def test_process_column_complex_ranges(self):
# Overlapping ranges and contexts consisting of multiple ranges
query_ranges = [
range(0, 10),
range(1, 5),
range(1, 2),
range(4, 5), [range(1, 2), range(3, 4),
range(7, 9)]
]
series_ranges = [
range(0, 2),
range(1, 3),
range(2, 4),
range(3, 6),
range(4, 8),
range(4, 10), [range(0, 3),
range(3, 5),
range(13, 15)]
]
correct, correct_qi, correct_si = self.bruteforce_cdm(
self.dist_matrix, query_ranges, series_ranges)
cdm = ContextualMatrixProfile(
GeneralStaticManager(series_ranges, query_ranges))
self.mock_initialise(cdm)
for column in range(0, self.dist_matrix.shape[1]):
cdm.process_column(column,
np.atleast_2d(self.dist_matrix[:, column]))
npt.assert_allclose(cdm.distance_matrix, correct)
npt.assert_equal(cdm.match_index_query, correct_qi)
npt.assert_equal(cdm.match_index_series, correct_si)
def test_process_diagonal_partial_calculation(self):
# Ranges selected so that the diagonals have a mix of the number of numbers that are filled in
query_ranges = [
range(0, 2),
range(2, 5),
range(7, 8),
range(8, 9),
range(9, 10)
]
series_ranges = [range(0, 2), range(2, 4), range(4, 10), range(13, 14)]
part_dist_matrix = np.full_like(self.dist_matrix, np.inf)
cdm = ContextualMatrixProfile(
GeneralStaticManager(series_ranges, query_ranges))
self.mock_initialise(cdm)
for diag in range(-8, self.dist_matrix.shape[1], 4):
diag_ind = diag_indices_of(self.dist_matrix, diag)
cdm.process_diagonal(diag,
np.atleast_2d(self.dist_matrix[diag_ind]))
part_dist_matrix[diag_ind] = self.dist_matrix[diag_ind]
correct, correct_qi, correct_si = self.bruteforce_cdm(
part_dist_matrix, query_ranges, series_ranges)
npt.assert_allclose(cdm.distance_matrix, correct)
npt.assert_equal(cdm.match_index_query, correct_qi)
npt.assert_equal(cdm.match_index_series, correct_si)
def test_process_column_context_falls_outside_distancematrix(self):
query_ranges = [range(0, 8), range(8, 16), range(20, 30)]
series_ranges = [range(0, 10), range(10, 20), range(30, 40)]
correct, correct_qi, correct_si = self.bruteforce_cdm(
self.dist_matrix, query_ranges, series_ranges)
cdm = ContextualMatrixProfile(
GeneralStaticManager(series_ranges, query_ranges))
self.mock_initialise(cdm)
for column in range(0, self.dist_matrix.shape[1]):
cdm.process_column(column,
np.atleast_2d(self.dist_matrix[:, column]))
npt.assert_allclose(cdm.distance_matrix, correct)
npt.assert_equal(cdm.match_index_query, correct_qi)
npt.assert_equal(cdm.match_index_series, correct_si)
def test_process_diagonal_context_goes_beyond_distancematrix(self):
query_ranges = [range(0, 8), range(8, 16)]
series_ranges = [range(0, 10), range(10, 20)]
correct, correct_qi, correct_si = self.bruteforce_cdm(
self.dist_matrix, query_ranges, series_ranges)
cdm = ContextualMatrixProfile(
