def _vector_space(self):
print('\nVector.space')
with FailCounter() as counter:
for [n_x, x] in samples(self.space):
if not x.space == self.space:
counter.fail('failed with x={:25s}'.format(n_x))
def norm(self):
"""Estimate the operator norm of the operator.
The norm is estimated by calculating
``A(x).norm() / x.norm()``
for some nonzero ``x``
Returns
-------
norm : `float`
Estimate of operator norm
References
----------
Wikipedia article on `Operator norm
<https://en.wikipedia.org/wiki/Operator_norm>`_.
"""
print('\n== Calculating operator norm ==\n')
operator_norm = 0.0
for [n_x, x] in samples(self.operator.domain):
result = self.operator(x)
x_norm = x.norm()
estimate = 0 if x_norm == 0 else result.norm() / x_norm
operator_norm = max(operator_norm, estimate)
print('Norm is at least: {}'.format(operator_norm))
self.operator_norm = operator_norm
return operator_norm
def vector_equals(self):
"""Verify `LinearSpaceVector.__eq__`."""
print('\nVector.__eq__()')
try:
zero = self.space.zero()
zero == zero
except NotImplementedError:
print('Vector has no __eq__')
return
with FailCounter() as counter:
for [n_x, x], [n_y, y] in samples(self.space,
self.space):
if n_x == n_y:
if not x == y:
counter.fail('failed x == x with x={:25s}'
''.format(n_x))
if x != y:
counter.fail('failed not x != x with x={:25s}'
''.format(n_x))
else:
if x == y:
counter.fail('failed not x == y with x={:25s}, '
'x={:25s}'.format(n_x, n_y))
if not x != y:
counter.fail('failed x != y with x={:25s}, x={:25s}'
''.format(n_x, n_y))
def _derivative_convergence(self):
name = 'Testing derivative is linear approximation'
with FailCounter(name, "Error = "
"inf_c ||A(x+c*p)-A(x)-A'(x)(c*p)|| / c") as counter:
for [name_x, x], [name_dx, dx] in samples(self.operator.domain,
self.operator.domain):
# Precompute some values
deriv = self.operator.derivative(x)
derivdx = deriv(dx)
opx = self.operator(x)
c = 1e-4 # initial step
derivative_ok = False
minerror = float('inf')
while c > 1e-14:
exact_step = self.operator(x + dx * c) - opx
expected_step = c * derivdx
err = (exact_step - expected_step).norm() / c
if err < 1e-4:
derivative_ok = True
break
else:
minerror = min(minerror, err)
c /= 10.0
if not derivative_ok:
counter.fail('x={:15s} p={:15s}, error={}'
''.format(name_x, name_dx, minerror))
def self_adjoint(self):
"""Verify (Ax, y) = (x, Ay)."""
name = 'Verifying the identity (Ax, y) = (x, Ay)'
left_inner_vals = []
right_inner_vals = []
with FailCounter(name, 'error = ||(Ax, y) - (x, Ay)|| / '
'||A|| ||x|| ||y||') as counter:
for [name_x, x], [name_y, y] in samples(self.operator.domain,
self.operator.range):
x_norm = x.norm()
y_norm = y.norm()
l_inner = self.operator(x).inner(y)
r_inner = x.inner(self.operator(y))
denom = self.operator_norm * x_norm * y_norm
error = 0 if denom == 0 else abs(l_inner - r_inner) / denom
if error > 0.00001:
counter.fail('x={:25s} y={:25s} : error={:6.5f}'
''.format(name_x, name_y, error))
left_inner_vals.append(l_inner)
right_inner_vals.append(r_inner)
scale = np.polyfit(left_inner_vals, right_inner_vals, 1)[0]
print('\nThe adjoint seems to be scaled according to:')
