Python matrix_equality_ratio Examples

Example #1

File: tst_svd.py Project: cctbx/cctbx-playground

def exercise_svd_basic():
  a = flex.double(xrange(1,19))
  sigma = [ 45.8945322027251, 1.6407053035305987, 0 ]
  a.resize(flex.grid(6,3))
  svd = scitbx.linalg.svd.real(
    a.deep_copy(),
    accumulate_u=True,
    accumulate_v=True)
  assert approx_equal(svd.sigma, sigma)
  a1 = svd.reconstruct()
  assert matrix_equality_ratio(a, a1) < 10
  assert matrix_normality_ratio(svd.u) < 10
  assert matrix_normality_ratio(svd.v) < 10
  svd = scitbx.linalg.svd.real(a.deep_copy(),
                             accumulate_u=False, accumulate_v=False)
  assert approx_equal(svd.sigma, sigma)
  assert not svd.u and not svd.v
  try:
    svd.reconstruct()
    raise Exception_expected
  except AssertionError:
    pass

  a = a.matrix_transpose()
  svd = scitbx.linalg.svd.real(
    a.deep_copy(),
    accumulate_u=True,
    accumulate_v=True)
  assert approx_equal(svd.sigma, sigma)
  a1 = svd.reconstruct()
  assert matrix_equality_ratio(a, a1) < 10
  assert matrix_normality_ratio(svd.u) < 10
  assert matrix_normality_ratio(svd.v) < 10

  a = flex.double(xrange(1,13))
  sigma = [25.436835633480246818, 1.7226122475210637387, 0]
  a.reshape(flex.grid(3,4))
  svd = scitbx.linalg.svd.real(
    a.deep_copy(),
    accumulate_u=True,
    accumulate_v=True)
  assert approx_equal(svd.sigma, sigma)
  a1 = svd.reconstruct()
  assert matrix_equality_ratio(a, a1) < 10
  assert matrix_normality_ratio(svd.u) < 10
  assert matrix_normality_ratio(svd.v) < 10

  a = a.matrix_transpose()
  svd = scitbx.linalg.svd.real(
    a.deep_copy(),
    accumulate_u=True,
    accumulate_v=True)
  assert approx_equal(svd.sigma, sigma)
  a1 = svd.reconstruct()
  assert matrix_equality_ratio(a, a1) < 10
  assert matrix_normality_ratio(svd.u) < 10
  assert matrix_normality_ratio(svd.v) < 10

Example #2

def exercise_svd_basic(klass):
    a = flex.double(range(1, 19))
    sigma = [45.8945322027251, 1.6407053035305987, 0]
    a.resize(flex.grid(6, 3))
    svd = klass(a.deep_copy(), accumulate_u=True, accumulate_v=True)

    assert approx_equal(svd.sigma, sigma)
    a1 = svd.reconstruct()
    assert matrix_equality_ratio(a, a1) < 10
    assert matrix_normality_ratio(svd.u) < 10
    assert matrix_normality_ratio(svd.v) < 10
    svd = klass(a.deep_copy(), accumulate_u=False, accumulate_v=False)
    assert approx_equal(svd.sigma, sigma)
    if klass == scitbx.linalg.svd.real:
        assert not svd.u and not svd.v
    else:
        try:
            svd.u
            raise Exception_expected
        except Exception:
            pass
    try:
        svd.reconstruct()
        raise Exception_expected
    except AssertionError:
        pass
    except RuntimeError:
        if klass == scitbx.linalg.svd_decompose:
            pass

    a = a.matrix_transpose()
    svd = klass(a.deep_copy(), accumulate_u=True, accumulate_v=True)
    assert approx_equal(svd.sigma, sigma)
    a1 = svd.reconstruct()
    assert matrix_equality_ratio(a, a1) < 10
    assert matrix_normality_ratio(svd.u) < 10
    assert matrix_normality_ratio(svd.v) < 10

    a = flex.double(range(1, 13))
    sigma = [25.436835633480246818, 1.7226122475210637387, 0]
    a.reshape(flex.grid(3, 4))
    svd = klass(a.deep_copy(), accumulate_u=True, accumulate_v=True)
    assert approx_equal(svd.sigma, sigma)
    a1 = svd.reconstruct()
    assert matrix_equality_ratio(a, a1) < 10
    assert matrix_normality_ratio(svd.u) < 10
    assert matrix_normality_ratio(svd.v) < 10

    a = a.matrix_transpose()
    svd = klass(a.deep_copy(), accumulate_u=True, accumulate_v=True)
    assert approx_equal(svd.sigma, sigma)
    a1 = svd.reconstruct()
    assert matrix_equality_ratio(a, a1) < 10
    assert matrix_normality_ratio(svd.u) < 10
    assert matrix_normality_ratio(svd.v) < 10