style: apply pre-commit

.coveragerc

@@ -3,9 +3,9 @@ omit =
      */tests/*
      */data/*
      */scripts/*
-     
+
 [report]
 omit =
      */tests/*
      */data/*
-     */scripts/*
+     */scripts/*

.gitignore

@@ -37,4 +37,4 @@ hera_qm/data/test_output/ant_metrics_output.json
 hera_qm/_version.py
 
 artifacts/*
-result.md
+result.md

.pre-commit-config.yaml

@@ -1,3 +1,5 @@
+exclude: '(^docs/conf.py|^hera_qm/data/|.codecov.yml)'
+
 ci:
   autoupdate_schedule: monthly
 

hera_qm/metrics_io.py

@@ -117,11 +117,11 @@ def _recursively_save_dict_to_group(h5file, path, in_dict):
     """
     allowed_types = (np.ndarray, np.float32, float, int,
                      bytes, str, list, bool, np.bool_)
-    
-        
+
+
     compressable_types = (np.ndarray, list)
     for key in in_dict:
-        # Catch case with numpy 2 where keys of type (np.int32(ant), 'polstr')) are 
+        # Catch case with numpy 2 where keys of type (np.int32(ant), 'polstr')) are
         # converted to string with the full np.int32 identifier in them.
         if isinstance(key, tuple):
             key = tuple(int(k) if isinstance(k, (int, np.int32, np.int64)) else k for k in key)

hera_qm/omnical_metrics.py

@@ -12,7 +12,6 @@
 import json
 import copy
 import os
-import warnings
 
 
 def get_omnical_metrics_dict():

hera_qm/tests/test_ant_metrics.py

@@ -364,11 +364,11 @@ def test_ant_metrics_run_and_load_antenna_metrics():
     # test a priori flagging via YAML
     four_pol_uvh5 = DATA_PATH + '/zen.2457698.40355.full_pol_test.uvh5'
     apf_yaml = os.path.join(DATA_PATH, 'a_priori_flags_sample.yaml')
-    
+
     # SGM: not sure if the following warning *should* be raised.
     with pytest.warns(RuntimeWarning, match='All-NaN slice encountered'):
         am = ant_metrics.ant_metrics_run(four_pol_uvh5, diff_files=four_pol_uvh5, overwrite=True, a_priori_xants_yaml=apf_yaml, verbose=True)
-        
+
     am_hdf5 = ant_metrics.load_antenna_metrics(four_pol_uvh5.replace('.uvh5', '.ant_metrics.hdf5'))
     for ant in [(0, 'Jee'), (0, 'Jnn'), (10, 'Jee'), (10, 'Jnn'), (1, 'Jee'), (3, 'Jnn')]:
         assert ant in am_hdf5['xants']

hera_qm/tests/test_auto_metrics.py

@@ -221,7 +221,7 @@ def test_auto_metrics_run():
         warnings.filterwarnings("ignore", message="K1 value 8 is larger than the data of dimension 4; using the size of the data for the kernel size")
         warnings.filterwarnings("ignore", message="Mean of empty slice")
         warnings.filterwarnings("ignore", message="Degrees of freedom <= 0 for slice")
-        
+
         ex_ants, modzs, spectra, flags = auto_metrics.auto_metrics_run(metrics_outfile, auto_files,
                                                                    median_round_modz_cut=75., mean_round_modz_cut=5.,
                                                                    edge_cut=100, Kt=8, Kf=8, sig_init=5.0, sig_adj=2.0,

hera_qm/tests/test_xrfi.py

@@ -1398,7 +1398,7 @@ def test_xrfi_run_step(tmpdir):
     assert np.all(np.isclose(uvf_a1.flag_array, uvf_a2.flag_array))
     assert np.all(np.isclose(uvf1.metric_array, uvf2.metric_array, atol=1e-5, rtol=1e-5))
     # hit one line involving uvcal reinitialization and include yaml file.
-    
+
     with pytest.warns(RuntimeWarning, match="invalid value encountered in subtract"):
         xrfi.xrfi_run_step(uv_files=ocal_file, calculate_uvf_apriori=True, run_filter=True, reinitialize=True, a_priori_flag_yaml=a_priori_flag_integrations)
     # test invalid data type error