Merge pull request #461 from HERA-Team/fix_pyuvdata_v3

Fix warning handling for pyuvdata v3.0

hera_qm/firstcal_metrics.py

@@ -10,6 +10,7 @@
 from . import utils, metrics_io
 import copy
 import os
+import warnings
 
 try:
     from sklearn import gaussian_process as gp
@@ -343,7 +344,11 @@ def __init__(self, calfits_files, use_gp=True):
         """
         # Instantiate UVCal and read calfits
         self.UVC = UVCal()
-        self.UVC.read_calfits(calfits_files, use_future_array_shapes=True)
+        with warnings.catch_warnings():
+            warnings.filterwarnings(
+                "ignore", "Future array shapes are now always used"
+            )
+            self.UVC.read_calfits(calfits_files, use_future_array_shapes=True)
 
         if hasattr(self.UVC, "telescope"):
             x_orientation = self.UVC.telescope.x_orientation

hera_qm/omnical_metrics.py

@@ -176,10 +176,9 @@ def load_firstcal_gains(fc_file):
     uvc = UVCal()
     with warnings.catch_warnings():
         warnings.filterwarnings(
-            "ignore", "The shapes of several attributes"
+            "ignore", "Future array shapes are now always used"
         )
-        uvc.read_calfits(fc_file)
-    uvc.use_future_array_shapes()
+        uvc.read_calfits(fc_file, use_future_array_shapes=True)
     fc_gains = np.moveaxis(uvc.gain_array, 1, 2)[:, :, :, 0]
     d_nu = np.mean(uvc.freq_array[1:] - uvc.freq_array[:-1])
     d_phi = np.abs(np.mean(np.angle(fc_gains)[:, :, 1:] - np.angle(fc_gains)[:, :, :-1], axis=2))
@@ -454,7 +453,11 @@ def __init__(self, omni_calfits, history=''):
 
         # Instantiate Data Object
         self.uv = UVCal()
-        self.uv.read_calfits(omni_calfits, use_future_array_shapes=True)
+        with warnings.catch_warnings():
+            warnings.filterwarnings(
+                "ignore", "Future array shapes are now always used"
+            )
+            self.uv.read_calfits(omni_calfits, use_future_array_shapes=True)
 
         # Get relevant metadata
         self.Nants = self.uv.Nants_data

hera_qm/tests/test_utils.py

@@ -262,6 +262,7 @@ def test_strip_extension_return_ext_extension():
     root, ext = utils.strip_extension(path, return_ext=True)
     assert ext == path[-3:]
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.parametrize(
     "filein",
     ["a_priori_flags_integrations.yaml",
@@ -351,6 +352,7 @@ def test_apply_yaml_flags_uvdata(tmpdir, filein, flag_freqs, flag_times, flag_an
 # this top one can be removed when we require pyuvdata >= 3.0
 @pytest.mark.filterwarnings("ignore:Cannot preserve total_quality_array when")
 @pytest.mark.filterwarnings("ignore:Changing number of antennas, but preserving")
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.parametrize(
     "filein",
     ["a_priori_flags_integrations.yaml",
@@ -417,6 +419,8 @@ def test_apply_yaml_flags_uvcal(filein):
             pytest.raises(NotImplementedError, utils.apply_yaml_flags, uvc, a_priori_flag_yaml=test_flag,
                          throw_away_flagged_ants=True, ant_indices_only=False)
 
+
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 def test_apply_yaml_flags_errors():
     test_flag_jds = os.path.join(DATA_PATH, 'a_priori_flags_jds.yaml')
     test_c_file = os.path.join(DATA_PATH, 'zen.2457698.40355.xx.HH.uvcAA.omni.calfits')

hera_qm/tests/test_vis_metrics.py

@@ -9,6 +9,7 @@
 import os
 import copy
 import pytest
+import warnings
 
 pytestmark = pytest.mark.filterwarnings(
     "ignore:The uvw_array does not match the expected values given the antenna positions.",
@@ -18,7 +19,9 @@
 def vismetrics_data():
     data = UVData()
     filename = os.path.join(DATA_PATH, 'zen.2457698.40355.xx.HH.uvcAA')
-    data.read_miriad(filename, use_future_array_shapes=True, check_autos=False)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        data.read_miriad(filename, use_future_array_shapes=True, check_autos=False)
 
     # massage the object to make it work with check_noise_variance
     data.select(antenna_nums=data.get_ants()[0:10])
@@ -75,11 +78,13 @@ def test_check_noise_variance_inttime_error(vismetrics_data):
 @pytest.fixture(scope='function')
 def uvd():
     uvd = UVData()
-    uvd.read_miriad(
-        os.path.join(DATA_PATH, 'zen.2458002.47754.xx.HH.uvA'),
-        projected=False, use_future_array_shapes=True,
-        check_autos=False
-    )
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvd.read_miriad(
+            os.path.join(DATA_PATH, 'zen.2458002.47754.xx.HH.uvA'),
+            projected=False, use_future_array_shapes=True,
+            check_autos=False
+        )
     return uvd
 
 def test_vis_bl_cov(uvd):
@@ -147,6 +152,7 @@ def test_plot_bl_bl_scatter(uvd):
     plt.close('all')
 
