test/matrices_test.py

   1 """
   2 Unit tests for the functions in the ``matrices`` module.
   3 """
   4
   5 from unittest import TestCase
   6
   7 from cvxopt import matrix
   8
   9 from dunshire.matrices import (append_col, append_row, condition_number,
  10                                eigenvalues, eigenvalues_re, identity,
  11                                inner_product, norm)
  12 from dunshire.options import ABS_TOL
  13 from .randomgen import random_matrix, random_natural, random_scalar
  14
  15 class AppendColTest(TestCase):
  16
  17     def test_size_increases(self):
  18         """
  19         If we append a column to a matrix, the result should be bigger
  20         than the original matrix.
  21         """
  22         dims = random_natural()
  23         mat1 = random_matrix(dims)
  24         mat2 = random_matrix(dims)
  25         bigmat = append_col(mat1, mat2)
  26         self.assertTrue(bigmat.size[0] >= mat1.size[0])
  27         self.assertTrue(bigmat.size[1] >= mat1.size[1])
  28
  29
  30 class AppendRowTest(TestCase):
  31
  32     def test_size_increases(self):
  33         """
  34         If we append a row to a matrix, the result should be bigger
  35         than the original matrix.
  36         """
  37         dims = random_natural()
  38         mat1 = random_matrix(dims)
  39         mat2 = random_matrix(dims)
  40         bigmat = append_row(mat1, mat2)
  41         self.assertTrue(bigmat.size[0] >= mat1.size[0])
  42         self.assertTrue(bigmat.size[1] >= mat1.size[1])
  43
  44
  45 class EigenvaluesTest(TestCase):
  46
  47     def test_eigenvalues_input_not_clobbered(self):
  48         mat = random_matrix(random_natural())
  49         symmat = mat + mat.trans()
  50         symmat_copy = matrix(symmat, symmat.size)
  51         eigs = eigenvalues(symmat)
  52         self.assertTrue(norm(symmat - symmat_copy) < ABS_TOL)
  53
  54     def test_eigenvalues_re_input_not_clobbered(self):
  55         mat = random_matrix(random_natural())
  56         mat_copy = matrix(mat, mat.size)
  57         eigs = eigenvalues_re(mat)
  58         self.assertTrue(norm(mat - mat_copy) < ABS_TOL)
  59
  60     def test_eigenvalues_of_symmetric_are_real(self):
  61         mat = random_matrix(random_natural())
  62         symmat = mat + mat.trans()
  63         eigs1 = sorted(eigenvalues(symmat))
  64         eigs2 = sorted(eigenvalues_re(symmat))
  65         diffs = [abs(e1-e2) for (e1,e2) in zip(eigs1,eigs2)]
  66         self.assertTrue(all([diff < ABS_TOL for diff in diffs]))
  67
  68
  69     def test_eigenvalues_of_identity(self):
  70         mat = identity(random_natural(), typecode='d')
  71         eigs1 = eigenvalues(mat)
  72         eigs2 = eigenvalues_re(mat)
  73         self.assertTrue(all([abs(e1 - 1) < ABS_TOL for e1 in eigs1]))
  74         self.assertTrue(all([abs(e2 - 1) < ABS_TOL for e2 in eigs2]))
  75
  76
  77 class InnerProductTest(TestCase):
  78
  79     def test_norm_is_nonnegative(self):
  80         vec = matrix([random_scalar() for _ in range(random_natural())])
  81         self.assertTrue(inner_product(vec,vec) >= 0)
  82
  83
  84 def ConditionNumberTest(TestCase):
  85
  86     def test_condition_number_ge_one(self):
  87         mat = random_matrix(random_natural())
  88         self.assertTrue(condition_number(mat) >= 1)