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code refactoring, mantaining coverage 100%
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@ernestoarbitrio
ernestoarbitrio committed May 5, 2020
1 parent dedf6cb commit 2aa5409
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Showing 3 changed files with 300 additions and 74 deletions.
86 changes: 16 additions & 70 deletions src/cr/cube/matrix.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -464,7 +464,7 @@ def _variance(self):
"""Returns the variance for cell percentages
`variance = p * (1-p)`
"""
return self._counts * (1 - self._counts)
return self._counts / self.table_margin * (1 - self._counts / self.table_margin)

@lazyproperty
def _zscores(self):
Expand Down Expand Up @@ -636,7 +636,11 @@ def _variance(self):
"""Returns the variance for cell percentages
`variance = p * (1-p)`
"""
return self._counts[:, 0, :] * (1 - self._counts[:, 0, :])
return (
self._counts[:, 0, :]
/ self.table_margin[:, None]
* (1 - self._counts[:, 0, :] / self.table_margin[:, None])
)

@lazyproperty
def _zscores(self):
Expand Down Expand Up @@ -774,7 +778,11 @@ def _variance(self):
"""Returns the variance for cell percentages
`variance = p * (1-p)`
"""
return self._counts[:, :, 0] * (1 - self._counts[:, :, 0])
return (
self._counts[:, :, 0]
/ self.table_margin
* (1 - self._counts[:, :, 0] / self.table_margin)
)

@lazyproperty
def _zscores(self):
Expand Down Expand Up @@ -987,7 +995,11 @@ def _variance(self):
"""Returns the variance for cell percentages
`variance = p * (1-p)`
"""
return self._counts[:, 0, :, 0] * (1 - self._counts[:, 0, :, 0])
return (
self._counts[:, 0, :, 0]
/ self.table_margin
* (1 - self._counts[:, 0, :, 0] / self.table_margin)
)

@lazyproperty
def _zscores(self):
Expand Down Expand Up @@ -1105,14 +1117,6 @@ def ordering(self):
"""
return (self._anchor_n, self._neg_idx, self)

@lazyproperty
def standard_deviation(self):
return self._standard_deviation

@lazyproperty
def standard_error(self):
return self._standard_error

@lazyproperty
def table_margin(self):
return self._table_margin
Expand Down Expand Up @@ -1141,27 +1145,6 @@ def _anchor_n(self):
else int(self.anchor) + 1
)

@lazyproperty
def _standard_deviation(self):
"""Returns the standard deviation for cell percentages
`std_deviation = sqrt(variance)`
"""
return np.sqrt(self._variance)

@lazyproperty
def _standard_error(self):
"""Returns the standard error for cell percentages
`std_error = sqrt(variance/N)`
"""
return np.sqrt(self._variance / self.table_margin)

@lazyproperty
def _variance(self):
"""Returns the variance for cell percentages
`variance = p * (1-p)`
"""
return self._values * (1 - self._values)

@lazyproperty
def _zscore(self):
# TODO: remove this if statement - temporary hack until MR zscore implementation
Expand Down Expand Up @@ -1675,27 +1658,6 @@ def numeric(self):
def pruned(self):
return self.base == 0 or np.isnan(self.base)

@lazyproperty
def standard_deviation(self):
"""Returns the standard deviation for cell percentages
`std_deviation = sqrt(variance)`
"""
return np.sqrt(self._variance)

@lazyproperty
def standard_error(self):
"""Returns the standard error for cell percentages
`std_error = sqrt(variance/N)`
"""
return np.sqrt(self._variance / self.table_margin)

@lazyproperty
def variance(self):
"""Returns the variance for cell percentages
`variance = p * (1-p)`
"""
return self.values * (1 - self.values)

@lazyproperty
def zscore(self):
variance = (
Expand Down Expand Up @@ -1803,14 +1765,6 @@ def __init__(
def pruned(self):
return self.table_base == 0

@lazyproperty
def standard_deviation(self):
return self._standard_deviation

@lazyproperty
def standard_error(self):
return self._standard_error

@lazyproperty
def table_base(self):
return np.sum(self._all_bases)
Expand Down Expand Up @@ -1884,14 +1838,6 @@ def margin(self):
def pruned(self):
return np.all(self.base == 0) or np.all(np.isnan(self.base))

