Merge branch 'develop' into documentation

CHANGELOG.md

@@ -2,6 +2,14 @@
 
 All notable changes to this project will be documented in this file.
 
+## [2.8.1] - 2023-06-01
+### Fixed
+- `input.pandas` can now deal with columns that only have `None` entries.
+- Bug in f-string conversion of `Obs` fixed.
+- Bug in edge case of `_compute_drho` fixed.
+- Several numpy 1.25 deprecations fixed.
+
+
 ## [2.8.0] - 2023-05-21
 ### Added
 - `pyerrors` can now deal with replica with different gapsizes.

pyerrors/obs.py

@@ -278,7 +278,7 @@ class Obs:
 
             def _compute_drho(i):
                 tmp = (self.e_rho[e_name][i + 1:w_max]
-                       + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else (2 * i - (2 * w_max) // 2):-1],
+                       + np.concatenate([self.e_rho[e_name][i - 1:None if i - (w_max - 1) // 2 <= 0 else (2 * i - (2 * w_max) // 2):-1],
                                          self.e_rho[e_name][1:max(1, w_max - 2 * i)]])
                        - 2 * self.e_rho[e_name][i] * self.e_rho[e_name][1:w_max - i])
                 self.e_drho[e_name][i] = np.sqrt(np.sum(tmp ** 2) / e_N)

tests/obs_test.py

@@ -1282,3 +1282,8 @@ def test_f_string_obs():
     print(f"{o1:+3}")
     print(f"{o1:-1}")
     print(f"{o1: 8}")
+
+def test_compute_drho_fails():
+    obs = pe.input.json.load_json("tests/data/compute_drho_fails.json.gz")
+    obs.gm()
+    assert np.isclose(obs.dvalue, 0.0022150779611891094)

tests/pandas_test.py

@@ -46,10 +46,9 @@ def test_nan_df_export_import(tmp_path):
     my_df.loc[1, "int"] = np.nan
 
     for gz in [True, False]:
-        pe.input.pandas.dump_df(my_df, (tmp_path / 'df_output').as_posix(), gz=gz)
-        reconstructed_df = pe.input.pandas.load_df((tmp_path / 'df_output').as_posix(), auto_gamma=True, gz=gz)
         with pytest.warns(UserWarning, match="nan value in column int will be replaced by None"):
-            warnings.warn("nan value in column int will be replaced by None", UserWarning)
+            pe.input.pandas.dump_df(my_df, (tmp_path / 'df_output').as_posix(), gz=gz)
+        reconstructed_df = pe.input.pandas.load_df((tmp_path / 'df_output').as_posix(), auto_gamma=True, gz=gz)
         assert reconstructed_df.loc[1, "int"] is None
         assert np.all(reconstructed_df.loc[:, "float"] == my_df.loc[:, "float"])
         assert np.all(reconstructed_df.loc[:, "Obs1"] == my_df.loc[:, "Obs1"])