print('(x, Ay) / (Ax, y) = {}. Should be 1.0'.format(scale))
def _adjoint_definition(self):
"""Verify (Ax, y) = (x, A^T y)"""
print('\nVerifying the identity (Ax, y) = (x, A^T y)')
Axy_vals = []
xAty_vals = []
with FailCounter('error = ||(Ax, y) - (x, A^T y)|| / '
'||A|| ||x|| ||y||') as counter:
for [n_x, x], [n_y, y] in samples(self.operator.domain,
self.operator.range):
x_norm = x.norm()
y_norm = y.norm()
Axy = self.operator(x).inner(y)
xAty = x.inner(self.operator.adjoint(y))
denom = self.operator_norm * x_norm * y_norm
error = 0 if denom == 0 else abs(Axy - xAty) / denom
if error > 0.00001:
counter.fail('x={:25s} y={:25s} : error={:6.5f}'
''.format(n_x, n_y, error))
Axy_vals.append(Axy)
xAty_vals.append(xAty)
scale = np.polyfit(Axy_vals, xAty_vals, 1)[0]
print('\nThe adjoint seems to be scaled according to:')
print('(x, A^T y) / (Ax, y) = {}. Should be 1.0'.format(scale))
def _identity_of_mult(self):
print('\nIdentity element of multiplication, 1 * x = x')
with FailCounter() as counter:
for [n_x, x] in samples(self.space):
ok = _apprimately_equal(1 * x, x, self.eps)
if not ok:
counter.fail('failed with x={:25s}'.format(n_x))
def vector_space(self):
"""Verify `LinearSpaceVector.space`."""
print('\nVector.space')
with FailCounter() as counter:
for [n_x, x] in samples(self.space):
if not x.space == self.space:
counter.fail('failed with x={:25s}'.format(n_x))
def element_space(self):
"""Verify `LinearSpaceElement.space`."""
with FailCounter(
test_name='Verify `LinearSpaceElement.space`',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
if x.space != self.space:
counter.fail('failed with x={:25s}'.format(n_x))
def _identity_of_mult(self):
"""Check multiplicative neutral element ('one')."""
print('\nIdentity element of multiplication, 1 * x = x')
with FailCounter() as counter:
for [n_x, x] in samples(self.space):
correct = _approx_equal(1 * x, x, self.eps)
if not correct:
counter.fail('failed with x={:25s}'.format(n_x))
def _inverse_element_of_addition(self):
print('\nInverse element of addition, x + (-x) = 0')
zero = self.space.zero()
with FailCounter() as counter:
for [n_x, x] in samples(self.space):
ok = _apprimately_equal(x + (-x), zero, self.eps)
if not ok:
counter.fail('failed with x={:25s}'.format(n_x))
def _inverse_element_of_addition(self):
"""Check additional inverse."""
print('\nInverse element of addition, x + (-x) = 0')
zero = self.space.zero()
with FailCounter() as counter:
for [n_x, x] in samples(self.space):
correct = _approx_equal(x + (-x), zero, self.eps)
if not correct:
counter.fail('failed with x={:25s}'.format(n_x))
def _commutativity_of_addition(self):
print('\nCommutativity of addition, x + y = y + x')
with FailCounter() as counter:
for [n_x, x], [n_y, y] in samples(self.space,
self.space):
ok = _apprimately_equal(x + y, y + x, self.eps)
if not ok:
counter.fail('failed with x={:25s} y={:25s}'
''.format(n_x, n_y))
def _inner_conjugate_symmetry(self):
print('\nConjugate symmetry, (x, y) = (y, x).conj()')
with FailCounter('error = |(x, y) - (y, x).conj()|') as counter:
for [n_x, x], [n_y, y] in samples(self.space,
self.space):
error = abs((x).inner(y) - y.inner(x).conjugate())
