def __add__(self, other):
# Deal with the possibility of an empty matrix.
if self._confusion.shape[0] == 0:
return copy.deepcopy(other)
elif other._confusion.shape[0] == 0:
return copy.deepcopy(self)
# First, create the merged labels list, and figure out what columns
# we'll need to insert in the respective matrices.
# Because we've disabled sort by count, _values is already sorted in
# alphabetical order.
i = 0
j = 0
self_cols_to_add = [0 for _ in range(len(self._values) + 1)]
other_cols_to_add = [0 for _ in range(len(other._values) + 1)]
merged_values = []
while i < len(self._values) and j < len(other._values):
if self._values[i] < other._values[j]:
# I have an item other doesn't. Record where to insert it.
merged_values.append(self._values[i])
other_cols_to_add[j] += 1
i += 1
elif self._values[i] > other._values[j]:
# Other has an item I don't. Record where to insert it.
merged_values.append(other._values[j])
self_cols_to_add[i] += 1
j += 1
else:
merged_values.append(self._values[i])
i += 1
j += 1
if i < len(self._values): # still some self values left
merged_values.extend(self._values[i:])
other_cols_to_add[-1] = len(self._values) - i
if j < len(other._values): # still some other values left
merged_values.extend(other._values[j:])
self_cols_to_add[-1] = len(other._values) - j
augmented_self_matrix = add_rows_and_cols_to_matrix(
self._confusion, self_cols_to_add)
augmented_other_matrix = add_rows_and_cols_to_matrix(
other._confusion, other_cols_to_add)
new_matrix = copy.copy(self)
new_matrix._values = merged_values
new_matrix.class_names = merged_values
new_matrix._indices = {val: i for i, val in enumerate(merged_values)}
new_matrix._confusion = augmented_self_matrix + augmented_other_matrix
new_matrix._max_conf = max(self._max_conf, other._max_conf)
new_matrix._total = self._total + other._total
new_matrix._correct = self._correct + other._correct
return new_matrix
def test_interspersed(self):
result = add_rows_and_cols_to_matrix(self.TEST_MATRIX, [0, 2, 1, 0])
correct = np.array([[1, 0, 0, 2, 0, 3], [0] * 6, [0] * 6,
[4, 0, 0, 5, 0, 6], [0] * 6, [7, 0, 0, 8, 0, 9]])
self.assertArraysEqual(correct, result)
def test_prepend_multiple(self):
result = add_rows_and_cols_to_matrix(self.TEST_MATRIX, [2, 0, 0, 0])
correct = np.array([[0] * 5, [0] * 5, [0, 0, 1, 2, 3], [0, 0, 4, 5, 6],
[0, 0, 7, 8, 9]])
self.assertArraysEqual(correct, result)
def test_append_multiple(self):
result = add_rows_and_cols_to_matrix(self.TEST_MATRIX, [0, 0, 0, 2])
correct = np.array([[1, 2, 3, 0, 0], [4, 5, 6, 0, 0], [7, 8, 9, 0, 0],
[0] * 5, [0] * 5])
self.assertArraysEqual(correct, result)
