Coverage for python/lsst/meas/algorithms/readTextCatalogTask.py : 64%

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1#
2# LSST Data Management System
3#
4# Copyright 2008-2017 AURA/LSST.
5#
6# This product includes software developed by the
7# LSST Project (http://www.lsst.org/).
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the LSST License Statement and
20# the GNU General Public License along with this program. If not,
21# see <https://www.lsstcorp.org/LegalNotices/>.
22#
24__all__ = ["ReadTextCatalogConfig", "ReadTextCatalogTask"]
26import numpy as np
27from astropy.table import Table
29import lsst.pex.config as pexConfig
30import lsst.pipe.base as pipeBase
33class ReadTextCatalogConfig(pexConfig.Config):
34 header_lines = pexConfig.Field(
35 dtype=int,
36 default=0,
37 doc='Number of lines to skip when reading the text reference file.'
38 )
39 colnames = pexConfig.ListField(
40 dtype=str,
41 default=[],
42 doc="An ordered list of column names to use in ingesting the catalog. "
43 "With an empty list, column names will be discovered from the first line "
44 "after the skipped header lines."
45 )
46 delimiter = pexConfig.Field(
47 dtype=str,
48 default=',',
49 doc='Delimiter to use when reading text reference files. Comma is default.'
50 )
51 format = pexConfig.Field(
52 dtype=str,
53 default='csv',
54 doc=("Format of files to read, from the astropy.table I/O list here:"
55 "http://docs.astropy.org/en/stable/io/unified.html#built-in-table-readers-writers")
56 )
58## @addtogroup LSST_task_documentation
59## @{
60## @page ReadTextCatalogTask
61## @ref ReadTextCatalogTask_ "ReadTextCatalogTask"
62## @copybrief ReadTextCatalogTask
63## @}
66class ReadTextCatalogTask(pipeBase.Task):
67 r"""!Read an object catalog from a text file
69 @anchor ReadTextCatalogTask_
71 @section meas_algorithms_readTextCatalog_Contents Contents
73 - @ref meas_algorithms_readTextCatalog_Purpose
74 - @ref meas_algorithms_readTextCatalog_Initialize
75 - @ref meas_algorithms_readTextCatalog_Config
76 - @ref meas_algorithms_readTextCatalog_Example
78 @section meas_algorithms_readTextCatalog_Purpose Description
80 Read an object catalog from a text file. Designed to read foreign catalogs
81 so they can be written out in a form suitable for IngestIndexedReferenceTask.
83 The file is assumed to be encoded as UTF-8 (which is compatible with ASCII).
85 @section meas_algorithms_readTextCatalog_Initialize Task initialisation
87 @copydoc \_\_init\_\_
89 @section meas_algorithms_readTextCatalog_Config Configuration parameters
91 See @ref ReadTextCatalogConfig
93 @section meas_algorithms_readTextCatalog_Example A complete example of using ReadTextCatalogTask
95 Given a file named `table.csv` containing the following:
97 ra, dec, flux
98 5.5, -45.2, 12453
99 19.6, 34.2, 32123
101 you can read this file with the following code:
103 from lsst.meas.algorithms.readTextCatalogTask import ReadTextCatalogTask
104 task = ReadTextCatalogTask()
105 catalogArray = task.run("table.csv")
107 The resulting `catalogArray` is a numpy structured array containing three fields
108 ("ra", "dec" and "flux") and two rows of data. For more complex cases,
109 config parameters allow you to specify the names of the columns (instead of using automatic discovery)
110 and set the number of rows to skip.
111 """
112 _DefaultName = 'readCatalog'
113 ConfigClass = ReadTextCatalogConfig
115 def run(self, filename):
116 """Read an object catalog from the specified text file
118 @param[in] filename path to text file
119 @return a numpy structured array containing the specified columns
120 """
121 kwargs = {}
122 if self.config.colnames:
123 kwargs['names'] = self.config.colnames
124 # if we specify the column names, then we need to just ignore the header lines.
125 kwargs['data_start'] = self.config.header_lines
126 else:
127 # if we don't specify column names, start the header at this line.
128 kwargs['header_start'] = self.config.header_lines
130 # return a numpy array for backwards compatibility with other readers
131 return np.array(Table.read(filename, format=self.config.format,
132 delimiter=self.config.delimiter,
133 **kwargs).as_array())