[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 repos:
   # Using this mirror lets us use mypyc-compiled black, which is about 2x faster
   - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 24.1.1
+    rev: 26.1.0
     hooks:
       - id: black
         # It is recommended to specify the latest version of Python

tests/test_calibration/test_cal_auto_ratio_remultiply.py

@@ -96,10 +96,8 @@ def test_cal_auto_ratio_remultiply(before_file, after_file):
     and then calls `cal_auto_ratio_remultiply`, checking the outputs match expectations
     """
     if before_file == None or after_file == None:
-        pytest.skip(
-            f"""This test has been skipped because the test was listed in the 
-                    skipped tests due to FHD not outputting them: {skip_tests}"""
-        )
+        pytest.skip(f"""This test has been skipped because the test was listed in the 
+                    skipped tests due to FHD not outputting them: {skip_tests}""")
 
     h5_before = load(before_file)
     expected_cal = load(after_file)

tests/test_calibration/test_calibrate_qu_mixing.py

@@ -80,14 +80,12 @@ def test_qu_mixing(before_file, after_file):
     """Runs the test on `calibrate_qu_mixing` - reads in the data in `data_loc`,
     and then calls `calibrate_qu_mixing`, checking the outputs match expectations"""
     if before_file == None or after_file == None:
-        pytest.skip(
-            f""""This test has been skipped because the test was listed 
+        pytest.skip(f""""This test has been skipped because the test was listed 
                     in the skipped tests due to FHD not outputting them: {skip_tests}.
                     In this case it as due to the LA_LEAST_SQUARES differences
                     compared to np.linalg.lstsq which doesn't use double precision
                     by default which for some reason makes a difference for values
-                    close to 0 in single precision."""
-        )
+                    close to 0 in single precision.""")
 
     h5_before = load(before_file)
     expected_calc_phase = load(after_file)

tests/test_calibration/test_vis_calibration_flag.py

@@ -101,16 +101,14 @@ def test_vis_calibration_flag(before_file, after_file):
     """Runs the test on `vis_calibration_flag` - reads in the data in before_file and after_file,
     and then calls `vis_calibration_flag`, checking the outputs match expectations"""
     if before_file == None or after_file == None:
-        pytest.skip(
-            f"""This test has been skipped because the test was listed in the 
+        pytest.skip(f"""This test has been skipped because the test was listed in the 
                     skipped tests due to FHD not outputting them: {skip_tests}. The reason
                     for skipping point_offzenith_run3 is due to the difference of NumPy median
                     and median in IDL. IDL doesn't take the average of the two middle numbers
                     when dealing with an an array of even values. It wasn't a problem in the other
                     cases, but not this one, and because we're dealing with a continuous set of data,
                     it doesn't feel appropriate to use the IDL median.
-                    """
-        )
+                    """)
 
     h5_before = load(before_file)
     expected_obs = load(after_file)