Source code for mpdaf.sdetect.catalog

"""
Copyright (c) 2010-2018 CNRS / Centre de Recherche Astrophysique de Lyon
Copyright (c) 2015-2017 Laure Piqueras <laure.piqueras@univ-lyon1.fr>
Copyright (c) 2015-2019 Simon Conseil <simon.conseil@univ-lyon1.fr>
Copyright (c) 2015-2018 Roland Bacon <roland.bacon@univ-lyon1.fr>
Copyright (c) 2018-2019 David Carton <cartondj@gmail.com>

All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors
   may be used to endorse or promote products derived from this software
   without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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"""

import glob
import logging
import numpy as np
import os
import sys

from astropy.coordinates import SkyCoord
from astropy.table import Table, Column, MaskedColumn, hstack, vstack, join
from astropy import units as u

from ..tools import LowercaseOrderedDict

INVALID = {
    type(1): -9999, np.int_: -9999, np.int32: -9999,
    type(1.0): np.nan, np.float_: np.nan,
    type('1'): '', np.str_: '',
    type(False): -9999, np.bool_: -9999
}

# List of required keywords and their type
MANDATORY_KEYS = ['ID', 'RA', 'DEC', 'FROM', 'FROM_V', 'CUBE', 'CUBE_V']
MANDATORY_TYPES = [int, np.float64, np.float64, str, str, str, str]
# List of exluded keywords
EXCLUDED_CARDS = {'SIMPLE', 'BITPIX', 'NAXIS', 'EXTEND', 'DATE', 'AUTHOR'}


[docs]class Catalog(Table): """This class inherits from `astropy.table.Table`. Its goal is to manage a list of objects. """ # These are default column names to be used if not provided by metadata. # They are not stored in the meta directly, and therefore not written when # the catalog is written to disk. _idname_default = 'ID' _raname_default = 'RA' _decname_default = 'DEC' def __init__(self, *args, **kwargs): """Initialize a Catalog instance Parameters ---------- idname : str, optional Table column name containing object IDs raname : str, optional Table column name containing object RA coords decname : str, optional Table column name containing object DEC coords Remaining args and kwargs are passed to `astropy.table.Table.__init__`. """ # pop kwargs for PY2 compatibility idname = kwargs.pop('idname', None) raname = kwargs.pop('raname', None) decname = kwargs.pop('decname', None) super(Catalog, self).__init__(*args, **kwargs) self._logger = logging.getLogger(__name__) if self.masked: self.masked_invalid() # replace Table.meta OrderedDict with a case insensitive version self.meta = LowercaseOrderedDict(self.meta) # set column names in metadata if idname is not None: self.meta['idname'] = idname if raname is not None: self.meta['raname'] = raname if decname is not None: self.meta['decname'] = decname @staticmethod def _merge_meta(catalogs, join_keys=None, suffix=None): """Returns a metadata object combined from a set of catalogs. Parameters ---------- catalogs : list< `mpdaf.sdetect.Catalog` > List of `mpdaf.sdetect.Catalog` objects to be combined suffix : list< str > Column suffixes that are appended column names when tables are joined. Must be the same length as the number of catalogs. Defaults to ['_1', '_2', '_3', etc.] """ if join_keys is None: join_keys = [] n_cat = len(catalogs) if suffix is None: suffix = tuple(['_{}'.format(i + 1) for i in range(n_cat)]) cat0 = catalogs[0] # create output with same type as meta of first catalog out = type(cat0.meta)() n_cat = len(catalogs) for i_cat, cat in enumerate(catalogs): s = suffix[i_cat] for key, value in cat.meta.items(): out[key + s] = value # special treatment for keys that identify columns col_keys = ['idname', 'raname', 'decname'] for i_cat, cat in enumerate(catalogs): for key in col_keys: # check key exists try: col_name = cat.meta[key] except KeyError: continue # check actually found in catalog if col_name not in cat.columns: continue # is col_name supposed to be joined if col_name not in join_keys: # check if name is dupilcated in other catalogs, and thus a # suffix is needed n = sum([1 for c in catalogs if col_name in c.columns]) if n > 1: # not unique key += suffix[i_cat] col_name += suffix[i_cat] out[key] = col_name # set default column keys to the first table # e.g. raname = raname_1 for key in col_keys: try: out[key] = out[key + suffix[0]] except KeyError: pass return out
