def test_fullmatch_two_residual(zero, a, b):
if fm is None:
pytest.skip("Failed to load optional dependency %s." % missing)
grid_1 = _fullgrid(zero, a, b, 5)
random = np.array([
(0.3, 0.4),
(-0.33, 12.5),
])
grid = np.vstack((grid_1, random))
parameters = {'min_delta': 0.3, 'max_delta': 3, 'tolerance': 0.1}
matcher = fm.FullMatcher(**parameters)
(matches, unmatched, weak) = matcher.full_match(grid, zero=zero)
print(matches[0])
assert (len(matches) == 1)
assert (len(unmatched) == len(random))
assert (len(weak) == 0)
match1 = matches[0]
assert np.allclose(zero, match1.zero)
assert (np.allclose(a, match1.a) or np.allclose(b, match1.a)
or np.allclose(-a, match1.a) or np.allclose(-b, match1.a))
assert (np.allclose(a, match1.b) or np.allclose(b, match1.b)
or np.allclose(-a, match1.b) or np.allclose(-b, match1.b))
assert (len(match1) == len(grid_1))
assert (np.allclose(match1.calculated_refineds, grid_1))
def test_fastmatch(zero, a, b):
grid = _fullgrid(zero, a, b, 5)
matcher = grm.Matcher()
match = matcher.fastmatch(centers=grid, zero=zero, a=a, b=b)
assert (np.allclose(zero, match.zero))
assert (np.allclose(a, match.a))
assert (np.allclose(b, match.b))
assert (len(match) == len(grid))
assert (np.allclose(match.calculated_refineds, grid))
def test_affinematch(zero, a, b):
grid = _fullgrid(zero, a, b, 5)
indices = grm.get_indices(grid, zero, a, b)
matcher = grm.Matcher()
match = matcher.affinematch(centers=grid, indices=indices)
assert (np.allclose(zero, match.zero))
assert (np.allclose(a, match.a))
assert (np.allclose(b, match.b))
assert (len(match) == len(grid))
assert (np.allclose(match.calculated_refineds, grid))
def test_fullmatch_weak(zero, a, b):
if fm is None:
pytest.skip("Failed to load optional dependency %s." % missing)
grid_1 = _fullgrid(zero, a, b, 7)
random = np.array([
(0.3, 0.5),
])
grid = np.vstack((grid_1, random))
parameters = {
'min_delta': 0.3,
'max_delta': 3,
'tolerance': 0.05,
'min_weight': 0.1
}
values = np.ones(len(grid))
elevations = np.ones(len(grid))
# The minimum weight is 0.1, so this should be ignored
elevations[0] = 0.01
matcher = fm.FullMatcher(**parameters)
(matches, unmatched, weak) = matcher.full_match(centers=grid,
refineds=grid,
peak_values=values,
peak_elevations=elevations,
zero=zero)
assert (len(matches) == 1)
assert (len(unmatched) == len(random))
assert (len(weak) == 1)
# We have kicked out the first point with a low weight
# so we make sure it is gone from the match although it
# would be at the right position
assert (len(matches[0]) == len(grid_1) - 1)
def test_fullmatch_cand(zero, a, b):
if fm is None:
pytest.skip("Failed to load optional dependency %s." % missing)
grid_1 = _fullgrid(zero, a, b, 7)
random = np.array([
(0.3, 0.5),
])
grid = np.vstack((grid_1, random))
parameters = {'min_delta': 0.3, 'max_delta': 3, 'tolerance': 0.05}
matcher = fm.FullMatcher(**parameters)
(matches, unmatched,
weak) = matcher.full_match(centers=grid,
zero=zero,
cand=[a, b, np.array((23, 42))])
# Make sure the odd candidate didn't catch anything
assert (len(matches) == 1)
assert (len(unmatched) == len(random))