if error > self.eps:
counter.fail('x={:25s}, y={:25s}: error={}'
''.format(n_x, n_y, error))
def _norm_homogeneity(self):
print('\nHomogeneity, ||a*x|| = |a| ||x||')
with FailCounter('error = abs(||a*x|| - |a| ||x||)') as counter:
for [name, vec], scalar in samples(self.space,
self.space.field):
error = abs((scalar * vec).norm() - abs(scalar) * vec.norm())
if error > self.eps:
counter.fail('x={:25s} a={}: ||x||={}'
''.format(name, scalar, error))
def _division(self):
print('\nDivision, x / a = x * (1/a)')
with FailCounter() as counter:
for [n_x, x], a in samples(self.space,
self.space.field):
if a != 0:
ok = _apprimately_equal(x / a, x * (1.0 / a), self.eps)
if not ok:
counter.fail('failed with x={:25s}, a={}'
''.format(n_x, a))
def _multiply_associative(self):
print('\nMultiplication associative, x * (y * z) = (x * y) * z')
with FailCounter() as counter:
for [n_x, x], [n_y, y], [n_z, z] in samples(self.space,
self.space,
self.space):
ok = _apprimately_equal(x * (y * z), (x * y) * z, self.eps)
if not ok:
counter.fail('failed with x={:25s} y={:25s} z={:25s}'
''.format(n_x, n_y, n_z))
def _multiply_commutative(self):
print('\nMultiplication commutative, x * y = y * x')
with FailCounter() as counter:
for [n_x, x], [n_y, y], [n_z, z] in samples(self.space,
self.space,
self.space):
ok = _apprimately_equal(x * y, y * x, self.eps)
if not ok:
counter.fail('failed with x={:25s} y={:25s}'
''.format(n_x, n_y))
def _commutativity_of_addition(self):
"""Check addition commutativity."""
print('\nCommutativity of addition, x + y = y + x')
with FailCounter() as counter:
for [n_x, x], [n_y, y] in samples(self.space,
self.space):
correct = _approx_equal(x + y, y + x, self.eps)
if not correct:
counter.fail('failed with x={:25s} y={:25s}'
''.format(n_x, n_y))
def _subtraction(self):
print('\nSubtraction, x - y = x + (-1 * y)')
with FailCounter() as counter:
for [n_x, x], [n_y, y] in samples(self.space,
self.space):
ok = (_apprimately_equal(x - y, x + (-1 * y), self.eps) and
_apprimately_equal(x - y, x + (-y), self.eps))
if not ok:
counter.fail('failed with x={:25s}, y={:25s}'
''.format(n_x, n_y))
def _vector_assign(self):
print('\nVector.assign()')
with FailCounter() as counter:
for [n_x, x], [n_y, y] in samples(self.space,
self.space):
x.assign(y)
ok = _apprimately_equal(x, y, self.eps)
if not ok:
counter.fail('failed with x={:25s} y={:25s}'
''.format(n_x, n_y))
def _vector_set_zero(self):
print('\nVector.set_zero()')
zero = self.space.zero()
with FailCounter() as counter:
for [n_x, x] in samples(self.space):
x.set_zero()
ok = _apprimately_equal(x, zero, self.eps)
if not ok:
counter.fail('failed with x={:25s}'
''.format(n_x))
def _inner_linear_scalar(self):
print('\nLinearity scalar, (a*x, y) = a*(x, y)')
with FailCounter('error = |(a*x, y) - a*(x, y)|') as counter:
for [n_x, x], [n_y, y], a in samples(self.space,
self.space,
self.space.field):
error = abs((a * x).inner(y) - a * x.inner(y))
if error > self.eps:
counter.fail('x={:25s}, y={:25s}, a={}: error={}'
''.format(n_x, n_y, a, error))
def _identity_of_mult(self):
"""Verify multiplicative neutral element ('one')."""
