Select main lobe 🔭 🛰️

hera_cal/chunker.py

@@ -14,7 +14,7 @@
 
 def chunk_files(filenames, inputfile, outputfile, chunk_size, type="data",
                 polarizations=None, spw_range=None, throw_away_flagged_ants=False,
-                clobber=False, ant_flag_yaml=None):
+                clobber=False, ant_flag_yaml=None, **read_kwargs):
     """Chunk a list of data or cal files together into a single file.
 
     Parameters
@@ -44,7 +44,8 @@ def chunk_files(filenames, inputfile, outputfile, chunk_size, type="data",
         defualt is false.
     flag_yaml : str, optional
         yaml file with list of antennas to flag and throw away if throw_away_flagged_ants is True
-
+    read_kwargs: kwargs dict
+        additional kwargs for for io.HERAData.read()
     Returns
     -------
     None
@@ -68,8 +69,8 @@ def chunk_files(filenames, inputfile, outputfile, chunk_size, type="data",
                 polarizations = chunked_files.pols
         if spw_range is None:
             spw_range = (0, chunked_files.Nfreqs)
-        data, flags, nsamples = chunked_files.read(axis='blt', polarizations=polarizations,
-                                                   freq_chans=range(spw_range[0], spw_range[1]))
+        data, flags, nsamples = chunked_files.read(polarizations=polarizations,
+                                                   freq_chans=range(spw_range[0], spw_range[1]), **read_kwargs)
     elif type == 'gains':
         chunked_files.read()
         if polarizations is None:

hera_cal/delay_filter.py

@@ -97,7 +97,7 @@ def load_delay_filter_and_write(datafile_list, baseline_list=None, calfile_list=
                                 res_outfilename=None, CLEAN_outfilename=None, filled_outfilename=None,
                                 clobber=False, add_to_history='', polarizations=None,
                                 skip_flagged_edges=False, overwrite_flags=False,
-                                flag_yaml=None, **filter_kwargs):
+                                flag_yaml=None, read_axis=None, **filter_kwargs):
     '''
     Uses partial data loading and writing to perform delay filtering.
     While this function reads from multiple files (in datafile_list)
@@ -133,6 +133,8 @@ def load_delay_filter_and_write(datafile_list, baseline_list=None, calfile_list=
         polarizations: list of polarizations to include and write.
         skip_flagged_edges: if true, skip flagged edges in filtering.
         flag_yaml: path to manual flagging text file.
+        read_axis: str
+            str to pass to axis arg for io.HERAData.read(). Default is None
         filter_kwargs: additional keyword arguments to be passed to DelayFilter.run_delay_filter()
     '''
     if baseline_list is not None and Nbls_per_load is not None:
@@ -145,9 +147,9 @@ def load_delay_filter_and_write(datafile_list, baseline_list=None, calfile_list=
     else:
         if baseline_list is None:
             if len(hd.filepaths) > 1:
-                baseline_list = list(hd.bls.values())[0]
+                baseline_list = list(hd.antpairs.values())[0]
             else:
-                baseline_list = hd.bls
+                baseline_list = hd.antpairs
         if spw_range is None:
             spw_range = [0, hd.Nfreqs]
         freqs = hd.freq_array.flatten()[spw_range[0]:spw_range[1]]
@@ -169,7 +171,8 @@ def load_delay_filter_and_write(datafile_list, baseline_list=None, calfile_list=
             Nbls_per_load = len(baseline_list)
         for i in range(0, len(baseline_list), Nbls_per_load):
             df = DelayFilter(hd, input_cal=cals)
-            df.read(bls=baseline_list[i:i + Nbls_per_load], frequencies=freqs)
+            df.read(bls=baseline_list[i:i + Nbls_per_load],
+                    frequencies=freqs, polarizations=polarizations, axis=read_axis)
             if avg_red_bllens:
                 df.avg_red_baseline_vectors()
             if external_flags is not None:

hera_cal/redcal.py

@@ -225,7 +225,7 @@ def split_bls(bls):
         ex_ants = expand_ants(ex_ants)
         bls = set(join_bl(i, j) for i, j in split_bls(bls) if i not in ex_ants and j not in ex_ants)
     bls.union(set(reverse_bl(k) for k in bls))  # put in reverse baselines, just in case
-    reds = [[key for key in gp if key in bls] for gp in reds]
+    reds = [[key for key in gp if key in bls or reverse_bl(key) in bls] for gp in reds]
     reds = [gp for gp in reds if len(gp) > 0]
 
     if min_bl_cut is not None or max_bl_cut is not None:

