def _test_match(values):
values = np.array(values, dtype=float)
ix = list(o.find_nearest_matches(values, values))
assert [values[i] for i in ix] == list(values)
values2 = values + 0.1
ix2 = list(o.find_nearest_matches(values2, values))
assert [values2[i] for i in ix] == [values2[i] for i in ix2]
values2 = values - 0.1
ix2 = list(o.find_nearest_matches(values2, values))
assert [values2[i] for i in ix] == [values2[i] for i in ix2]
def _test_match(values):
values = array32(values)
ix = list(o.find_nearest_matches(values, values))
assert [values[i] for i in ix] == list(values)
values2 = values + 0.1
ix2 = list(o.find_nearest_matches(values2, values))
assert [values2[i] for i in ix] == [values2[i] for i in ix2]
values2 = values - 0.1
ix2 = list(o.find_nearest_matches(values2, values))
assert [values2[i] for i in ix] == [values2[i] for i in ix2]
def _test_match(values):
values = np.array(values, dtype=float)
ix = list(o.find_nearest_matches(values, values))
assert [values[i] for i in ix] == list(values)
values2 = values + 0.1
ix2 = list(o.find_nearest_matches(values2, values))
assert [values2[i] for i in ix] == [values2[i] for i in ix2]
values2 = values - 0.1
ix2 = list(o.find_nearest_matches(values2, values))
assert [values2[i] for i in ix] == [values2[i] for i in ix2]
def test_find_neared_matches():
ix = o.find_nearest_matches(np.arange(4.0), np.arange(2.0))
assert list(ix) == [0, 1]
ix = o.find_nearest_matches(np.arange(2.0), np.arange(4.0))
assert list(ix) == [0, 1, 1, 1]
# unsorted with duplicates
_test_match([2, 7, 0, 5, 3, 7, 2, 1, 3, 9])
# unsorted without duplicates
_test_match([7, 0, 5, 2, 1, 3, 9])
# sorted
_test_match([1, 2, 5, 6, 9, 11])
# reverse sorted
_test_match([11, 9, 6, 5, 2, 1, 0])
# one element basis
_test_match([2])
# two element basis const
_test_match([2, 2])
# two element basis asc
_test_match([2, 3])
# two element basis desc
_test_match([3, 2])
# constant sequence
_test_match([2, 2, 2])
# nearly constant sequence 1
_test_match([3, 2, 2, 2])
# nearly constant sequence 2
_test_match([3, 3, 3, 2])
# nearly constant sequence 3
_test_match([1, 2, 2, 2])
# nearly constant sequence 4
_test_match([1, 1, 1, 2])
def test_find_neared_matches():
ix = o.find_nearest_matches(arange32(4.0), arange32(2.0))
assert list(ix) == [0, 1]
ix = o.find_nearest_matches(arange32(2.0), arange32(4.0))
assert list(ix) == [0, 1, 1, 1]
# unsorted with duplicates
_test_match([2, 7, 0, 5, 3, 7, 2, 1, 3, 9])
# unsorted without duplicates
_test_match([7, 0, 5, 2, 1, 3, 9])
# sorted
_test_match([1, 2, 5, 6, 9, 11])
# reverse sorted
_test_match([11, 9, 6, 5, 2, 1, 0])
# one element basis
_test_match([2])
# two element basis const
_test_match([2, 2])
# two element basis asc
_test_match([2, 3])
# two element basis desc
_test_match([3, 2])
# constant sequence
_test_match([2, 2, 2])
# nearly constant sequence 1
_test_match([3, 2, 2, 2])
# nearly constant sequence 2
_test_match([3, 3, 3, 2])
# nearly constant sequence 3
_test_match([1, 2, 2, 2])
# nearly constant sequence 4
_test_match([1, 1, 1, 2])
def _test_find_neared_matches_fuzzy():
for l in range(1, 100):
for i in range(100):
basis = np.random.random((l, ))
basis.sort()
search = np.random.random((l, ))
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
basis = basis[::-1]
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
search = basis
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
basis = basis[::-1]
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
# introduct dupplicates
basis = np.hstack((basis, basis))
basis.sort()
search = np.random.random((l, ))
search = basis
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
basis = basis[::-1]
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
# introduct more dupplicates
basis = np.hstack((basis, basis))
basis.sort()
search = np.random.random((l, ))
search = basis
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
basis = basis[::-1]
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
def _test_find_neared_matches_fuzzy():
for l in range(1, 100):
for i in range(100):
basis = np.random.random((l,))
basis.sort()
search = np.random.random((l,))
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
basis = basis[::-1]
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
search = basis
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
basis = basis[::-1]
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
# introduct dupplicates
basis = np.hstack((basis, basis))
basis.sort()
search = np.random.random((l,))
search = basis
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
basis = basis[::-1]
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
# introduct more dupplicates
basis = np.hstack((basis, basis))
basis.sort()
search = np.random.random((l,))
search = basis
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
basis = basis[::-1]
tobe = o.find_nearest_matches(basis, search, 0)
optim = o.find_nearest_matches(basis, search)
assert np.all(tobe == optim)
