Fix a SSINS test for future pyuvdata compatibility

.github/workflows/testsuite.yml

@@ -19,15 +19,17 @@ jobs:
         os: [ubuntu-latest, macos-latest, windows-latest]
         python-version: [3.9, "3.10", "3.11", "3.12"]
     steps:
-      - uses: actions/checkout@master
+      - uses: actions/checkout@main
         with:
           fetch-depth: 1
 
-      - name: Setup Miniconda
+      - name: Setup Minimamba
         uses: conda-incubator/setup-miniconda@v2
         with:
           auto-update-conda: true
           miniconda-version: "latest"
+          miniforge-variant: Mambaforge
+          use-mamba: true
           python-version: ${{ env.PYTHON }}
           environment-file: ci/${{ env.ENV_NAME }}.yml
           activate-environment: ${{ env.ENV_NAME }}
@@ -42,16 +44,54 @@ jobs:
           fi
       - name: Install
         run: |
-          pip install .
+          pip install --no-deps .
       - name: Run Tests
         run: |
           python -m pytest --cov=SSINS --cov-config=.coveragerc --cov-report xml:./coverage.xml --junitxml=test-reports/xunit.xml
-      - name: Doc Tests
-        run: |
-          python -m pytest docs/tutorial.rst
       - name: Upload Coverage
         uses: codecov/codecov-action@v1
         with:
           token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos
           files: ./coverage.xml
           verbose: true
+
+  docs_test:
+    env:
+      ENV_NAME: SSINS_tests
+      PYTHON: "3.11"
+    name: Doc Testing
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        # Adding -l {0} helps ensure conda can be found properly.
+        shell: bash -l {0}
+    strategy:
+      fail-fast: false
+    steps:
+      - uses: actions/checkout@main
+        with:
+          fetch-depth: 1
+
+      - name: Setup Minimamba
+        uses: conda-incubator/setup-miniconda@v2
+        with:
+          auto-update-conda: true
+          miniconda-version: "latest"
+          miniforge-variant: Mambaforge
+          use-mamba: true
+          python-version: ${{ env.PYTHON }}
+          environment-file: ci/${{ env.ENV_NAME }}.yml
+          activate-environment: ${{ env.ENV_NAME }}
+
+      - name: Conda Info
+        run: |
+          conda info -a
+          conda list
+          PYVER=`python -c "import sys; print('{:d}.{:d}'.format(sys.version_info.major, sys.version_info.minor))"`
+          if [[ $PYVER != ${{ env.PYTHON }} ]]; then
+            exit 1;
+          fi
+      - name: Install
+        run: pip install --no-deps .
+      - name: Doc Tests
+        run: python -m pytest docs/tutorial.rst

SSINS/incoherent_noise_spectrum.py

@@ -19,7 +19,7 @@ class INS(UVFlag):
     the UVFlag class, a member of the pyuvdata software package.
     """
 
-    def __init__(self, indata=None, history="", label="", use_future_array_shapes=False, run_check=True,
+    def __init__(self, indata=None, history="", label="", run_check=True,
                  check_extra=True, run_check_acceptability=True, order=0, mask_file=None,
                  match_events_file=None, spectrum_type="cross",
                  use_integration_weights=False, nsample_default=1, **kwargs):
@@ -32,8 +32,6 @@ def __init__(self, indata=None, history="", label="", use_future_array_shapes=Fa
                 saved INS object. If None, initializes an empty object.
             history (str): History to append to object's history string.
             label (str): String used for labeling the object (e.g. 'MWA Highband').
-            use_future_array_shapes (bool): Option to convert to the future planned array shapes before the changes go
-                into effect by removing the spectral window axis (potentially necessary for initializing from SS).
             run_check (bool): Whether to check that the object's parameters have the right shape (default True).
             check_extra (bool): Whether to also check optional parameters (default True)
             run_check_acceptability (bool): Whether to check that the object's parameters take appropriate values 
@@ -58,13 +56,12 @@ def __init__(self, indata=None, history="", label="", use_future_array_shapes=Fa
 
