ReadTextCatalogTask¶
ReadTextCatalogTask
reads an object catalog from a UTF-8 encoded text file into a numpy array object suitable for use with lsst.meas.algorithms.IngestIndexReferenceTask
.
Python API summary¶
from lsst.meas.algorithms.readTextCatalogTask import ReadTextCatalogTask
-
class
(config: Optional[Config] = None, name: Optional[str] = None, parentTask: Optional[Task] = None, log: Optional[Union[logging.Logger, lsst.utils.logging.LsstLogAdapter]] = None)ReadTextCatalogTask
Read an object catalog from a text file
...
-
attribute
config
Access configuration fields and retargetable subtasks.
See also
See the ReadTextCatalogTask
API reference for complete details.
Retargetable subtasks¶
No subtasks.
Configuration fields¶
colnames¶
An ordered list of column names to use in ingesting the catalog. With an empty list, column names will be discovered from the first line after the skipped header lines.
delimiter¶
Delimiter to use when reading text reference files. Comma is default.
fill_values¶
A list giving [<match_string>, <fill_value>], which is used to mask the given values in the input file. ‘0’ is suggested for the fill value in order to prevent changing the column datatype. The default behavior is to fill empty data with zeros. See https://docs.astropy.org/en/stable/io/ascii/read.html#bad-or-missing-values for more details.Use
replace_missing_floats_with_nan
to change floats to NaN instead of <fill_value>.format¶
Format of files to read, from the astropy.table I/O list here:http://docs.astropy.org/en/stable/io/unified.html#built-in-table-readers-writers
header_lines¶
Number of lines to skip when reading the text reference file.
replace_missing_floats_with_nan¶
If True, replace missing data in float columns with NaN instead of zero. If
fill_values
is set, this parameter with replace the floats identified as missing by fill_values
, and the fill value from fill_values
will be overridden with NaN for floats.Examples¶
- Given a file named
table.csv
containing the following: - ra, dec, flux 5.5, -45.2, 12453 19.6, 34.2, 32123
you can read this file with the following code:
from lsst.meas.algorithms.readTextCatalogTask import ReadTextCatalogTask
task = ReadTextCatalogTask()
catalogArray = task.run("table.csv")
The resulting catalogArray
is a numpy structured array containing three fields
(“ra”, “dec” and “flux”) and two rows of data. For more complex cases,
config parameters allow you to specify the names of the columns (instead of using automatic discovery)
and set the number of rows to skip.