@lazyproperty
def standard_deviation(self):
return self._standard_deviation

@lazyproperty
def standard_error(self):
return self._standard_error

@lazyproperty
def values(self):
return self._selected
Expand Down
229 changes: 229 additions & 0 deletions tests/integration/test_headers_and_subtotals.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2569,6 +2569,226 @@ def it_calculates_residuals_for_cat_x_items_x_cats_with_col_insertion(self):
],
],
)
# Test std deviation
np.testing.assert_almost_equal(
slice_.standard_deviation,
[
[
0.03018845,
0.0319175,
0.04857593,
0.04751389,
0.08953993,
0.10328323,
0.1524741,
0.18022756,
0.13456855,
0.18607541,
0.28325803,
],
[
0.0595667,
0.04309204,
0.04933763,
0.07460264,
0.11766836,
0.14009466,
0.20399558,
0.2858036,
0.24756061,
0.30673482,
0.43888846,
],
[
0.0451034,
0.03524264,
0.04325743,
0.05778187,
0.09675494,
0.11460302,
0.16205685,
0.20556123,
0.16948566,
0.2256755,
0.33368666,
],
[
0.02002223,
0.02248904,
0.01817414,
0.01864496,
0.05761441,
0.0601484,
0.09295886,
0.10388546,
0.09123329,
0.11333915,
0.17684956,
],
[
0.04082826,
0.02342972,
0.02170135,
0.02434758,
0.06941901,
0.09116899,
0.13440853,
0.1652839,
0.1624643,
0.2043584,
0.29853975,
],
[
0.03566708,
0.01482241,
0.02063053,
0.03399419,
0.05407998,
0.07387197,
0.10215211,
0.13465807,
0.12933925,
0.14491506,
0.23175336,
],
[
0.02433953,
0.0148974,
0.01541497,
0.02545434,
0.04827421,
0.04793991,
0.06399285,
0.08495292,
0.06291114,
0.08184793,
0.13290769,
],
[
0.01960535,
0.01548208,
0.01906989,
0.02260114,
0.04638769,
0.04187538,
0.07265425,
0.09220725,
0.07954493,
0.09381268,
0.15249847,
],
],
)
# Test standard error
np.testing.assert_almost_equal(
slice_.standard_error,
[
[
0.00034447,
0.0003642,
0.00055429,
0.00054217,
0.00102171,
0.00117853,
0.00173984,
0.00205652,
0.00153552,
0.00212325,
0.00323218,
],
[
0.0006797,
0.00049171,
0.00056298,
0.00085127,
0.00134268,
0.00159858,
0.00232773,
0.00326122,
0.00282484,
0.00350006,
0.00500803,
],
[
0.00051466,
0.00040214,
0.0004936,
0.00065933,
0.00110404,
0.0013077,
0.00184918,
0.0023456,
0.00193395,
0.00257512,
0.0038076,
],
[
0.00022847,
0.00025662,
0.00020738,
0.00021275,
0.00065742,
0.00068634,
0.00106073,
0.00118541,
0.00104104,
0.00129328,
0.00201798,
],
[
0.00046588,
0.00026735,
0.00024763,
0.00027782,
0.00079212,
0.0010403,
0.0015337,
0.00188601,
0.00185383,
0.00233187,
0.00340655,
],
[
0.00040699,
0.00016913,
0.00023541,
0.0003879,
0.00061709,
0.00084293,
0.00116563,
0.00153654,
0.00147585,
0.00165358,
0.00264447,
],
[
0.00027773,
0.00016999,
0.0001759,
0.00029045,
0.00055084,
0.00054703,
0.0007302,
0.00096937,
0.00071786,
0.00093394,
0.00151657,
],
[
0.00022371,
0.00017666,
0.0002176,
0.0002579,
0.00052932,
0.00047783,
0.00082904,
0.00105215,
0.00090766,
0.00107047,
0.00174012,
],
],
)

transforms = {"columns_dimension": {"insertions": {}}}
slice_no_col_insertion_ = Cube(
Expand All @@ -2582,6 +2802,14 @@ def it_calculates_residuals_for_cat_x_items_x_cats_with_col_insertion(self):
np.testing.assert_almost_equal(
slice_no_col_insertion_.pvals, slice_.pvals[:, : slice_.pvals.shape[1] - 1]
)
np.testing.assert_almost_equal(
slice_no_col_insertion_.standard_deviation,
slice_.standard_deviation[:, : slice_.standard_deviation.shape[1] - 1],
)
np.testing.assert_almost_equal(
slice_no_col_insertion_.standard_error,
slice_.standard_error[:, : slice_.standard_error.shape[1] - 1],
)

def it_calculates_residuals_for_ca_as_0th_with_1_col_insertion(self):
# Test for multi-cube when first cube represents a categorical-array
Expand Down Expand Up @@ -3429,4 +3657,5 @@ def it_provide_residual_test_stats_including_hs(self):
slice_ = Cube(CR.CAT_X_CAT_HS_2ROWS_1COL).partitions[0]
np.testing.assert_array_equal(slice_.pvals, slice_.residual_test_stats[0])
np.testing.assert_array_equal(slice_.zscore, slice_.residual_test_stats[1])

assert slice_.residual_test_stats.shape == (2, 6, 7)
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