         self.set_extra_params(order=order, spectrum_type=spectrum_type, use_integration_weights=use_integration_weights,
                               nsample_default=nsample_default, mask_file=mask_file, match_events_file=match_events_file)
-
         super().__init__(indata=indata, mode='metric', copy_flags=False, waterfall=False, history=history, label=label, 
-                         use_future_array_shapes=use_future_array_shapes, run_check=run_check, check_extra=check_extra,
+                         use_future_array_shapes=True, run_check=run_check, check_extra=check_extra,
                          run_check_acceptability=run_check_acceptability, **kwargs)
 
 
-    def read(self, filename, history="", use_future_array_shapes=False, run_check=True, check_extra=True,
+    def read(self, filename, history="", run_check=True, check_extra=True,
              run_check_acceptability=True, **kwargs):
         """
         Populate the object by reading a file. This is called during instantiation, but due to inheritance issues, is not
@@ -74,8 +71,6 @@ def read(self, filename, history="", use_future_array_shapes=False, run_check=Tr
         Args:
             filename (str): Path to the file to be read.
             history (str): History to be appended to the object's history string.
-            use_future_array_shapes (bool): Whether to assume a spectral index axis -- should do nothing since all INS
-                objects should be written out in waterfall mode.
             run_check (bool): Whether to check that the object's parameters have the right shape (default True).
             check_extra (bool): Whether to also check optional parameters (default True)
             run_check_acceptability (bool): Whether to check that the object's parameters take appropriate values 
@@ -92,7 +87,8 @@ def read(self, filename, history="", use_future_array_shapes=False, run_check=Tr
         attrs = ("order", "use_integration_weights", "nsample_default", "mask_file", "match_events_file", "spectrum_type", "spec_type_str")
         attr_dict = {attr: deepcopy(getattr(self, attr)) for attr in attrs}
 
-        super().read(filename, history=history, use_future_array_shapes=use_future_array_shapes, run_check=run_check,
+        kwargs.pop("use_future_array_shapes", None)
+        super().read(filename, history=history, use_future_array_shapes=True, run_check=run_check,
                      check_extra=check_extra, run_check_acceptability=run_check_acceptability, **kwargs)
 
         self._pol_check()
@@ -118,7 +114,7 @@ def read(self, filename, history="", use_future_array_shapes=False, run_check=Tr
             self.metric_array.mask = self.weights_array == 0
         else:
             # Read in the flag array
-            flag_uvf = UVFlag(self.mask_file)
+            flag_uvf = UVFlag(self.mask_file, use_future_array_shapes=True)
             self.metric_array.mask = np.copy(flag_uvf.flag_array)
             del flag_uvf
 
@@ -210,7 +206,7 @@ def _pol_check(self):
                                 " currently support pseudo-Stokes spectra.")
 
     def from_uvdata(self, indata, mode="metric", copy_flags=False, waterfall=False, history="",
-                    label="", use_future_array_shapes=False, run_check=True, check_extra=True,
+                    label="", run_check=True, check_extra=True,
                     run_check_acceptability=True, **kwargs):
         """
         Construct an INS object from a UVData (SS) object. This is called during instantiation, but due to inheritance 
@@ -223,8 +219,6 @@ def from_uvdata(self, indata, mode="metric", copy_flags=False, waterfall=False,
             copy_flags (bool): Does nothing -- for compatibility with base class.
             waterfall (bool): Does nothing -- for compatibility with base class.
             history (str): History to be appended to history string of object.
-            use_future_array_shapes (bool): Option to convert to the future planned array shapes before the changes go
-                into effect by removing the spectral window axis (potentially necessary for initializing from SS).
             run_check (bool): Whether to check that the object's parameters have the right shape (default True).
             check_extra (bool): Whether to also check optional parameters (default True)
             run_check_acceptability (bool): Whether to check that the object's parameters take appropriate values 
@@ -235,8 +229,9 @@ def from_uvdata(self, indata, mode="metric", copy_flags=False, waterfall=False,
         self._has_data_params_check()
         # Must be in metric mode, do not copy flags -- have own flag handling
         # will turn to waterfall later. These are just here to match signature.
+        kwargs.pop("use_future_array_shapes", None)
         super().from_uvdata(indata, mode="metric", copy_flags=False, waterfall=False, 
-                            history=history, label=label, use_future_array_shapes=use_future_array_shapes,
+                            history=history, label=label, use_future_array_shapes=True,
                             run_check=run_check, check_extra=check_extra, run_check_acceptability=run_check_acceptability,
                             **kwargs)
 
