def test_compare_two_dictionaries_where_values_are_arrays_four():
# The dictionaries are equal
d1 = {0: np.array([1, 2, 3]), 1: np.array([4, 5, 6])}
d2 = {0: np.array([1, 2, 3]), 1: np.array([4, 5, 6])}
are_equal = compare_methods.compare_two_dictionaries_where_values_are_arrays(d1, d2)
assert are_equal
def test_compare_two_dictionaries_where_values_are_arrays_one():
# Dictionaries have different lengths
d1 = {0: np.array([1, 2, 3]), 1: np.array([4, 5, 6])}
d2 = {0: np.array([1, 2, 3])}
are_equal = compare_methods.compare_two_dictionaries_where_values_are_arrays(d1, d2)
assert are_equal is False
def test_compare_two_dictionaries_where_values_are_arrays_three():
# The values are in different orders
d1 = {0: np.array([1, 2, 3])}
d2 = {1: np.array([1, 3, 2])}
are_equal = compare_methods.compare_two_dictionaries_where_values_are_arrays(d1, d2)
assert are_equal is False
def test_get_indices_leading_to_endpoints():
endpoints = np.array([7, 7, 7, 5, 5, 5, 7, 7, 7, 22, 5, 5, 13, 13, 13, 22,
22, 23, 13, 13, 13, 22, 22, 23, 13, 13, 13, 28, 28, 29])
# unique_endpoints = np.array([5, 7, 13, 22, 23, 28, 29])
result_indices_to_endpoints = {5: np.array([3, 4, 5, 10, 11]),
7: np.array([0, 1, 2, 6, 7, 8]),
13: np.array([12, 13, 14, 18, 19, 20, 24, 25, 26]),
22: np.array([9, 15, 16, 21, 22]),
23: np.array([17, 23]),
28: np.array([27, 28]),
29: np.array([29])}
indices_to_endpoints = trap_analysis.get_indices_leading_to_endpoints(endpoints)
for minimum in indices_to_endpoints:
indices_to_endpoints[minimum] = np.sort(indices_to_endpoints[minimum])
are_equal = compare_methods.compare_two_dictionaries_where_values_are_arrays(indices_to_endpoints,
result_indices_to_endpoints)
assert are_equal