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 def test_sequential_diff():
     uvd = UVData()
     uvd.read_miriad(os.path.join(DATA_PATH, 'zen.2457698.40355.xx.HH.uvcAA'), use_future_array_shapes=True)

hera_qm/tests/test_xrfi.py

@@ -52,7 +52,9 @@
 
 @pytest.fixture(scope="session")
 def uvdata_miriad_main():
-    uv = UVData.from_file(test_d_file, use_future_array_shapes=True)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uv = UVData.from_file(test_d_file, use_future_array_shapes=True)
     yield uv
 
     # clean up when done
@@ -74,9 +76,11 @@ def uvdata_miriad(uvdata_miriad_main):
 
 @pytest.fixture(scope="session")
 def uvflag_metric_miriad_main(uvdata_miriad_main):
-    uvm = UVFlag(
-        uvdata_miriad_main, history='I made this', use_future_array_shapes=True
-    )
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvm = UVFlag(
+            uvdata_miriad_main, history='I made this', use_future_array_shapes=True
+        )
     yield uvm
     # clean up when done
     del uvm
@@ -96,12 +100,14 @@ def uvflag_metric_miriad(uvflag_metric_miriad_main):
 
 @pytest.fixture(scope="session")
 def uvflag_metric_waterfall_miriad_main(uvdata_miriad_main):
-    uvm = UVFlag(
-        uvdata_miriad_main,
-        history='I made this',
-        waterfall=True,
-        use_future_array_shapes=True
-    )
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvm = UVFlag(
+            uvdata_miriad_main,
+            history='I made this',
+            waterfall=True,
+            use_future_array_shapes=True
+        )
     yield uvm
     # clean up when done
     del uvm
@@ -121,7 +127,9 @@ def uvflag_metric_waterfall_miriad(uvflag_metric_waterfall_miriad_main):
 
 @pytest.fixture(scope="session")
 def uvflag_flag_miriad_main(uvdata_miriad_main):
-    uvf = UVFlag(uvdata_miriad_main, mode='flag', use_future_array_shapes=True)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvf = UVFlag(uvdata_miriad_main, mode='flag', use_future_array_shapes=True)
     yield uvf
     # clean up when done
     del uvf
@@ -141,12 +149,14 @@ def uvflag_flag_miriad(uvflag_flag_miriad_main):
 
 @pytest.fixture(scope="session")
 def uvflag_flag_waterfall_miriad_main(uvdata_miriad_main):
-    uvf = UVFlag(
-        uvdata_miriad_main,
-        mode='flag',
-        waterfall=True,
-        use_future_array_shapes=True
-    )
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvf = UVFlag(
+            uvdata_miriad_main,
+            mode='flag',
+            waterfall=True,
+            use_future_array_shapes=True
+        )
     yield uvf
     # clean up when done
     del uvf
@@ -166,7 +176,9 @@ def uvflag_flag_waterfall_miriad(uvflag_flag_waterfall_miriad_main):
 
 @pytest.fixture(scope="session")
 def uvcal_calfits_main():
-    uvc = UVCal.from_file(test_c_file, use_future_array_shapes=True)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvc = UVCal.from_file(test_c_file, use_future_array_shapes=True)
     yield uvc
 
     # clean up when done
@@ -188,9 +200,11 @@ def uvcal_calfits(uvcal_calfits_main):
 
 @pytest.fixture(scope="session")
 def uvflag_metric_calfits_main(uvcal_calfits_main):
-    uvm = UVFlag(
-        uvcal_calfits_main, history='I made this', use_future_array_shapes=True
-    )
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvm = UVFlag(
+            uvcal_calfits_main, history='I made this', use_future_array_shapes=True
+        )
     yield uvm
 
     # clean up when done
@@ -212,7 +226,9 @@ def uvflag_metric_calfits(uvflag_metric_calfits_main):
 
 @pytest.fixture(scope="session")
 def uvflag_flag_calfits_main(uvcal_calfits_main):
-    uvf = UVFlag(uvcal_calfits_main, mode='flag', use_future_array_shapes=True)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvf = UVFlag(uvcal_calfits_main, mode='flag', use_future_array_shapes=True)
     yield uvf
 
     # clean up when done
@@ -234,7 +250,9 @@ def uvflag_flag_calfits(uvflag_flag_calfits_main):
 
 @pytest.fixture(scope="session")
 def uvflag_f_main():
-    uvf = UVFlag(test_f_file, use_future_array_shapes=True)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", "Future array shapes are now always used")
+        uvf = UVFlag(test_f_file, use_future_array_shapes=True)
     yield uvf
 