[docs] @classmethod def from_sources(cls, sources, fmt='default'): """Construct a catalog from a list of source objects. The new catalog will contain all data stored in the primary headers and in the tables extensions of the sources: * a column per header fits ('SIMPLE', 'BITPIX', 'NAXIS', 'EXTEND', 'DATE', 'AUTHOR', 'COM*' and 'HIST*' are excluded) * two columns per magnitude band: [BAND] [BAND]_ERR * three columns per redshift Z_[Z_DESC], Z_[Z_DESC]_MIN and Z_[Z_DESC]_MAX * several columns per line. The lines columns depend of the format. By default the columns names are created around unique LINE name [LINE]_[LINES columns names]. But it is possible to use a working format. [LINES columns names]_xxx where xxx is the number of lines present in each source. Parameters ---------- sources : list< `mpdaf.sdetect.Source` > List of `mpdaf.sdetect.Source` objects fmt : str 'working'|'default' Format of the catalog. The format differs for the LINES table. """ logger = logging.getLogger(__name__) ############################################### # List the columns (name/type) of the catalog # ############################################### # union of all headers keywords without mandatory FITS keywords d = {} for source in sources: d.update({k: (type(v), com) for k, v, com in source.header.cards}) keys = set(d.keys()) - EXCLUDED_CARDS if 'CUBE_V' not in keys: logger.warning('CUBE_V keyword in missing. It will be soon ' 'mandatory and its absecne will return an error') d['CUBE_V'] = (str, 'datacube version') names_hdr = MANDATORY_KEYS + list(keys - set(MANDATORY_KEYS)) tuple_hdr = [d[k] for k in names_hdr] dtype_hdr = (MANDATORY_TYPES + [c[0] for c in tuple_hdr[len(MANDATORY_TYPES):]]) desc_hdr = [c[:c.find('u.')] if c.find('u.') != -1 else c[:c.find('%')] if c.find('%') != -1 else c for _, c in tuple_hdr] unit_hdr = [c[c.find('u.'):].split()[0][2:] if c.find('u.') != -1 else None for _, c in tuple_hdr] format_hdr = [c[c.find('%'):].split()[0] if c.find('%') != -1 else None for _, c in tuple_hdr] has_mag = any(source.mag for source in sources) has_z = any(source.z for source in sources) names_mag = [] names_z = [] names_lines = [] dtype_lines = [] units_lines = [] # magnitudes if has_mag: names_mag = list(set(np.concatenate( [s.mag['BAND'].data for s in sources if s.mag is not None]))) names_mag += ['%s_ERR' % mag for mag in names_mag] names_mag.sort() # redshifts if has_z: names_z = list(set(np.concatenate([ s.z['Z_DESC'].data for s in sources if s.z is not None]))) names_z = ['Z_%s' % z for z in names_z] colnames = list(set(np.concatenate([ s.z.colnames for s in sources if s.z is not None]))) if 'Z_ERR' in colnames: names_err = ['%s_ERR' % z for z in names_z] else: names_err = [] if 'Z_MIN' in colnames: names_min = ['%s_MIN' % z for z in names_z] names_max = ['%s_MAX' % z for z in names_z] else: names_min = [] names_max = [] names_z += names_err names_z += names_min names_z += names_max names_z.sort() # lines llines = [len(source.lines) for source in sources if source.lines is not None] if len(llines) > 0: if fmt == 'default': d = {} unit = {} for source in sources: if source.lines is not None and \ 'LINE' in source.lines.colnames: colnames = source.lines.colnames colnames.remove('LINE') for col in colnames: d[col] = source.lines.dtype[col] unit[col] = source.lines[col].unit for