filter warnings

HERA-Team · Oct 16, 2024 · 9852412 · 9852412
1 parent 86e633c
commit 9852412
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Showing 2 changed files with 10 additions and 4 deletions.
diff --git a/hera_cal/tests/test_abscal.py b/hera_cal/tests/test_abscal.py
@@ -1790,8 +1790,10 @@ def test_post_redcal_abscal_run_units_warning(self, tmpdir):
         hcr.gain_scale = 'k str'
         hcr.write_calfits(calfile_units)
         with pytest.warns(RuntimeWarning, match='Overwriting redcal gain_scale of k str with model gain_scale of Jy'):
-            hca = abscal.post_redcal_abscal_run(self.data_file, calfile_units, [model_units], phs_conv_crit=1e-4,
-                                                nInt_to_load=30, verbose=False, add_to_history='testing')
+            with warnings.catch_warnings():
+                warnings.filterwarnings("ignore", message="All-NaN slice encountered")
+                hca = abscal.post_redcal_abscal_run(self.data_file, calfile_units, [model_units], phs_conv_crit=1e-4,
+                                                    nInt_to_load=30, verbose=False, add_to_history='testing')
         assert hca.gain_scale == 'Jy'
 
     def test_post_redcal_abscal_run(self, tmpdir):

diff --git a/hera_cal/tests/test_frf.py b/hera_cal/tests/test_frf.py
@@ -1177,7 +1177,9 @@ def test_get_frop_for_noise():
 def test_prep_var_for_frop():
     uvh5 = os.path.join(DATA_PATH, "test_input/zen.2458101.46106.xx.HH.OCR_53x_54x_only.uvh5")
     hd = io.HERAData([uvh5])
-    data, flags, nsamples = hd.read(fix_autos=True)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", message="Fixing auto-correlations")
+        data, flags, nsamples = hd.read()
     # The first 37 freqs give 0 variance so just exclude them to make the rest
     # of the test more transparent
     freq_slice = slice(37, 1024)
@@ -1213,7 +1215,9 @@ def test_prep_var_for_frop():
 def test_get_FRF_cov():
     uvh5 = os.path.join(DATA_PATH, "test_input/zen.2458101.46106.xx.HH.OCR_53x_54x_only.uvh5")
     hd = io.HERAData([uvh5])
-    data, flags, nsamples = hd.read(fix_autos=True)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", message="Fixing auto-correlations")
+        data, flags, nsamples = hd.read()
     # The first 37 freqs give 0 variance so just exclude them to make the rest
     # of the test more transparent
     freq_slice = slice(37, 1024)