Add test outlier detection #298
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| @@ -174,3 +174,9 @@ def test_detect_outlier_multivariate_local(): | |||
| V[-1] = (-3, 3) | |||
| outliers = cleansing.detect_outliers(V, 4, coord=X, k=50) | |||
| assert outliers.sum() == 2 | |||
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| def test_detect_outlier_input_dims(): | |||
| V = np.zeros((20, 3, 2)) | |||
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could you test a list of input dimensions/different cases?
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Thanks @chiara-arpae for the contribution.
The test is failing because there is a bug in the detect_outliers function.
When the dimensions are incorrect, the code raising the exception has a error:
raise ValueError(
f"input_array must have 1 (n) or 2 dimensions (n, m), "
f"but it has {coord.ndim}"
)
Here, {coord.ndim} should be {input_array.ndim}
Do you want to add the fix to bug?
|
hey @chiara-arpae please let us know if something is not clear in the comments left above. The pull request is almost ready to be merged, just few final changes are needed ;) |
|
Hi! I'm very sorry for late. I should have committed the suggested correction few minutes ago. Please let me know if it's all fine. |
correcting input_array instead of coords in log message
|
Hi, I'm very sorry for late. I should have committed the correction but I
received a message about check black failing from Github.
I realized I have modified and committed on master branch, instead of doing
it on the branch 'test_cleaning_2d'. Maybe could it depend on that? Sorry
very much for mess. If you could help me I'd be grateful.
Il giorno ven 16 set 2022 alle ore 10:32 Daniele Nerini <
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… hey @chiara-arpae <https://github.com/chiara-arpae> please let us know if
something is not clear in the comments left above. The pull request is
almost ready to be merged, just few final changes are needed ;)
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Codecov Report
@@ Coverage Diff @@
## master #298 +/- ##
==========================================
+ Coverage 82.71% 82.74% +0.03%
==========================================
Files 160 160
Lines 12292 12310 +18
==========================================
+ Hits 10167 10186 +19
+ Misses 2125 2124 -1
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removed k parameter from cleansing.detect_outliers in test.test_utils_cleansing.test_detect_outlier_input_dims() because not necessary for test and coords is not passed.
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hey @chiara-arpae no worries and thanks for getting back on this! It looks good to go! :-) |
[ERAD]Test that input arrays with more than 2 dimensions raise a ValueError exception](https://app.codecov.io/gh/pySTEPS/pysteps/compare/283/tree/pysteps/utils/cleansing.py#D1L173)