@@ -255,7 +250,7 @@ def from_uvdata(self, indata, mode="metric", copy_flags=False, waterfall=False,
             # Set nsample default if some are zero
             indata.nsample_array[indata.nsample_array == 0] = self.nsample_default
             # broadcast problems with single pol
-            self.weights_array *= (indata.integration_time[:, np.newaxis, np.newaxis, np.newaxis] * indata.nsample_array)
+            self.weights_array *= (indata.integration_time[:, np.newaxis, np.newaxis] * indata.nsample_array)
 
         cross_bool = self.ant_1_array != self.ant_2_array
         auto_bool = self.ant_1_array == self.ant_2_array

SSINS/sky_subtract.py

@@ -45,7 +45,8 @@ def read(self, filename, diff=False, flag_choice=None, INS=None, custom=None,
         warnings.warn("SS.read will be renamed to SS.read_data soon to avoid"
                       " conflicts with UVData.read.", category=PendingDeprecationWarning)
 
-        super().read(filename, **kwargs)
+        kwargs.pop("use_future_array_shapes", None)
+        super().read(filename, use_future_array_shapes=True, **kwargs)
         if self.Nphase > 1:
             raise NotImplementedError("SSINS cannot handle files with more than one phase center.")
 
@@ -92,7 +93,7 @@ def apply_flags(self, flag_choice=None, INS=None, custom=None):
                 # Skip if nothing to flag
                 if len(freq_inds) > 0:
                     blt_inds = np.where(self.time_array == time)
-                    self.data_array.mask[blt_inds, :, freq_inds, pol_inds] = True
+                    self.data_array.mask[blt_inds, freq_inds, pol_inds] = True
         elif flag_choice == 'custom':
             self.data_array.mask[:] = False
             if custom is not None:
@@ -181,14 +182,14 @@ def diff(self, flag_choice=None, INS=None, custom=None):
             blend = bltaxisboundaries2[bl_num + 1]                                # index in baseline-time axis to end
 
             blt_slice = slice(blstart, blstart + len_diff)
-            self.data_array[blt_slice, :, :, :] = diff_dat
+            self.data_array[blt_slice] = diff_dat
             """The differenced visibilities. Complex array of shape (Nblts, Nspws, Nfreqs, Npols)."""
-            self.flag_array[blt_slice, :, :, :] = diff_flags
+            self.flag_array[blt_slice] = diff_flags
             """The flag array, which results from boolean OR of the flags corresponding to visibilities that are differenced from one another."""
 
             self.time_array[blt_slice] = diff_times
             """The center time of the differenced visibilities. Length Nblts."""
-            self.nsample_array[blt_slice, :, :, :] = diff_nsamples
+            self.nsample_array[blt_slice] = diff_nsamples
             """See pyuvdata documentation. Here we average the nsample_array of the visibilities that are differenced"""
 
             where_bl = np.where(self.baseline_array == bl)
@@ -245,7 +246,7 @@ def MLE_calc(self):
         frequency. Used for developing a mixture fit.
         """
 
-        self.MLE = np.sqrt(0.5 * np.mean(np.absolute(self.data_array)**2, axis=(0, 1, -1)))
+        self.MLE = np.sqrt(0.5 * np.mean(np.absolute(self.data_array)**2, axis=(0, -1)))
 
     def mixture_prob(self, bins):
         """
@@ -265,7 +266,7 @@ def mixture_prob(self, bins):
         if type(bins) == str:
             _, bins = np.histogram(np.abs(self.data_array[np.logical_not(self.data_array.mask)]))
 