line in source.lines['LINE'].data: if line is not None: try: float(line) logger.warning( 'source %d: line labeled \"%s\" not ' 'loaded', source.ID, line) except Exception: names_lines += [ '%s_%s' % (line.replace('_', ''), col) for col in colnames ] names_lines = list(set(np.concatenate([names_lines]))) names_lines.sort() dtype_lines = [d['_'.join(name.split('_')[1:])] for name in names_lines] units_lines = [unit['_'.join(name.split('_')[1:])] for name in names_lines] elif fmt == 'working': lmax = max(llines) d = {} unit = {} for source in sources: if source.lines is not None: for col in source.lines.colnames: d[col] = source.lines.dtype[col] unit[col] = source.lines[col].unit if lmax == 1: names_lines = sorted(d) dtype_lines = [d[key] for key in sorted(d)] units_lines = [unit[key] for key in sorted(d)] else: names_lines = [] inames_lines = sorted(d) for i in range(1, lmax + 1): names_lines += [col + '%03d' % i for col in inames_lines] dtype_lines = [d[key] for key in sorted(d)] * lmax units_lines = [unit[key] for key in sorted(d)] * lmax else: raise IOError('Catalog creation: invalid format. It must be ' 'default or working.') ############################################### # Set the data row by row # ############################################### data_rows = [] for source in sources: # header h = source.header keys = list(h.keys()) row = [] for key, typ in zip(names_hdr, dtype_hdr): if typ == type('1'): row += [('%s' % h[key]).replace('\n', ' ') if key in keys else INVALID[typ]] else: k = [h[key] if key in keys else INVALID[typ]] if type(k[0]) == type('1'): raise ValueError('column %s: could not convert string to %s' % (key, typ)) row += k # magnitudes if has_mag: if source.mag is None: row += [np.nan for key in names_mag] else: keys = source.mag['BAND'] for key in names_mag: if key in keys: row += [source.mag['MAG'][source.mag['BAND'] == key].data[0]] elif key[-4:] == '_ERR' and key[:-4] in keys: row += [source.mag['MAG_ERR'][source.mag['BAND'] == key[:-4]].data[0]] else: row += [np.nan] # redshifts if has_z: if source.z is None: row += [np.nan for key in names_z] else: keys = source.z['Z_DESC'] for key in names_z: key = key[2:] if key in keys: row += [source.z['Z'][source.z['Z_DESC'] == key].data[0]] elif key[-4:] == '_MAX' and key[:-4] in keys: row += [source.z['Z_MAX'][source.z['Z_DESC'] == key[:-4]].data[0]] elif key[-4:] == '_MIN' and key[:-4] in keys: row += [source.z['Z_MIN'][source.z['Z_DESC'] == key[:-4]].data[0]] elif key[-4:] == '_ERR' and key[:-4] in keys: row += [source.z['Z_ERR'][source.z['Z_DESC'] == key[:-4]].data[0]] else: row += [np.nan] # lines if len(llines) != 0: if source.lines is None: for typ in dtype_lines: row += [INVALID[typ.type]] else: if fmt == 'default': if 'LINE' not in source.lines.colnames: logger.warning( 'source %d:LINE column not present in LINE ' 'table. LINE information will be not loaded ' 'with the default format.', source.ID) for typ in dtype_lines: row += [INVALID[typ.type]] else: copy = source.lines['LINE'].data.copy() for i in range(len(source.lines)): source.lines['LINE'][i] = source.lines['LINE'][i].replace('_', '') for name, typ in zip(names_lines, dtype_lines): colname = '_'.join(name.split('_')[1:]) line = name.split('_')[0] if 'LINE' in source.lines.colnames and \ colname in source.lines.colnames and \ line in source.lines['LINE'].data: row += [source.lines[colname][source.lines['LINE'] == line].data[0]] else: row += [INVALID[typ.type]] source.lines['LINE'] = copy elif fmt == 'working': keys = source.lines.colnames if lmax == 1: row += [source.lines[key][0] if key in keys else INVALID[typ.type] for key, typ in zip(names_lines, dtype_lines)] else: try: subtab1 = source.lines[source.lines['LINE'] != ""] subtab2 = source.lines[source.lines['LINE'] == ""] lines = vstack([subtab1, subtab2]) except Exception: lines = source.lines n = len(lines) for key, typ in zip(names_lines, dtype_lines): if key[:-3] in keys and int(key[-3:]) <= n: row += [lines[key[:-3]][int(key[-3:]) - 1]] else: row += [INVALID[typ.type]] else: pass # final row data_rows.append(row) dtype = dtype_hdr # magnitudes if has_mag: dtype += ['f8' for i in range(len(names_mag))] # redshifts if has_z: dtype += ['f8' for i in range(len(names_z))] # lines if len(llines) != 0: dtype += dtype_lines # create Table names = names_hdr + names_mag + names_z + names_lines # raise a warning if the type is not the same between each source for i in range(len(names_hdr)): check = set([type(r[i]) for r in data_rows]) if len(check) > 1: logger.warning('column %s is defined with different types(%s) ' 'that will be converted to %s', names[i], check, dtype[i]) t = cls(rows=data_rows, names=names, masked=True, dtype=dtype) # format for name, desc, unit, fmt in zip(names_hdr, desc_hdr, unit_hdr, format_hdr): t[name].description = desc t[name].unit = unit t[name].format = fmt for name in names_z: t[name].format = '.4f' t[name].unit = u.dimensionless_unscaled if name[-3:] == 'MIN': t[name].description = 'Lower bound of estimated redshift' elif name[-3:] == 'MAX': t[name].description = 'Upper bound of estimated redshift' elif name[-3:] == 'ERR': t[name].description = 'Error of estimated redshift' else: t[name].description = 'Estimated redshift' for name in names_mag: t[name].format = '.3f' t[name].unit = u.mag if name[-3:] == 'ERR': t[name].description = 'Error in AB Magnitude' else: t[name].description = 'AB Magnitude' if len(llines) != 0: for name, unit in zip(names_lines, units_lines): t[name].unit = unit if 'LBDA' in name or 'EQW' in name: t[name].format = '.2f' if 'FLUX' in name or 'FWHM' in name: t[name].format = '.1f' return t
[docs] @classmethod def from_path(cls, path, fmt='default', pattern='*.fits'): """Construct a catalog from a list of source objects which are contains in the directory given as input. The new catalog will contain all data stored in the primary headers and in the tables extensions of the sources: * a column per header fits ('SIMPLE', 'BITPIX', 'NAXIS', 'EXTEND', 'DATE', 'AUTHOR', 'COM*' and 'HIST*' are excluded) * two columns per magnitude band: [BAND] [BAND]_ERR * three columns per redshift Z_[Z_DESC], Z_[Z_DESC]_MIN and Z_[Z_DESC]_MAX * several columns per line. The lines columns depend of the format. By default the columns names are created around unique LINE name [LINE]_[LINES columns names]. But it is possible to use a working format. [LINES columns names]_xxx where xxx is the number of lines present in each source. Parameters ---------- path : str Directory containing Source files fmt : str 'working'|'default' Format of the catalog. The format differs for the LINES table. pattern : str Pattern used to select the files, default to ``*.fits``. """ logger = logging.getLogger(__name__) if not os.path.exists(path): raise IOError("Invalid path: {0}".format(path)) from .source import Source slist = [] filenames = [] files = glob.glob(os.path.join(path, pattern)) files.sort() n = len(files) logger.info('Building catalog from path %s', path) for f in files: try: slist.append(Source.from_file(f)) filenames.append(os.path.basename(f)) except KeyboardInterrupt: return except Exception as inst: logger.warning('source %s not loaded (%s)', f, inst) sys.stdout.write("\r\x1b[K %i%%" % (100 * len(filenames) / n)) sys.stdout.flush() sys.stdout.write("\r\x1b[K ") sys.stdout.flush() t = cls.from_sources(slist, fmt) t['FILENAME'] = filenames return t