with FailCounter(
test_name='Verifying identity element of multiplication',
err_msg='error = dist(1 * x, x)',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
correct = _approx_equal(1 * x, x, self.tol)
if not correct:
counter.fail('failed with x={:25s}'.format(n_x))
def _inner_linear_sum(self):
print('\nLinearity sum, (x+y, z) = (x, z) + (y, z)')
with FailCounter('error = |(x+y, z) - ((x, z)+(y, z))|') as counter:
for [n_x, x], [n_y, y], [n_z, z] in samples(self.space,
self.space,
self.space):
error = abs((x + y).inner(z) - (x.inner(z) + y.inner(z)))
if error > self.eps:
counter.fail('x={:25s}, y={:25s}, z={:25s}: error={}'
''.format(n_x, n_y, n_z, error))
def _multiply_zero(self):
print('\nMultiplication by zero, x * 0 = 0')
zero = self.space.zero()
with FailCounter('error = ||x*0||') as counter:
for [n_x, x] in samples(self.space):
error = (zero * x).norm()
if error > self.eps:
counter.fail('x={:25s},: error={}'
''.format(n_x, error))
def _multiply_distributive_scalar(self):
print('\nMultiplication distributive wrt scal, a * (x + y) = '
'a * x + a * y')
with FailCounter() as counter:
for [n_x, x], [n_y, y], a in samples(self.space,
self.space,
self.space.field):
ok = _apprimately_equal(a * (x + y), a * x + a * y, self.eps)
if not ok:
counter.fail('failed with x={:25s} y={:25s} a={}'
''.format(n_x, n_y, a))
def _multiply_distributive_vec(self):
print('\nMultiplication distributive wrt vec, x * (y + z) = '
'x * y + x * z')
with FailCounter() as counter:
for [n_x, x], [n_y, y], [n_z, z] in samples(self.space,
self.space,
self.space):
ok = _apprimately_equal(x * (y + z), x * y + x * z, self.eps)
if not ok:
counter.fail('failed with x={:25s} y={:25s} z={:25s}'
''.format(n_x, n_y, n_z))
def _distributivity_of_mult_scalar(self):
print('\nDistributivity of multiplication wrt scalar add, '
'(a + b) * x = a * x + b * x')
with FailCounter() as counter:
for [n_x, x], a, b in samples(self.space,
self.space.field,
self.space.field):
ok = _apprimately_equal((a + b) * x, a * x + b * x, self.eps)
if not ok:
counter.fail('failed with x={:25s}, a={}, b={}'
''.format(n_x, a, b))
def _distributivity_of_mult_vector(self):
print('\nDistributivity of multiplication wrt vector add, '
'a * (x + y) = a * x + a * y')
with FailCounter() as counter:
for [n_x, x], [n_y, y], a in samples(self.space,
self.space,
self.space.field):
ok = _apprimately_equal(a * (x + y), a * x + a * y, self.eps)
if not ok:
counter.fail('failed with x={:25s}, y={:25s}, a={}'
''.format(n_x, n_y, a))
def _dist_symmetric(self):
"""Verify symmetry of the distance."""
with fail_counter(test_name='Verifying symmetry of the distance',
err_msg='error = |d(x, y) - d(y, x)|',
logger=self.log) as counter:
for [n_x, x], [n_y, y] in samples(self.space, self.space):
dist_1 = x.dist(y)
dist_2 = y.dist(x)
error = abs(dist_1 - dist_2)
if error > self.tol:
counter.fail('x={:25s}, y={:25s}: error={}'
''.format(n_x, n_y, error))
def _multiply_distributive_scalar(self):
"""Verify distributivity of scalar multiplication."""
with fail_counter(
test_name='Verifying distributivity of vector multiplication '
'under scalar multiplication',
err_msg='error = dist(a * (x + y), a * x + a * y)',
logger=self.log) as counter:
for [n_x, x], [n_y, y], [_, a] in samples(self.space, self.space,
self.space.field):
correct = _approx_equal(a * (x + y), a * x + a * y, self.tol)
if not correct:
counter.fail('failed with x={:25s} y={:25s} a={}'
''.format(n_x, n_y, a))
def _multiply_associative(self):
"""Verify associativity of vector multiplication."""
with fail_counter(
test_name='Verifying associativity of vector multiplication',
err_msg='error = dist(x * (y * z), (x * y) * z)',
logger=self.log) as counter:
for [n_x, x], [n_y, y], [n_z,
z] in samples(self.space, self.space,
self.space):
correct = _approx_equal(x * (y * z), (x * y) * z, self.tol)
if not correct:
counter.fail('failed with x={:25s} y={:25s} z={:25s}'
''.format(n_x, n_y, n_z))
def _inner_linear_scalar(self):
"""Verify homogeneity of the inner product in the first argument."""