-        N_spec = np.sum(np.logical_not(self.data_array.mask), axis=(0, 1, -1))
+        N_spec = np.sum(np.logical_not(self.data_array.mask), axis=(0, -1))
         N_total = np.sum(N_spec)
 
         # Calculate the fraction belonging to each frequency
@@ -345,7 +346,9 @@ def write(self, filename_out, file_type_out, UV=None, filename_in=None,
             self.reorder_blts(order='baseline')
         if UV is None:
             UV = UVData()
-            UV.read(filename_in, **read_kwargs)
+            UV.read(filename_in, use_future_array_shapes=True, **read_kwargs)
+        else:
+            UV.use_future_array_shapes()
 
         # Option to keep old flags
         if not combine:

SSINS/tests/test_INS.py

@@ -137,22 +137,22 @@ def test_mask_to_flags(tmp_path, tv_obs, tv_testfile):
     ss.read(tv_testfile, diff=True)
 
     uvd = UVData()
-    uvd.read(tv_testfile)
+    uvd.read(tv_testfile, use_future_array_shapes=True)
 
-    uvf = UVFlag(uvd, mode='flag', waterfall=True)
+    uvf = UVFlag(uvd, mode='flag', waterfall=True, use_future_array_shapes=True)
     # start with some flags so that we can test the intended OR operation
     uvf.flag_array[6, :] = True
     ins = INS(ss)
 
     # Check error handling
     with pytest.raises(ValueError):
-        bad_uvf = UVFlag(uvd, mode='metric', waterfall=True)
+        bad_uvf = UVFlag(uvd, mode='metric', waterfall=True, use_future_array_shapes=True)
         err_uvf = ins.flag_uvf(uvf=bad_uvf)
     with pytest.raises(ValueError):
-        bad_uvf = UVFlag(uvd, mode='flag', waterfall=False)
+        bad_uvf = UVFlag(uvd, mode='flag', waterfall=False, use_future_array_shapes=True)
         err_uvf = ins.flag_uvf(uvf=bad_uvf)
     with pytest.raises(ValueError):
-        bad_uvf = UVFlag(uvd, mode='flag', waterfall=True)
+        bad_uvf = UVFlag(uvd, mode='flag', waterfall=True, use_future_array_shapes=True)
         # Pretend the data is off by 1 day
         bad_uvf.time_array += 1
         err_uvf = ins.flag_uvf(uvf=bad_uvf)
@@ -191,7 +191,7 @@ def test_mask_to_flags(tmp_path, tv_obs, tv_testfile):
 
     # Test write/read
     ins.write(prefix, output_type='flags', uvf=uvf)
-    read_uvf = UVFlag(flags_outfile, mode='flag', waterfall=True)
+    read_uvf = UVFlag(flags_outfile, mode='flag', waterfall=True, use_future_array_shapes=True)
     # Check equality
     assert read_uvf == uvf, "UVFlag object differs after read"
 
@@ -338,8 +338,19 @@ def test_spectrum_type_file_init(cross_testfile, tv_ins_testfile):
 
 def test_old_file():
     old_ins_file = os.path.join(DATA_PATH, "1061313128_99bl_1pol_half_time_old_SSINS.h5")
-    with pytest.raises(ValueError, match="Required UVParameter _antenna_names has not been set."):
-        ins = INS(old_ins_file)
+    try:
+        # this works with pyuvdata>=3.0
+        with pytest.raises(
+            ValueError, match="Required UVParameter _Nants has not been set."
+        ):
+            ins = INS(old_ins_file)
+    except AssertionError:
+        # this works with pyuvdata<3.0
+        with pytest.raises(
+            ValueError, match="Required UVParameter _antenna_names has not been set."
+        ):
+            ins = INS(old_ins_file)
+
 
     with pytest.raises(ValueError, 
                        match="spectrum_type is set to auto, but file input is a cross spectrum from an old file."):