     # clean up when done
@@ -1042,7 +1060,8 @@ def test_flag(
 
     # test time flagging in baseline type
     # convert to current shapes for test coverage
-    uvm.use_current_array_shapes()
+    if hasattr(uvm, "use_current_array_shapes"):
+        uvm.use_current_array_shapes()
     uvm.metric_array = np.zeros_like(uvm.metric_array)
     times = np.unique(uvm.time_array)
     inds1 = np.where(uvm.time_array == times[0])[0]
@@ -1113,6 +1132,7 @@ def test_unflag():
     assert True
 
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:instrument is not the same")
 def test_flag_apply(
     uvdata_miriad,
@@ -1405,6 +1425,7 @@ def test_xrfi_run_step(tmpdir):
 
 
 # TODO: check whether invalid value encountered in subtract warning is expected
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:invalid value encountered in subtract:RuntimeWarning")
 @pytest.mark.filterwarnings("ignore:Mean of empty slice:RuntimeWarning")
 @pytest.mark.filterwarnings("ignore:Degrees of freedom <= 0 for slice:RuntimeWarning")
@@ -1813,6 +1834,7 @@ def test_xrfi_run(tmpdir):
     for fname in [ocal_file, acal_file, model_file, raw_dfile]:
         os.remove(fname)
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:This object is already a waterfall")
 @pytest.mark.filterwarnings("ignore:x_orientation is not the same")
 def test_xrfi_run_edgeflag(tmpdir):
@@ -1932,6 +1954,7 @@ def test_xrfi_run_edgeflag(tmpdir):
 
 
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:This object is already a waterfall")
 @pytest.mark.filterwarnings("ignore:x_orientation is not the same")
 def test_xrfi_run_multifile(tmpdir):
@@ -2040,6 +2063,7 @@ def test_xrfi_run_multifile(tmpdir):
             if ext == 'flags2.h5':
                 assert not np.all(uvf.flag_array)
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:This object is already a waterfall")
 def test_day_threshold_run(tmpdir):
     # The warnings are because we use UVFlag.to_waterfall() on the total chisquareds
@@ -2110,6 +2134,7 @@ def test_day_threshold_run(tmpdir):
         assert os.path.exists(calfile)
 
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:This object is already a waterfall")
 def test_day_threshold_run_yaml(tmpdir):
     # The warnings are because we use UVFlag.to_waterfall() on the total chisquareds
@@ -2164,6 +2189,7 @@ def test_day_threshold_run_yaml(tmpdir):
 
 @pytest.mark.filterwarnings("ignore:All-NaN slice encountered")
 @pytest.mark.filterwarnings("ignore:instrument is not the same")
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 def test_day_threshold_run_data_only(tmpdir):
     # The warnings are because we use UVFlag.to_waterfall() on the total chisquareds
     # This doesn't hurt anything, and lets us streamline the pipe
@@ -2217,6 +2243,7 @@ def test_day_threshold_run_data_only(tmpdir):
         assert os.path.exists(calfile)
 
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:This object is already a waterfall")
 def test_day_threshold_run_cal_only(tmpdir):
     # The warnings are because we use UVFlag.to_waterfall() on the total chisquareds
@@ -2288,6 +2315,7 @@ def test_day_threshold_run_cal_only(tmpdir):
         assert os.path.exists(calfile)
 
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:instrument is not the same")
 def test_day_threshold_run_omnivis_only(tmpdir):
     # The warnings are because we use UVFlag.to_waterfall() on the total chisquareds
@@ -2655,6 +2683,7 @@ def test_threshold_wf_exceptions(uvflag_f):
     pytest.raises(ValueError, xrfi.threshold_wf, 'foo')  # not a UVFlag object
 
 
+@pytest.mark.filterwarnings("ignore:Future array shapes are now always used")
 @pytest.mark.filterwarnings("ignore:This object is already a waterfall")
 @pytest.mark.filterwarnings("ignore:instrument is not the same")
 def test_xrfi_h3c_idr2_1_run(tmp_path, uvcal_calfits):

hera_qm/utils.py

@@ -734,7 +734,11 @@ def apply_yaml_flags(uv, a_priori_flag_yaml, lat_lon_alt_degrees=None, telescope
         raise NotImplementedError("uv must be a UVData, UVCal, or UVFlag object.")
 
     # this is a no-op if it's already using future shapes
-    uv.use_future_array_shapes()
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "ignore", "Future array shapes are now always used"
+        )
+        uv.use_future_array_shapes()
 
     # if UVCal provided and lst_array is None, get lst_array from times.
     # If lat_lon_alt is not specified, try to infer it from the telescope name, which calfits files generally carry around