24 __all__ = [
"IngestIndexedReferenceConfig",
"IngestIndexedReferenceTask",
"DatasetConfig"]
33 from .indexerRegistry
import IndexerRegistry
34 from .readTextCatalogTask
import ReadTextCatalogTask
38 """!Task runner for the reference catalog ingester 40 Data IDs are ignored so the runner should just run the task on the parsed command. 43 def run(self, parsedCmd):
45 Several arguments need to be collected to send on to the task methods. 47 @param[in] parsedCmd Parsed command including command line arguments. 48 @returns Struct containing the result of the indexing. 50 files = parsedCmd.files
51 butler = parsedCmd.butler
52 task = self.TaskClass(config=self.config, log=self.log, butler=butler)
53 task.writeConfig(parsedCmd.butler, clobber=self.clobberConfig, doBackup=self.doBackup)
55 result = task.create_indexed_catalog(files)
56 if self.doReturnResults:
57 return pipeBase.Struct(
63 ref_dataset_name = pexConfig.Field(
65 default=
'cal_ref_cat',
66 doc=
'String to pass to the butler to retrieve persisted files.',
68 indexer = IndexerRegistry.makeField(
70 doc=
'Name of indexer algoritm to use. Default is HTM',
75 dataset_config = pexConfig.ConfigField(
77 doc=
"Configuration for reading the ingested data",
79 file_reader = pexConfig.ConfigurableField(
80 target=ReadTextCatalogTask,
81 doc=
'Task to use to read the files. Default is to expect text files.' 83 ra_name = pexConfig.Field(
85 doc=
"Name of RA column",
87 dec_name = pexConfig.Field(
89 doc=
"Name of Dec column",
91 mag_column_list = pexConfig.ListField(
93 doc=
"The values in the reference catalog are assumed to be in AB magnitudes. " 94 "List of column names to use for photometric information. At least one entry is required." 96 mag_err_column_map = pexConfig.DictField(
100 doc=
"A map of magnitude column name (key) to magnitude error column (value)." 102 is_photometric_name = pexConfig.Field(
105 doc=
'Name of column stating if satisfactory for photometric calibration (optional).' 107 is_resolved_name = pexConfig.Field(
110 doc=
'Name of column stating if the object is resolved (optional).' 112 is_variable_name = pexConfig.Field(
115 doc=
'Name of column stating if the object is measured to be variable (optional).' 117 id_name = pexConfig.Field(
120 doc=
'Name of column to use as an identifier (optional).' 122 extra_col_names = pexConfig.ListField(
125 doc=
'Extra columns to add to the reference catalog.' 129 pexConfig.Config.validate(self)
131 raise ValueError(
"ra_name and dec_name and at least one entry in mag_column_list must be" +
134 raise ValueError(
"If magnitude errors are provided, all magnitudes must have an error column")
138 """!Class for both producing indexed reference catalogs and for loading them. 140 This implements an indexing scheme based on hierarchical triangular mesh (HTM). 141 The term index really means breaking the catalog into localized chunks called 142 shards. In this case each shard contains the entries from the catalog in a single 145 canMultiprocess =
False 146 ConfigClass = IngestIndexedReferenceConfig
147 RunnerClass = IngestReferenceRunner
148 _DefaultName =
'IngestIndexedReferenceTask' 150 _flags = [
'photometric',
'resolved',
'variable']
153 def _makeArgumentParser(cls):
154 """Create an argument parser 156 This overrides the original because we need the file arguments 158 parser = pipeBase.InputOnlyArgumentParser(name=cls.
_DefaultName)
159 parser.add_argument(
"files", nargs=
"+", help=
"Names of files to index")
163 """!Constructor for the HTM indexing engine 165 @param[in] butler dafPersistence.Butler object for reading and writing catalogs 168 pipeBase.Task.__init__(self, *args, **kwargs)
169 self.
indexer = IndexerRegistry[self.config.dataset_config.indexer.name](
170 self.config.dataset_config.indexer.active)
171 self.makeSubtask(
'file_reader')
174 """!Index a set of files comprising a reference catalog. Outputs are persisted in the 177 @param[in] files A list of file names to read. 181 for filename
in files:
182 arr = self.file_reader.run(filename)
183 index_list = self.
indexer.index_points(arr[self.config.ra_name], arr[self.config.dec_name])
187 dataId = self.
indexer.make_data_id(
'master_schema',
188 self.config.dataset_config.ref_dataset_name)
192 pixel_ids = set(index_list)
193 for pixel_id
in pixel_ids:
194 dataId = self.
indexer.make_data_id(pixel_id, self.config.dataset_config.ref_dataset_name)
196 els = np.where(index_list == pixel_id)
198 record = catalog.addNew()
199 rec_num = self.