with fail_counter(
test_name='Verifying homogeneity of the inner product in the '
'first argument',
err_msg='error = |<a*x, y> - a*<x, y>|',
logger=self.log) as counter:
for [n_x, x], [n_y, y], [_, a] in samples(self.space, self.space,
self.space.field):
error = abs((a * x).inner(y) - a * x.inner(y))
if error > self.tol:
counter.fail('x={:25s}, y={:25s}, a={}: error={}'
''.format(n_x, n_y, a, error))
def _commutativity_of_scalar_mult(self):
"""Verify scalar multiplication commutativity."""
with FailCounter(
test_name='Verifying commutativity of scalar multiplication',
err_msg='error = dist(a * (b * x), (a * b) * x)',
logger=self.log) as counter:
for [n_x, x], [_, a], [_,
b] in samples(self.space, self.space.field,
self.space.field):
correct = _approx_equal(a * (b * x), (a * b) * x, self.tol)
if not correct:
counter.fail('failed with x={:25s}, a={}, b={}'
''.format(n_x, a, b))
def _norm_subadditive(self):
"""Check subadditivity of the norm."""
name = 'Sub-additivity, ||x+y|| <= ||x|| + ||y||'
with FailCounter(name, 'error = ||x+y|| - ||x|| + ||y||') as counter:
for [n_x, x], [n_y, y] in samples(self.space, self.space):
norm_x = x.norm()
norm_y = y.norm()
norm_xy = (x + y).norm()
error = norm_xy - norm_x - norm_y
if error > 0:
counter.fail('x={:25s} y={:25s}: error={}'
''.format(n_x, n_y, error))
def _dist_positivity(self):
"""Verify nonnegativity of the distance."""
with FailCounter(test_name='Verifying nonnegativity of the distance',
logger=self.log) as counter:
for [n_x, x], [n_y, y] in samples(self.space, self.space):
dist = x.dist(y)
if n_x == n_y and dist != 0:
counter.fail('d(x, x) != 0.0, x={:25s}: dist={}'
''.format(n_x, dist))
elif n_x != n_y and dist <= 0:
counter.fail('d(x, y) <= 0, x={:25s} y={:25s}: dist={}'
''.format(n_x, n_y, dist))
def _norm_positive(self):
"""Check nonnegativity of the norm."""
name = 'Positivity, ||x|| >= 0'
with FailCounter(name) as counter:
for [n_x, x] in samples(self.space):
norm = x.norm()
if n_x == 'Zero' and norm != 0:
counter.fail('||0|| != 0.0, x={:25s}: ||x||={}'
''.format(n_x, norm))
elif n_x != 'Zero' and norm <= 0:
counter.fail('||x|| <= 0, x={:25s}: ||x||={}'
''.format(n_x, norm))
def _distributivity_of_mult_scalar(self):
"""Verify scalar multiplication distributivity wrt scalar addition."""
with FailCounter(
test_name='Verifying distributivity of scalar multiplication '
'under scalar addition',
err_msg='error = dist((a + b) * x, a * x + b * x)',
logger=self.log) as counter:
for [n_x, x], [_, a], [_, b] in samples(self.space,
self.space.field,
self.space.field):
correct = _approx_equal((a + b) * x, a * x + b * x, self.tol)
if not correct:
counter.fail('failed with x={:25s}, a={}, b={}'
''.format(n_x, a, b))
def _inner_linear_sum(self):
"""Verify distributivity of the inner product in the first argument."""
with FailCounter(
test_name='Verifying distributivity of the inner product'
'in the first argument',
err_msg='error = |<x+y, z> - (<x, z> + <y, z>)|',
logger=self.log) as counter:
for [n_x, x], [n_y, y], [n_z, z] in samples(self.space,
self.space,
self.space):
error = abs((x + y).inner(z) - (x.inner(z) + y.inner(z)))
if error > self.tol:
counter.fail('x={:25s}, y={:25s}, z={:25s}: error={}'
''.format(n_x, n_y, n_z, error))
def _multiply_distributive_vector(self):
"""Verify distributivity of vector multiplication."""