hera_cal/tests/test_vis_clean.py

@@ -1143,7 +1143,7 @@ def test_time_chunk_from_baseline_chunks(self, tmp_path):
             fragment_filename = tmp_path / fname
             frf.load_tophat_frfilter_and_write(datafiles, baseline_list=baselines, calfile_list=cals,
                                                spw_range=[0, 20], cache_dir=cdir, read_cache=True, write_cache=True,
-                                               res_outfilename=fragment_filename, clobber=True)
+                                               res_outfilename=fragment_filename, clobber=True, case='sky')
             # load in fragment and make sure the number of baselines is equal to the length of the baseline list
             hd_fragment = io.HERAData(str(fragment_filename))
             assert len(hd_fragment.bls) == len(baselines)
@@ -1164,7 +1164,7 @@ def test_time_chunk_from_baseline_chunks(self, tmp_path):
         # compare to xtalk filtering the whole file.
         frf.load_tophat_frfilter_and_write(datafile_list=os.path.join(DATA_PATH, "test_input/zen.2458101.46106.xx.HH.OCR_53x_54x_only.uvh5"),
                                            calfile_list=os.path.join(DATA_PATH, "test_input/zen.2458101.46106.xx.HH.uv.abs.calfits_54x_only"),
-                                           res_outfilename=str(tmp_path / 'temp.h5'), clobber=True, spw_range=[0, 20])
+                                           res_outfilename=str(tmp_path / 'temp.h5'), clobber=True, spw_range=[0, 20], case='sky')
         hd = io.HERAData(str(tmp_path / 'temp.h5'))
         hd.read()
         assert np.all(np.isclose(hd.data_array, hd_reconstituted.data_array))
@@ -1183,7 +1183,7 @@ def test_time_chunk_from_baseline_chunks(self, tmp_path):
         # compare to xtalk filtering the whole file.
         frf.load_tophat_frfilter_and_write(datafile_list=os.path.join(DATA_PATH, "test_input/zen.2458101.46106.xx.HH.OCR_53x_54x_only.uvh5"),
                                            calfile_list=os.path.join(DATA_PATH, "test_input/zen.2458101.46106.xx.HH.uv.abs.calfits_54x_only"),
-                                           res_outfilename=str(tmp_path / 'temp.h5'), clobber=True, spw_range=[0, 20])
+                                           res_outfilename=str(tmp_path / 'temp.h5'), clobber=True, spw_range=[0, 20], case='sky')
         hd = io.HERAData(str(tmp_path / 'temp.h5'))
         hd.read()
         assert np.all(np.isclose(hd.data_array, hd_reconstituted.data_array))

scripts/tophat_frfilter_run.py

@@ -28,15 +28,14 @@
     filter_kwargs['skip_contiguous_flags'] = False
     filter_kwargs['skip_flagged_edges'] = False
     filter_kwargs['flag_model_rms_outliers'] = False
-elif ap.mode == 'dpss_leastsq':
+elif ap.mode == 'dpss_leastsq' or ap.mode == 'dft_leastsq':
     filter_kwargs = {}
     avg_red_bllens = True
     filter_kwargs['skip_contiguous_flags']=True
     filter_kwargs['skip_flagged_edges'] = True
     filter_kwargs['max_contiguous_edge_flags'] = 1
     filter_kwargs['flag_model_rms_outliers'] = True
 
-
 if ap.cornerturnfile is not None:
     baseline_list = io.baselines_from_filelist_position(filename=ap.cornerturnfile, filelist=ap.datafilelist)
 else:
@@ -55,11 +54,12 @@
                                    read_cache=ap.read_cache, mode=ap.mode, res_outfilename=ap.res_outfilename,
                                    factorize_flags=ap.factorize_flags, time_thresh=ap.time_thresh,
                                    add_to_history=' '.join(sys.argv), verbose=ap.verbose,
-                                   flag_yaml=ap.flag_yaml, Nbls_per_load=ap.Nbls_per_load,
+                                   flag_yaml=ap.flag_yaml, Nbls_per_load=ap.Nbls_per_load, case=ap.case,
                                    external_flags=ap.external_flags, filter_spw_ranges=ap.filter_spw_ranges,
                                    overwrite_flags=ap.overwrite_flags, skip_autos=ap.skip_autos,
                                    skip_if_flag_within_edge_distance=ap.skip_if_flag_within_edge_distance,
                                    zeropad=ap.zeropad, tol=ap.tol, skip_wgt=ap.skip_wgt, max_frate_coeffs=ap.max_frate_coeffs,
-                                   frate_width_multiplier=ap.frate_width_multiplier, frate_standoff=ap.frate_standoff,
-                                   min_frate_half_width=ap.min_frate_half_width,
-                                   clean_flags_in_resid_flags=True, **filter_kwargs)
+                                   frate_width_multiplier=ap.frate_width_multiplier, frate_standoff=ap.frate_standoff, fr_freq_skip=ap.fr_freq_skip,
+                                   min_frate_half_width=ap.min_frate_half_width, beamfitsfile=ap.beamfitsfile, percentile_low=ap.percentile_low, percentile_high=ap.percentile_high,
+                                   clean_flags_in_resid_flags=True, pre_filter_modes_between_lobe_minimum_and_zero=ap.pre_filter_modes_between_lobe_minimum_and_zero,
+                                   **filter_kwargs)

setup.py

@@ -41,7 +41,7 @@ def package_files(package_dir, subdirectory):
                 'scripts/smooth_cal_run.py', 'scripts/redcal_run.py',
                 'scripts/auto_reflection_run.py', 'scripts/noise_from_autos.py',
                 'scripts/query_ex_ants.py', 'scripts/red_average.py',
-                'scripts/time_average.py',
+                'scripts/time_average.py', 'scripts/tophat_frfilter_run.py',
                 'scripts/time_chunk_from_baseline_chunks_run.py', 'scripts/chunk_files.py', 'scripts/transfer_flags.py',
                 'scripts/flag_all.py', 'scripts/throw_away_flagged_antennas.py', 'scripts/select_spw_ranges.py'],
     'version': version.version,
@@ -50,6 +50,7 @@ def package_files(package_dir, subdirectory):
         'numpy>=1.10',
         'scipy',
         'astropy',
+        'astropy-healpix',
         'pyuvdata',
         'linsolve @ git+http://github.com/HERA-Team/linsolve',
         'hera_qm @ git+http://github.com/HERA-Team/hera_qm',