_fill_record(record, row, rec_num, key_map)
200 self.
butler.put(catalog,
'ref_cat', dataId=dataId)
201 dataId = self.
indexer.make_data_id(
None, self.config.dataset_config.ref_dataset_name)
202 self.
butler.put(self.config.dataset_config,
'ref_cat_config', dataId=dataId)
206 """!Create an ICRS SpherePoint from a np.array row 207 @param[in] row dict like object with ra/dec info in degrees 208 @param[in] ra_name name of RA key 209 @param[in] dec_name name of Dec key 210 @returns ICRS SpherePoint constructed from the RA/Dec values 214 def _set_flags(self, record, row, key_map):
215 """!Set the flags for a record. Relies on the _flags class attribute 216 @param[in,out] record SourceCatalog record to modify 217 @param[in] row dict like object containing flag info 218 @param[in] key_map Map of catalog keys to use in filling the record 220 names = record.schema.getNames()
223 attr_name =
'is_{}_name'.format(flag)
224 record.set(key_map[flag], bool(row[getattr(self.config, attr_name)]))
226 def _set_mags(self, record, row, key_map):
227 """!Set the flux records from the input magnitudes 228 @param[in,out] record SourceCatalog record to modify 229 @param[in] row dict like object containing magnitude values 230 @param[in] key_map Map of catalog keys to use in filling the record 232 for item
in self.config.mag_column_list:
233 record.set(key_map[item+
'_flux'], fluxFromABMag(row[item]))
234 if len(self.config.mag_err_column_map) > 0:
235 for err_key
in self.config.mag_err_column_map.keys():
236 error_col_name = self.config.mag_err_column_map[err_key]
237 record.set(key_map[err_key+
'_fluxSigma'],
238 fluxErrFromABMagErr(row[error_col_name], row[err_key]))
240 def _set_extra(self, record, row, key_map):
241 """!Copy the extra column information to the record 242 @param[in,out] record SourceCatalog record to modify 243 @param[in] row dict like object containing the column values 244 @param[in] key_map Map of catalog keys to use in filling the record 246 for extra_col
in self.config.extra_col_names:
247 value = row[extra_col]
255 if isinstance(value, np.str_):
257 record.set(key_map[extra_col], value)
259 def _fill_record(self, record, row, rec_num, key_map):
260 """!Fill a record to put in the persisted indexed catalogs 262 @param[in,out] record afwTable.SourceRecord in a reference catalog to fill. 263 @param[in] row A row from a numpy array constructed from the input catalogs. 264 @param[in] rec_num Starting integer to increment for the unique id 265 @param[in] key_map Map of catalog keys to use in filling the record 267 record.setCoord(self.
compute_coord(row, self.config.ra_name, self.config.dec_name))
268 if self.config.id_name:
269 record.setId(row[self.config.id_name])
272 record.setId(rec_num)
282 """!Get a catalog from the butler or create it if it doesn't exist 284 @param[in] dataId Identifier for catalog to retrieve 285 @param[in] schema Schema to use in catalog creation if the butler can't get it 286 @returns table (an lsst.afw.table.SourceCatalog) for the specified identifier 288 if self.
butler.datasetExists(
'ref_cat', dataId=dataId):
289 return self.
butler.get(
'ref_cat', dataId=dataId)
290 return afwTable.SourceCatalog(schema)
293 """!Make the schema to use in constructing the persisted catalogs. 295 @param[in] dtype A np.dtype to use in constructing the schema 296 @returns a pair of items: 297 - The schema for the output source catalog. 298 - A map of catalog keys to use in filling the record 301 mag_column_list = self.config.mag_column_list
302 mag_err_column_map = self.config.mag_err_column_map
303 if len(mag_err_column_map) > 0
and (
304 not len(mag_column_list) == len(mag_err_column_map)
or 305 not sorted(mag_column_list) == sorted(mag_err_column_map.keys())):
306 raise ValueError(
"Every magnitude column must have a corresponding error column")
308 schema = afwTable.SourceTable.makeMinimalSchema()
311 if dtype[name].kind ==
'U': 314 at_size = dtype[name].itemsize
315 return schema.addField(name, type=at_type, size=at_size)
317 at_type = dtype[name].type
318 return schema.addField(name, at_type)
320 for item
in mag_column_list:
321 key_map[item+
'_flux'] = schema.addField(item+
'_flux', float)
322 if len(mag_err_column_map) > 0:
323 for err_item
in mag_err_column_map.keys():
324 key_map[err_item+
'_fluxSigma'] = schema.addField(err_item+
'_fluxSigma', float)
326 attr_name =
'is_{}_name'.format(flag)
327 if getattr(self.config, attr_name):
328 key_map[flag] = schema.addField(flag,
'Flag')
329 for col
in self.config.extra_col_names:
330 key_map[col] = add_field(col)
331 return schema, key_map
def create_indexed_catalog(self, files)
Index a set of files comprising a reference catalog.
def _fill_record(self, record, row, rec_num, key_map)
Fill a record to put in the persisted indexed catalogs.
def make_schema(self, dtype)
Make the schema to use in constructing the persisted catalogs.
def _set_mags(self, record, row, key_map)
Set the flux records from the input magnitudes.
def _set_extra(self, record, row, key_map)
Copy the extra column information to the record.
def get_catalog(self, dataId, schema)
Get a catalog from the butler or create it if it doesn't exist.
def compute_coord(row, ra_name, dec_name)
Create an ICRS SpherePoint from a np.array row.
Class for both producing indexed reference catalogs and for loading them.
def run(self, parsedCmd)
Run the task.
Task runner for the reference catalog ingester.
def _set_flags(self, record, row, key_map)
Set the flags for a record.
def __init__(self, args, kwargs)
Constructor for the HTM indexing engine.