GeneralStaticManager(series_ranges, query_ranges))
self.mock_initialise(cdm)
for diag in range(-self.dist_matrix.shape[0] + 1,
self.dist_matrix.shape[1]):
diag_ind = diag_indices_of(self.dist_matrix, diag)
cdm.process_diagonal(diag,
np.atleast_2d(self.dist_matrix[diag_ind]))
npt.assert_allclose(cdm.distance_matrix, correct)
npt.assert_equal(cdm.match_index_query, correct_qi)
npt.assert_equal(cdm.match_index_series, correct_si)
def test_process_column_partial_calculation(self):
# Ranges selected so that the contexts will receive 0, 1, 2 or 3 columns
query_ranges = [range(0, 2), range(2, 5), range(7, 10)]
series_ranges = [range(0, 2), range(2, 4), range(4, 6), range(9, 14)]
part_dist_matrix = np.full_like(self.dist_matrix, np.inf)
cdm = ContextualMatrixProfile(
GeneralStaticManager(series_ranges, query_ranges))
self.mock_initialise(cdm)
for column in [2, 3, 4, 5, 10, 11, 12]:
cdm.process_column(column,
np.atleast_2d(self.dist_matrix[:, column]))
part_dist_matrix[:, column] = self.dist_matrix[:, column]
correct, correct_qi, correct_si = self.bruteforce_cdm(
part_dist_matrix, query_ranges, series_ranges)
npt.assert_allclose(cdm.distance_matrix, correct)
npt.assert_equal(cdm.match_index_query, correct_qi)
npt.assert_equal(cdm.match_index_series, correct_si)
def test_streaming_process_diagonal(self):
cdm = ContextualMatrixProfile(MockContextManager())
cdm.initialise(1, 4, 6)
v = self.dist_matrix[0:4, 0:6]
cdm.process_diagonal(0, np.atleast_2d(v[diag_indices_of(v, 0)]))
cdm.process_diagonal(2, np.atleast_2d(v[diag_indices_of(v, 2)]))
cdm.process_diagonal(-1, np.atleast_2d(v[diag_indices_of(v, -1)]))
npt.assert_equal(cdm.distance_matrix,
[[3.1, 0.5, 8., np.Inf], [np.Inf, 5.8, 1., np.Inf]])
npt.assert_equal(cdm.match_index_query,
[[2, 0, 2, -1], [-1, 3, 3, -1]])
npt.assert_equal(cdm.match_index_series,
[[1, 2, 4, -1], [-1, 2, 5, -1]])
cdm.shift_series(1)
cdm.shift_query(2)
v = self.dist_matrix[2:6, 1:7]
npt.assert_equal(cdm.distance_matrix,
[[3.1, 0.5, 8., np.Inf], [np.Inf, 5.8, 1., np.Inf]])
npt.assert_equal(cdm.match_index_query,
[[2, 0, 2, -1], [-1, 3, 3, -1]])
npt.assert_equal(cdm.match_index_series,
[[1, 2, 4, -1], [-1, 2, 5, -1]])
cdm.process_diagonal(5, np.atleast_2d(v[diag_indices_of(v, 5)]))
cdm.process_diagonal(1, np.atleast_2d(v[diag_indices_of(v, 1)]))
cdm.process_diagonal(0, np.atleast_2d(v[diag_indices_of(v, 0)]))
cdm.process_diagonal(-3, np.atleast_2d(v[diag_indices_of(v, -3)]))
npt.assert_equal(cdm.distance_matrix,
[[3.1, 0.5, 8., 2.7], [8.1, 5.8, 1., np.Inf]])
npt.assert_equal(cdm.match_index_query, [[2, 0, 2, 2], [5, 3, 3, -1]])
npt.assert_equal(cdm.match_index_series, [[1, 2, 4, 6], [1, 2, 5, -1]])
cdm.shift_series(1)
cdm.shift_query(2)
v = self.dist_matrix[4:8, 2:8]
npt.assert_equal(
cdm.distance_matrix,
[[5.8, 1., np.Inf, np.Inf], [np.Inf, np.Inf, np.Inf, np.Inf]])
