def it_can_compute_a_subtotal_intersection_value(
self,
request,
row_add_idxs,
row_sub_idxs,
col_add_idxs,
col_sub_idxs,
diff_cols_nan,
diff_rows_nan,
expected_value,
):
col_subtotal_ = instance_mock(
request,
_Subtotal,
addend_idxs=col_add_idxs,
subtrahend_idxs=col_sub_idxs,
)
row_subtotal_ = instance_mock(
request,
_Subtotal,
addend_idxs=row_add_idxs,
subtrahend_idxs=row_sub_idxs,
)
base_values = np.arange(12).reshape(3, 4)
subtotals = SumSubtotals(base_values, None, diff_cols_nan,
diff_rows_nan)
np.testing.assert_equal(
subtotals._intersection(row_subtotal_, col_subtotal_),
expected_value)
def it_can_compute_a_subtotal_row_to_help(self, subtotal_, addend_idxs,
subtrahend_idxs, diff_rows_nan,
expected_value):
subtotal_.addend_idxs = addend_idxs
subtotal_.subtrahend_idxs = subtrahend_idxs
base_values = np.arange(12).reshape(3, 4)
subtotals = SumSubtotals(base_values,
None,
diff_rows_nan=diff_rows_nan)
assert subtotals._subtotal_row(subtotal_).tolist() == pytest.approx(
expected_value, nan_ok=True)
def rows_margin_proportion(self):
"""1D/2D np.float64 ndarray of weighted-proportion for each slice row/cell."""
# --- an X_MR slice produces a 2D rows-margin (each cell has its own N) ---
# --- TODO: Should rows_margin_proportion only be defined when it's 1D? This would
# --- require changes to exporter to use the bases to give a "rows_margin_range"
if not self._measures.rows_table_proportion.is_defined:
return self._assemble_matrix(
SumSubtotals.blocks(
self.rows_margin / self.table_weighted_bases,
self._dimensions,
)
)
# --- otherwise rows-margin is a vector ---
return self._assemble_marginal(self._measures.rows_table_proportion)
def it_provides_a_subtotal_rows_interface_method(self, request,
dimensions_, _init_):
base_values = [[4, 1], [3, 5]]
property_mock(
request,
SumSubtotals,
"_subtotal_rows",
return_value=np.array([[4, 3], [2, 1]]),
)
subtotal_rows = SumSubtotals.subtotal_rows(base_values, dimensions_)
_init_.assert_called_once_with(ANY, [[4, 1], [3, 5]], dimensions_,
False, False)
assert subtotal_rows.tolist() == [[4, 3], [2, 1]]
def it_provides_an_intersections_interface_method(self, request,
dimensions_, _init_):
base_values = [[1, 5], [8, 0]]
property_mock(
request,
SumSubtotals,
"_intersections",
return_value=np.array([[1, 2], [3, 4]]),
)
intersections = SumSubtotals.intersections(base_values, dimensions_)
_init_.assert_called_once_with(ANY, [[1, 5], [8, 0]], dimensions_,
False, False)
assert intersections.tolist() == [[1, 2], [3, 4]]
def columns_margin_proportion(self):
"""1D/2D np.float64 ndarray of weighted-prop for each column of this slice."""
# --- an MR_X slice produces a 2D columns-margin (each cell has its own N) ---
# --- TODO: Should colums_margin_proportion only be defined when it's 1D? This
# --- requires changes to exporter to use the bases to give a
# --- "columns_margin_range"
if not self._measures.columns_table_proportion.is_defined:
return self._assemble_matrix(
SumSubtotals.blocks(
self.columns_margin / self.table_weighted_bases,
self._dimensions,
)
)
# --- otherwise columns-margin-proportion is a maginal ---
return self._assemble_marginal(self._measures.columns_table_proportion)
def it_provides_a_subtotal_columns_interface_method(
self, request, dimensions_, _init_):
base_values = [[0, 4], [7, 9]]
property_mock(
request,
SumSubtotals,
"_subtotal_columns",
return_value=np.array([[1, 2], [3, 4]]),
)
subtotal_columns = SumSubtotals.subtotal_columns(
base_values, dimensions_)
_init_.assert_called_once_with(ANY, [[0, 4], [7, 9]], dimensions_,
False, False)
assert subtotal_columns.tolist() == [[1, 2], [3, 4]]