with FailCounter(
test_name='Verifying distributivity of vector multiplication '
'under vector multiplication',
err_msg='error = dist(x * (y + z), x * y + x * z)',
logger=self.log) as counter:
for [n_x, x], [n_y, y], [n_z, z] in samples(self.space,
self.space,
self.space):
correct = _approx_equal(x * (y + z), x * y + x * z, self.tol)
if not correct:
counter.fail('failed with x={:25s} y={:25s} z={:25s}'
''.format(n_x, n_y, n_z))
def _inverse_element_of_addition(self):
"""Verify additive inverse."""
try:
zero = self.space.zero()
except (AttributeError, NotImplementedError):
print('*** SPACE HAS NO ZERO VECTOR ***')
return
with FailCounter(test_name='Verifying inverse element of addition',
err_msg='error = dist(x + (-x), 0)',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
correct = _approx_equal(x + (-x), zero, self.tol)
if not correct:
counter.fail('failed with x={:25s}'.format(n_x))
def _norm_subadditive(self):
"""Verify subadditivity of the norm."""
with FailCounter(test_name='Verifying sub-additivity of the norm',
err_msg='error = max(||x+y|| - (||x|| + ||y||), 0)',
logger=self.log) as counter:
for [n_x, x], [n_y, y] in samples(self.space, self.space):
norm_x = x.norm()
norm_y = y.norm()
norm_xy = (x + y).norm()
error = norm_xy - norm_x - norm_y
if error > 0:
counter.fail('x={:25s} y={:25s}: error={}'
''.format(n_x, n_y, error))
def _multiply_zero(self):
"""Verify that vector multiplication with zero is zero."""
try:
zero = self.space.zero()
except NotImplementedError:
print('*** SPACE HAS NO ZERO VECTOR ***')
return
with FailCounter(test_name='Verifying vector multiplication with zero',
err_msg='error = ||x * 0||',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
error = (zero * x).norm()
if error > self.tol:
counter.fail('x={:25s},: error={}' ''.format(n_x, error))
def _norm_positive(self):
"""Verify positive definiteness of the norm."""
with FailCounter(
test_name='Verifying positive definiteness of the norm',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
norm = x.norm()
if n_x == 'Zero' and norm != 0:
counter.fail('||0|| != 0.0, x={:25s}: ||x||={}'
''.format(n_x, norm))
elif n_x != 'Zero' and norm <= 0:
counter.fail('||x|| <= 0, x={:25s}: ||x||={}'
''.format(n_x, norm))
def _identity_of_addition(self):
"""Verify additive neutral element ('zero')."""
try:
zero = self.space.zero()
except (AttributeError, NotImplementedError):
print('*** SPACE HAS NO ZERO VECTOR ***')
return
with fail_counter(test_name='Verifying identity element of addition',
err_msg='error = dist(x + 0, x)',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
correct = _approx_equal(x + zero, x, self.tol)
if not correct:
counter.fail('failed with x={:25s}'.format(n_x))
def element_set_zero(self):
"""Verify `LinearSpaceElement.set_zero`."""
try:
zero = self.space.zero()
except NotImplementedError:
print('*** SPACE HAS NO ZERO VECTOR ***')
return
with FailCounter(
test_name='Verify behavior of `LinearSpaceElement.set_zero`',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
x.set_zero()
correct = _approx_equal(x, zero, self.tol)
if not correct:
counter.fail('failed with x={:25s}' ''.format(n_x))
def _norm_inner_compatible(self):
"""Check compatibility of norm and inner product."""
name = 'Inner compatibility, ||x||^2 = (x, x)'
try:
zero = self.space.zero()
zero.inner(zero)
except NotImplementedError:
print('Space is not a inner product space')
return
with FailCounter(name, 'error = | ||x||^2 = (x, x) |') as counter:
for [n_x, x] in samples(self.space):
error = abs(x.norm()**2 - x.inner(x))
if error > self.eps:
counter.fail('x={:25s}: error={}' ''.format(n_x, error))
def _dist_norm_compatible(self):
"""Check compatibility of distance and norm."""
