[gentoo-commits] repo/gentoo:master commit in: dev-python/statsmodels/files/

[Andrew Ammerlaan]

commit:     fdd4806b2335243519f86233a64110c4a9284ba0
Author:     Michael Mair-Keimberger <mmk <AT> levelnine <DOT> at>
AuthorDate: Tue May 10 18:01:22 2022 +0000
Commit:     Andrew Ammerlaan <andrewammerlaan <AT> gentoo <DOT> org>
CommitDate: Thu May 12 14:16:45 2022 +0000
URL:        https://gitweb.gentoo.org/repo/gentoo.git/commit/?id=fdd4806b

dev-python/statsmodels: remove unused patch(es)

Package-Manager: Portage-3.0.30, Repoman-3.0.3
Signed-off-by: Michael Mair-Keimberger <mmk <AT> levelnine.at>
Closes: https://github.com/gentoo/gentoo/pull/25426
Signed-off-by: Andrew Ammerlaan <andrewammerlaan <AT> gentoo.org>

 .../files/statsmodels-0.11.1-tests.patch           |  35 ------
 .../statsmodels-0.12.2-new-pandas-scipy.patch      | 122 ---------------------
 2 files changed, 157 deletions(-)

diff --git a/dev-python/statsmodels/files/statsmodels-0.11.1-tests.patch b/dev-python/statsmodels/files/statsmodels-0.11.1-tests.patch
deleted file mode 100644
index 9a1a258d0779..000000000000
--- a/dev-python/statsmodels/files/statsmodels-0.11.1-tests.patch
+++ /dev/null
@@ -1,35 +0,0 @@
-diff -ur statsmodels-0.11.1.orig/statsmodels/base/tests/test_penalized.py statsmodels-0.11.1/statsmodels/base/tests/test_penalized.py
---- statsmodels-0.11.1.orig/statsmodels/base/tests/test_penalized.py	2020-04-28 22:02:47.150938650 -0700
-+++ statsmodels-0.11.1/statsmodels/base/tests/test_penalized.py	2020-04-28 22:03:24.468704937 -0700
-@@ -73,6 +73,7 @@
-         y = np.random.poisson(mu)
-         return y
- 
-+    @pytest.mark.skip("Broken on all impls")
-     def test_params_table(self):
-         res1 = self.res1
-         res2 = self.res2
-@@ -380,9 +381,6 @@
-         bse = np.array([0.028126650444581985, 0.033099984564283147,
-                         0.033184585514904545, 0.034282504130503301])
-         assert_allclose(res2.params[:self.k_nonzero], params, atol=1e-5)
--        assert_allclose(res2.bse[:self.k_nonzero], bse, rtol=5e-6)
--        assert_allclose(res1.params[:self.k_nonzero], params, atol=1e-5)
--        assert_allclose(res1.bse[:self.k_nonzero], bse, rtol=5e-6)
- 
- 
- # the following classes are copies of Poisson with model adjustments
-Only in statsmodels-0.11.1/statsmodels/base/tests: test_penalized.py.orig
-diff -ur statsmodels-0.11.1.orig/statsmodels/tsa/statespace/tests/test_structural.py statsmodels-0.11.1/statsmodels/tsa/statespace/tests/test_structural.py
---- statsmodels-0.11.1.orig/statsmodels/tsa/statespace/tests/test_structural.py	2020-04-28 22:02:47.207938293 -0700
-+++ statsmodels-0.11.1/statsmodels/tsa/statespace/tests/test_structural.py	2020-04-28 22:04:02.871464429 -0700
-@@ -243,7 +243,7 @@
-     run_ucm('rtrend_ar1', use_exact_diffuse=True)
- 
- 
--@×××××××××××.slow
-+@×××××××××××.skip("Fails")
- def test_lltrend_cycle_seasonal_reg_ar1(close_figures):
-     run_ucm('lltrend_cycle_seasonal_reg_ar1_approx_diffuse')
-     run_ucm('lltrend_cycle_seasonal_reg_ar1', use_exact_diffuse=True)
-Only in statsmodels-0.11.1/statsmodels/tsa/statespace/tests: .test_structural.py.un~

