Reader for matched-table catalog and config files for composite add-o…

GCRCatalogs/catalog_configs/dc2_object_run2.1.1i_matched.yaml

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+subclass_name: dc2_matched_table.DC2MatchedTable
+filename: '/global/projecta/projectdirs/lsst/groups/SSim/DC2/matched_ids_run2.1.1i_dpdd.fits.gz'
+version: '2.1.1i'
+truth_version: 'cosmoDC2_v1.1.4'
+object_id: 'objectId'
+truth_id: 'truthId'
+match_flag: 'is_matched'
+is_star: 'is_star'
+creator: 'Javier Sanchez'
+description: 'This is the table of matches between the object catalog and the extragalactic catalog'

GCRCatalogs/catalog_configs/dc2_object_run2.1.1i_matched_addon.yaml

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+subclass_name: composite.CompositeReader
+description: DC2 Run 2.1.1i Object Catalog Matched Table addon catalog
+creators: ['Javi Sanchez', 'Eve Kovacs']
+catalogs:
+  - catalog_name: dc2_object_run2.1i_dr1
+    matching_method: objectId
+  - catalog_name: dc2_object_run2.1.1i_matched 
+    matching_method: objectId

GCRCatalogs/dc2_matched_table.py

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+"""
+DC2 matched table reader
+
+This reader was written by Eve Kovacs
+based on a matching table provided by Javier Sanchez .
+"""
+
+import numpy as np
+import numpy.ma as ma
+from astropy.io import fits
+from GCRCatalogs import BaseGenericCatalog
+
+__all__ = ['DC2MatchedTable']
+
+class DC2MatchedTable(BaseGenericCatalog):
+
+    def _subclass_init(self, **kwargs):
+
+        """
+        DC2MatchedTable reader, inherited from BaseGenericCatalog class 
+        """
+        self._filename = kwargs.get('filename', None)
+        if not self._filename:
+            print('Filename for matching table required')
+            return
+        object_id = kwargs.get('object_id', 'objectId')
+        truth_id = kwargs.get('truth_id', 'truthId')
+        match_flag = kwargs.get('match_flag', 'is_matched')
+        is_star = kwargs.get('is_star', 'is_star')
+        self._version = kwargs.get('version', '')
+        self._truth_version = kwargs.get('truth_version', '')
+
+        # check matched table quantities
+        with fits.open(self._filename) as hdul:
+            cols = hdul[1].columns.names
+            if not object_id in cols or not match_flag in cols or not is_star in cols or not truth_id in cols:
+                print('Matching table does not have minimal expected columns')
+                return
+
+            self._galaxy_match_mask = (~hdul[1].data[is_star]) & (hdul[1].data[match_flag])
+            self._matched_galaxy_count = np.count_nonzero(self._galaxy_match_mask)
+            self._star_match_mask = (hdul[1].data[is_star]) & (hdul[1].data[match_flag])
+            self._matched_star_count = np.count_nonzero(self._star_match_mask)
+
+        # modify native quantities
+        self._quantity_modifiers = {}
+        modified_quantity_list = [c for c in cols if not is_star in c and not match_flag in c]
+        for q in modified_quantity_list:
+            self._quantity_modifiers[q + '_galaxy'] =  (lambda x: x[self._galaxy_match_mask], q)
+            self._quantity_modifiers[q + '_star'] =  (lambda x: x[self._star_match_mask], q)
+
+
+    def _generate_native_quantity_list(self):
+        """
+        Return an iterable of all native quantity names.
+        """
+        with fits.open(self._filename) as hdul:
+            return hdul[1].columns.names
+
+
+    def _iter_native_dataset(self, native_filters=None):
+        """
+        Must yield a callable, *native_quantity_getter*.
+        Must return a numpy 1d array.
+        """
+        assert not native_filters, '*native_filters* is not supported'
+        with fits.open(self._filename) as hdul:
+            def native_quantity_getter(native_quantity):
+                return hdul[1].data[native_quantity]
+            yield native_quantity_getter