name = 'Norm compatibility, d(x, y) = ||x-y||'
try:
self.space.zero().norm()
except NotImplementedError:
print('Space is not normed')
return
with FailCounter(name, 'error = |d(x, y) - ||x-y|| |') as counter:
for [n_x, x], [n_y, y] in samples(self.space, self.space):
error = abs(x.dist(y) - (x - y).norm())
if error > self.eps:
counter.fail('x={:25s}, y={:25s}: error={}'
''.format(n_x, n_y, error))
def _dist_subadditive(self):
"""Check subadditivity of the distance."""
name = 'Sub-additivity, d(x, y) = d(y, x)'
with FailCounter(name,
'error = d(x,z) - (d(x, y) + d(y, z))') as counter:
for [n_x, x], [n_y, y], [n_z,
z] in samples(self.space, self.space,
self.space):
dxz = x.dist(z)
dxy = x.dist(y)
dyz = y.dist(z)
error = dxz - (dxy + dyz)
if error > self.eps:
counter.fail('x={:25s}, y={:25s}, z={:25s}: error={}'
''.format(n_x, n_y, n_z, error))
def _dist_subtransitive(self):
"""Verify sub-transitivity of the distance."""
with FailCounter(
test_name='Verifying sub-additivity of the distance',
err_msg='error = max(d(x,z) - (d(x, y) + d(y, z)), 0)',
logger=self.log) as counter:
for [n_x, x], [n_y, y], [n_z, z] in samples(self.space,
self.space,
self.space):
dxz = x.dist(z)
dxy = x.dist(y)
dyz = y.dist(z)
error = dxz - (dxy + dyz)
if error > self.tol:
counter.fail('x={:25s}, y={:25s}, z={:25s}: error={}'
''.format(n_x, n_y, n_z, error))
def _inner_positive(self):
"""Check positive definiteness of the inner product."""
name = 'Positivity, (x, x) >= 0'
with FailCounter(name) as counter:
for [n_x, x] in samples(self.space):
inner = x.inner(x)
if abs(inner.imag) > self.eps:
counter.fail('(x, x).imag != 0, x={:25s}' ''.format(n_x))
if n_x == 'Zero' and inner.real != 0:
counter.fail('(0, 0) != 0.0, x={:25s}: (0, 0)={}'
''.format(n_x, inner))
elif n_x != 'Zero' and inner.real <= 0:
counter.fail('(x, x) <= 0, x={:25s}: (x, x)={}'
''.format(n_x, inner))
def _scale_invariance(self):
"""Verify ``A(c*x) = c * A(x)``."""
with FailCounter(
test_name='Verifying homogeneity under scalar multiplication',
err_msg='error = ||A(c*x)-c*A(x)|| / |c| ||A|| ||x||',
logger=self.log) as counter:
for [name_x, x], [_, scale] in samples(self.operator.domain,
self.operator.domain.field):
opx = self.operator(x)
scaled_opx = self.operator(scale * x)
denom = self.operator_norm * scale * x.norm()
error = (0 if denom == 0
else (scaled_opx - opx * scale).norm() / denom)
if error > self.tol:
counter.fail('x={:25s} scale={:7.2f} error={:6.5f}'
''.format(name_x, scale, error))
def _scale_invariance(self):
name = "Calculating invariance under scaling"
# Test scaling
with FailCounter(name, 'error = ||A(c*x)-c*A(x)|| / '
'|c| ||A|| ||x||') as counter:
for [name_x, x], [_, scale] in samples(self.operator.domain,
self.operator.domain.field):
opx = self.operator(x)
scaled_opx = self.operator(scale * x)
denom = self.operator_norm * scale * x.norm()
error = (0 if denom == 0
else (scaled_opx - opx * scale).norm() / denom)
if error > 0.00001:
counter.fail('x={:25s} scale={:7.2f} error={:6.5f}'
''.format(name_x, scale, error))
def _derivative_convergence(self):
"""Verify that the derivative is a first-order approximation.
The code verifies if
``||A(x+c*p) - A(x) - A'(x)(c*p)|| / c = o(c)``
for ``c --> 0``.