diff --git a/dev-python/statsmodels/files/statsmodels-0.12.2-new-pandas-scipy.patch b/dev-python/statsmodels/files/statsmodels-0.12.2-new-pandas-scipy.patch
deleted file mode 100644
index d11cd08ecf6f..000000000000
--- a/dev-python/statsmodels/files/statsmodels-0.12.2-new-pandas-scipy.patch
+++ /dev/null
@@ -1,122 +0,0 @@
-From 4f32f3990fbba0ee440af47e23a9354fdb7a0285 Mon Sep 17 00:00:00 2001
-From: Kevin Sheppard <kevin.sheppard@×××××.com>
-Date: Fri, 12 Mar 2021 10:52:38 +0000
-Subject: [PATCH] MAINT: Fix issues arising from future changes
-
-Fix issues due to changes in SciPy and pandas
----
- statsmodels/regression/tests/test_rolling.py | 6 ++++--
- statsmodels/stats/descriptivestats.py        | 8 +++++++-
- statsmodels/stats/stattools.py               | 4 +++-
- 3 files changed, 14 insertions(+), 4 deletions(-)
-
-diff --git a/statsmodels/regression/tests/test_rolling.py b/statsmodels/regression/tests/test_rolling.py
-index 050de605f..f02e076d6 100644
---- a/statsmodels/regression/tests/test_rolling.py
-+++ b/statsmodels/regression/tests/test_rolling.py
-@@ -1,5 +1,6 @@
- from io import BytesIO
- from itertools import product
-+import warnings
- 
- import numpy as np
- import pandas as pd
-@@ -261,8 +262,9 @@ def test_plot():
-         res.plot_recursive_coefficient(variables="x4")
- 
-     fig = plt.Figure()
--    with pytest.warns(Warning):
--        # Just silence the warning
-+    # Just silence the warning
-+    with warnings.catch_warnings():
-+        warnings.simplefilter("ignore")
-         out = res.plot_recursive_coefficient(fig=fig)
-     assert out is fig
-     res.plot_recursive_coefficient(alpha=None, figsize=(30, 7))
-diff --git a/statsmodels/stats/descriptivestats.py b/statsmodels/stats/descriptivestats.py
-index 96d455ca1..d5ad2f2a5 100644
---- a/statsmodels/stats/descriptivestats.py
-+++ b/statsmodels/stats/descriptivestats.py
-@@ -446,8 +446,14 @@ class Description:
-         else:
-             iqr = mean
- 
-+        def _safe_jarque_bera(c):
-+            a = np.asarray(c)
-+            if a.shape[0] < 2:
-+                return (np.nan,) * 4
-+            return jarque_bera(a)
-+
-         jb = df.apply(
--            lambda x: list(jarque_bera(x.dropna())), result_type="expand"
-+            lambda x: list(_safe_jarque_bera(x.dropna())), result_type="expand"
-         ).T
-         nan_mean = mean.copy()
-         nan_mean.loc[nan_mean == 0] = np.nan
-diff --git a/statsmodels/stats/stattools.py b/statsmodels/stats/stattools.py
-index d349c472d..2ee1a6e0b 100644
---- a/statsmodels/stats/stattools.py
-+++ b/statsmodels/stats/stattools.py
-@@ -118,7 +118,9 @@ def jarque_bera(resids, axis=0):
-     where n is the number of data points, S is the sample skewness, and K is
-     the sample kurtosis of the data.
-     """
--    resids = np.asarray(resids)
-+    resids = np.atleast_1d(np.asarray(resids, dtype=float))
-+    if resids.size < 2:
-+        raise ValueError("resids must contain at least 2 elements")
-     # Calculate residual skewness and kurtosis
-     skew = stats.skew(resids, axis=axis)
-     kurtosis = 3 + stats.kurtosis(resids, axis=axis)
--- 
-2.32.0
-
-From a9e21aef508ea98da8c5889547b8e5748986dae1 Mon Sep 17 00:00:00 2001
-From: Kevin Sheppard <kevin.k.sheppard@×××××.com>
-Date: Wed, 7 Apr 2021 09:52:25 +0100
-Subject: [PATCH] MAINT: Fix descriptive stats with extension dtypes
-
-Add special path for extension dtypes to remove N/A
----
- statsmodels/stats/descriptivestats.py | 17 +++++++++++++++--
- 1 file changed, 15 insertions(+), 2 deletions(-)
-
-diff --git a/statsmodels/stats/descriptivestats.py b/statsmodels/stats/descriptivestats.py
-index d5ad2f2a5..0fd3eb542 100644
---- a/statsmodels/stats/descriptivestats.py
-+++ b/statsmodels/stats/descriptivestats.py
-@@ -441,8 +441,20 @@ class Description:
-         loc = count > 0
-         mode_freq = np.full(mode.shape[0], np.nan)
-         mode_freq[loc] = mode_counts[loc] / count.loc[loc]
-+        # TODO: Workaround for pandas AbstractMethodError in extension
-+        #  types. Remove when quantile is supported for these
-+        _df = df
-+        try:
-+            from pandas.api.types import is_extension_array_dtype
-+            _df = df.copy()
-+            for col in df:
-+                if is_extension_array_dtype(df[col].dtype):
-+                    _df[col] = _df[col].astype(object).fillna(np.nan)
-+        except ImportError:
-+            pass
-+
-         if df.shape[1] > 0:
--            iqr = df.quantile(0.75) - df.quantile(0.25)
-+            iqr = _df.quantile(0.75) - _df.quantile(0.25)
-         else:
-             iqr = mean
- 
-@@ -493,7 +505,8 @@ class Description:
-             return results_df
-         # Pandas before 1.0 cannot handle empty DF
-         if df.shape[1] > 0:
--            perc = df.quantile(self._percentiles / 100).astype(float)
-+            # TODO: Remove when extension types support quantile
-+            perc = _df.quantile(self._percentiles / 100).astype(float)
-         else:
-             perc = pd.DataFrame(index=self._percentiles / 100, dtype=float)
-         if np.all(np.floor(100 * perc.index) == (100 * perc.index)):
--- 
-2.32.0
-