npt.assert_equal(cdm.match_index_query,
[[3, 3, -1, -1], [-1, -1, -1, -1]])
npt.assert_equal(cdm.match_index_series,
[[2, 5, -1, -1], [-1, -1, -1, -1]])
cdm.process_diagonal(-2, np.atleast_2d(v[diag_indices_of(v, -2)]))
cdm.process_diagonal(0, np.atleast_2d(v[diag_indices_of(v, 0)]))
cdm.process_diagonal(1, np.atleast_2d(v[diag_indices_of(v, 1)]))
cdm.process_diagonal(2, np.atleast_2d(v[diag_indices_of(v, 2)]))
cdm.process_diagonal(3, np.atleast_2d(v[diag_indices_of(v, 3)]))
cdm.process_diagonal(4, np.atleast_2d(v[diag_indices_of(v, 4)]))
npt.assert_equal(cdm.distance_matrix,
[[1.2, 1., 1.2, np.Inf], [1.2, 3.7, 2.5, np.Inf]])
npt.assert_equal(cdm.match_index_query, [[6, 3, 4, -1], [6, 6, 7, -1]])
npt.assert_equal(cdm.match_index_series,
[[2, 5, 6, -1], [2, 4, 6, -1]])
def test_streaming_process_column(self):
cdm = ContextualMatrixProfile(MockContextManager())
cdm.initialise(1, 4, 6)
cdm.process_column(0, np.atleast_2d(self.dist_matrix[0:4, 0]))
cdm.process_column(2, np.atleast_2d(self.dist_matrix[0:4, 2]))
npt.assert_equal(
cdm.distance_matrix,
[[7.2, 0.5, np.Inf, np.Inf], [5.3, 5.8, np.Inf, np.Inf]])
npt.assert_equal(cdm.match_index_query,
[[2, 0, -1, -1], [3, 3, -1, -1]])
npt.assert_equal(cdm.match_index_series,
[[0, 2, -1, -1], [0, 2, -1, -1]])
cdm.shift_series(1)
cdm.shift_query(2)
npt.assert_equal(
cdm.distance_matrix,
[[7.2, 0.5, np.Inf, np.Inf], [5.3, 5.8, np.Inf, np.Inf]])
npt.assert_equal(cdm.match_index_query,
[[2, 0, -1, -1], [3, 3, -1, -1]])
npt.assert_equal(cdm.match_index_series,
[[0, 2, -1, -1], [0, 2, -1, -1]])
cdm.process_column(0, np.atleast_2d(self.dist_matrix[2:6, 1]))
cdm.process_column(1, np.atleast_2d(self.dist_matrix[2:6, 2]))
cdm.process_column(3, np.atleast_2d(self.dist_matrix[2:6, 4]))
npt.assert_equal(cdm.distance_matrix,
[[3.1, 0.5, 8.0, np.Inf], [4.8, 2.3, 2.1, np.Inf]])
npt.assert_equal(cdm.match_index_query, [[2, 0, 2, -1], [4, 5, 4, -1]])
npt.assert_equal(cdm.match_index_series,
[[1, 2, 4, -1], [1, 2, 4, -1]])
cdm.shift_series(1)
cdm.shift_query(2)
npt.assert_equal(
cdm.distance_matrix,
[[2.3, 2.1, np.Inf, np.Inf], [np.Inf, np.Inf, np.Inf, np.Inf]])
npt.assert_equal(cdm.match_index_query,
[[5, 4, -1, -1], [-1, -1, -1, -1]])
npt.assert_equal(cdm.match_index_series,
[[2, 4, -1, -1], [-1, -1, -1, -1]])
cdm.process_column(0, np.atleast_2d(self.dist_matrix[4:8, 2]))
cdm.process_column(3, np.atleast_2d(self.dist_matrix[4:8, 5]))
cdm.process_column(4, np.atleast_2d(self.dist_matrix[4:8, 6]))
cdm.process_column(5, np.atleast_2d(self.dist_matrix[4:8, 7]))
npt.assert_equal(cdm.distance_matrix,
[[1.2, 2.1, 1.2, np.Inf], [1.2, 7.5, 2.5, np.Inf]])
npt.assert_equal(cdm.match_index_query, [[6, 4, 4, -1], [6, 7, 7, -1]])
npt.assert_equal(cdm.match_index_series,
[[2, 4, 6, -1], [2, 5, 6, -1]])