"""
with FailCounter(
test_name='Verifying that derivative is a first-order '
'approximation',
err_msg="error = inf_c ||A(x+c*p)-A(x)-A'(x)(c*p)|| / c",
logger=self.log) as counter:
for [name_x, x], [name_dx, dx] in samples(self.operator.domain,
self.operator.domain):
# Precompute some values
deriv = self.operator.derivative(x)
derivdx = deriv(dx)
opx = self.operator(x)
c = 1e-4 # initial step
derivative_ok = False
minerror = float('inf')
while c > 1e-14:
exact_step = self.operator(x + dx * c) - opx
expected_step = c * derivdx
err = (exact_step - expected_step).norm() / c
# Need to be slightly more generous here due to possible
# numerical instabilities.
# TODO: perform more tests to find a good threshold here.
if err < 10 * self.tol:
derivative_ok = True
break
else:
minerror = min(minerror, err)
c /= 10.0
if not derivative_ok:
counter.fail('x={:15s} p={:15s}, error={}'
''.format(name_x, name_dx, minerror))
def _dist_norm_compatible(self):
"""Verify compatibility of distance and norm."""
try:
self.space.zero().norm()
except NotImplementedError:
self.log('Space has no norm')
return
with FailCounter(
test_name='Verifying compatibility of distance and norm',
err_msg='error = |d(x, y) - ||x-y|| |',
logger=self.log) as counter:
for [n_x, x], [n_y, y] in samples(self.space, self.space):
error = abs(x.dist(y) - (x - y).norm())
if error > self.tol:
counter.fail('x={:25s}, y={:25s}: error={}'
''.format(n_x, n_y, error))
def contains(self):
"""Verify `LinearSpace.__contains__`."""
with FailCounter(test_name='Verify behavior of `obj in space`',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
if x not in self.space:
counter.fail('x not in space, with x={}' ''.format(n_x))
if x not in self.space:
counter.fail('not x in space, with x={}' ''.format(n_x))
for obj in [[1, 2], list(), tuple(), dict(), 5.0]:
if obj in self.space:
counter.fail('obj in space, with obj={}' ''.format(obj))
if not obj not in self.space:
counter.fail('not obj not in space, with obj={}'
''.format(obj))
def element_copy(self):
"""Verify `LinearSpaceElement.copy`."""
with FailCounter(
test_name='Verify behavior of `LinearSpaceElement.copy`',
logger=self.log) as counter:
for [n_x, x] in samples(self.space):
# equal after copy
y = x.copy()
correct = _approx_equal(x, y, self.tol)
if not correct:
counter.fail('failed with x={:s5s}' ''.format(n_x))
# modify y, x stays the same
y *= 2.0
correct = n_x == 'Zero' or not _approx_equal(x, y, self.tol)
if not correct:
counter.fail('modified y, x changed with x={:25s}'
''.format(n_x))
def vector_copy(self):
"""Verify `LinearSpaceVector.copy`."""
name = 'Vector.copy()'
with FailCounter(name) as counter:
for [n_x, x] in samples(self.space):
# equal after copy
y = x.copy()
correct = _approx_equal(x, y, self.eps)
if not correct:
counter.fail('failed with x={:s5s}' ''.format(n_x))
# modify y, x stays the same
y *= 2.0
correct = n_x == 'Zero' or not _approx_equal(x, y, self.eps)
if not correct:
counter.fail('modified y, x changed with x={:25s}'
''.format(n_x))
def _addition_invariance(self):
name = "Calculating invariance under addition"
# Test addition
with FailCounter(name, 'error = ||A(x+y) - A(x) - A(y)|| / '
'||A||(||x|| + ||y||)') as counter:
for [name_x, x], [name_y, y] in samples(self.operator.domain,
self.operator.domain):
opx = self.operator(x)
opy = self.operator(y)
opxy = self.operator(x + y)
denom = self.operator_norm * (x.norm() + y.norm())
error = (0 if denom == 0
else (opxy - opx - opy).norm() / denom)
if error > 0.00001:
counter.fail('x={:25s} y={:25s} error={:6.5f}'
''.format(name_x, name_y, error))
