def test_toy_create_difference_matrix_direct_neighbor_without_censoring(
toy_data):
_, y = toy_data
status = numpy.ones(y.shape, dtype=bool)
mat = create_difference_matrix(status.astype(numpy.uint8),
y["time"],
kind="next")
expected = numpy.zeros((5, 6), dtype=numpy.int8)
expected[0, 0] = -1
expected[0, 1] = 1
expected[1, 1] = -1
expected[1, 2] = 1
expected[2, 2] = -1
expected[2, 3] = 1
expected[3, 3] = -1
expected[3, 4] = 1
expected[4, 4] = -1
expected[4, 5] = 1
assert_array_equal(expected, mat.toarray())
# should return first-order differences of y["time"]
actual_diff = mat.dot(y["time"])
expected_diff = (y["time"][1:] - y["time"][:-1])
assert_array_almost_equal(expected_diff, actual_diff)
def test_toy_create_difference_matrix_direct_neighbor_without_censoring_shuffled(
toy_data):
_, y = toy_data
status = numpy.ones(y.shape, dtype=bool)
order = [3, 2, 5, 0, 1, 4] # = [ 20. 11. 70. 3. 6. 37.]
time = y["time"][order]
mat = create_difference_matrix(status.astype(numpy.uint8),
time,
kind="next")
expected = numpy.zeros((5, 6), dtype=numpy.int8)
expected[0, 3] = -1
expected[0, 4] = 1
expected[1, 4] = -1
expected[1, 1] = 1
expected[2, 1] = -1
expected[2, 0] = 1
expected[3, 0] = -1
expected[3, 5] = 1
expected[4, 5] = -1
expected[4, 2] = 1
assert_array_equal(expected, mat.toarray())
# should return first-order differences of y["time"]
actual_diff = mat.dot(time)
expected_diff = (y["time"][1:] - y["time"][:-1])
assert_array_almost_equal(expected_diff, actual_diff)
def test_toy_create_difference_matrix_full_censored(toy_data):
_, y = toy_data
mat = create_difference_matrix(y["status"].astype(numpy.uint8),
y["time"],
kind="all")
expected = numpy.zeros((11, 6), dtype=numpy.int8)
expected[0, 1] = 1
expected[0, 0] = -1
expected[1:3, 2] = 1
expected[1, 0] = -1
expected[2, 1] = -1
expected[3:5, 3] = 1
expected[3, 0] = -1
expected[4, 1] = -1
expected[5:8, 4] = 1
expected[5, 0] = -1
expected[6, 1] = -1
expected[7, 3] = -1
expected[8:12, 5] = 1
expected[8, 0] = -1
expected[9, 1] = -1
expected[10, 3] = -1
assert_array_equal(expected, mat.toarray())
def test_toy_create_difference_matrix_full(toy_data):
_, y = toy_data
status = numpy.repeat(True, len(y))
mat = create_difference_matrix(status.astype(numpy.uint8),
y["time"],
kind="all")
expected = numpy.zeros((15, 6), dtype=numpy.int8)
expected[0, 1] = 1
expected[0, 0] = -1
expected[1:3, 2] = 1
expected[1, 0] = -1
expected[2, 1] = -1
expected[3:6, 3] = 1
expected[3, 0] = -1
expected[4, 1] = -1
expected[5, 2] = -1
expected[6:10, 4] = 1
expected[6, 0] = -1
expected[7, 1] = -1
expected[8, 2] = -1
expected[9, 3] = -1
expected[10:15, 5] = 1
expected[10, 0] = -1
expected[11, 1] = -1
expected[12, 2] = -1
expected[13, 3] = -1
expected[14, 4] = -1
assert_array_equal(expected, mat.toarray())
def test_toy_create_difference_matrix_nearest_neighbor_censored(self):
mat = create_difference_matrix(self.y["status"].astype(numpy.uint8), self.y["time"], kind="nearest")
expected = numpy.zeros((5, 6), dtype=numpy.int8)
expected[0, 0] = -1
expected[0, 1] = 1
expected[1, 1] = -1
expected[1, 2] = 1
expected[2, 1] = -1
expected[2, 3] = 1
expected[3, 3] = -1
expected[3, 4] = 1
expected[4, 3] = -1
expected[4, 5] = 1
assert_array_equal(expected, mat.toarray())
def test_toy_create_difference_matrix_nearest_neighbor(self):
status = numpy.repeat(True, len(self.y))
mat = create_difference_matrix(status.astype(numpy.uint8), self.y["time"], kind="nearest")
expected = numpy.zeros((5, 6), dtype=numpy.int8)
expected[0, 0] = -1
expected[0, 1] = 1
expected[1, 1] = -1
expected[1, 2] = 1
expected[2, 2] = -1
expected[2, 3] = 1
expected[3, 3] = -1
expected[3, 4] = 1
expected[4, 4] = -1
expected[4, 5] = 1
assert_array_equal(expected, mat.toarray())
def test_toy_create_difference_matrix_direct_neighbor_with_censoring(self):
mat = create_difference_matrix(self.y["status"].astype(numpy.uint8), self.y["time"], kind="next")
expected = numpy.zeros((3, 6), dtype=numpy.int8)
expected[0, 0] = -1
expected[0, 1] = 1
expected[1, 1] = -1
expected[1, 2] = 1
expected[2, 3] = -1
expected[2, 4] = 1
assert_array_equal(expected, mat.toarray())
# should return first-order differences of self.y["time"]
actual_diff = mat.dot(self.y["time"])
comparable_pairs = numpy.array([True, True, False, True, False])
expected_diff = (self.y["time"][1:] - self.y["time"][:-1])[comparable_pairs]
assert_array_almost_equal(expected_diff, actual_diff)
