan Seefeld # All rights reserved. # # This file is part of OpenVSIP. It is made available under the # license contained in the accompanying LICENSE.BSD file. from vsip import vector from vsip import matrix from vsip.selgen.generation import ramp from vsip.math.matvec import dot, prod import numpy as np from numpy import array as A v1 = ramp(float, 0, 1, 8) v2 = ramp(float, 1, 2, 8) d = dot(v1, v2) assert d == np.dot(A(v1), A(v2)) v1 = vector(array=np.arange(4, dtype=float)) m1 = matrix(array=np.arange(16, dtype=float).reshape(4, 4)) m2 = matrix(array=np.arange(16, dtype=float).reshape(4, 4)) # vector * matrix v3 = prod(v1, m1) assert (A(v3) == np.tensordot(A(v1), A(m1), (0, 0))).all() # matrix * vector v3 = prod(m1, v1) assert (A(v3) == np.tensordot(A(m1), A(v1), (1, 0))).all() # matrix * matrix m3 = prod(m1, m2) assert (A(m3) == np.tensordot(A(m1), A(m2), (1, 0))).all()
from vsip import matrix from vsip.math.solvers import svd from vsip.math.matvec import prod, trans import numpy as np A = matrix(array=[[1.,2.,3.],[4.,5.,6.]]) M,N = A.rows(), A.cols() print A svd = svd(float, M, N, svd.uvfull, svd.uvfull) s = svd.decompose(A) S = matrix(float, M, N) S.diag()[:] = s U = svd.u(0, M-1) V = svd.v(0, N-1) C = prod(prod(U, S), trans(V)) print C assert np.isclose(C, A).all()