[docs] def write(self, *args, **kwargs): """Write this Table object out in the specified format. This function provides the Table interface to the astropy unified I/O layer. This allows easily writing a file in many supported data formats using syntax such as:: >>> from astropy.table import Table >>> dat = Table([[1, 2], [3, 4]], names=('a', 'b')) >>> dat.write('table.dat', format='ascii') # doctest: +SKIP The arguments and keywords (other than ``format``) provided to this function are passed through to the underlying data reader (e.g. `~astropy.io.ascii.write`). """ # Try to detect if the file is saved as FITS. In this case, Astropy # 3.0 serialize .format and .description in yaml comments, which causes # the table to not be readable by Catalog.read (inside Astropy it is # then read as QTable which is not parent class from Catalog). # So for now we just remove .format and .description in this case. # https://github.com/astropy/astropy/issues/7181 if (kwargs.get('format') == 'fits' or ( isinstance(args[0], str) and args[0].endswith('.fits'))): t = self.copy() for col in t.itercols(): col.format = None col.description = None super(Catalog, t).write(*args, **kwargs) else: super(Catalog, self).write(*args, **kwargs)
def _get_radec_colnames(self, col): """Helper method to get the names of ra,dec columns.""" ra = col[0] or self.meta.get('raname', self._raname_default) dec = col[1] or self.meta.get('decname', self._decname_default) return ra, dec
[docs] def masked_invalid(self): """Mask where invalid values occur (NaNs or infs or -9999 or '').""" for col in self.colnames: try: self[col][:] = np.ma.masked_invalid(self[col]) self[col][:] = np.ma.masked_equal(self[col], -9999) except Exception: pass
[docs] def hstack(self, cat2, **kwargs): """Peforms an `astropy.table.hstack` with another catalog, but also handles the metadata correctly. Parameters ---------- cat2 : `astropy.table.Table` Catalog to stack with. Remaining args and kwargs are passed to `astropy.table.hstack`, excecpt metadata_conflicts. Returns ------- stacked : `Catalog` object New catalog containing the stacked data """ # convert cat2 to Catalog object if not isinstance(cat2, Catalog): cat2 = Catalog(cat2, copy=False) # suppress metadata conflict warnings kwargs['metadata_conflicts'] = 'silent' stacked = hstack([self, cat2], **kwargs) stacked.meta = self._merge_meta([self, cat2]) return stacked
[docs] def join(self, cat2, **kwargs): """Peforms an `astropy.table.join` with another catalog, but also handles the metadata correctly. Parameters ---------- cat2 : `astropy.table.Table` Right catalog to join with. Remaining args and kwargs are passed to `astropy.table.join`, excecpt metadata_conflicts. Returns ------- joined : `~astropy.table.Table` object New table containing the result of the join operation. """ # convert cat2 to Catalog object if not isinstance(cat2, Catalog): cat2 = Catalog(cat2, copy=False) # suppress metadata conflict warnings keys = kwargs.get('keys', None) kwargs['metadata_conflicts'] = 'silent' joined = join(self, cat2, **kwargs) joined.meta = self._merge_meta([self, cat2], join_keys=keys) return joined
[docs] def match(self, cat2, radius=1, colc1=(None, None), colc2=(None, None), full_output=True, **kwargs): """Match elements of the current catalog with another (in RA, DEC). Parameters ---------- cat2 : `astropy.table.Table` Catalog to match. radius : float Matching size in arcsec (default 1). colc1: tuple Name of ra,dec columns in input table. colc2: tuple Name of ra,dec columns in cat2. full_output: bool output flag **kwargs Other arguments are passed to `astropy.coordinates.match_coordinates_sky`. Returns ------- out : astropy.Table, astropy.Table, astropy.Table If ``full_output`` is True, return a tuple ``(match, nomatch1, nomatch2)`` where: - match: table of matched elements in RA,DEC. - nomatch1: sub-table of non matched elements of the current catalog. - nomatch2: sub-table of non matched elements of the catalog cat2. If ``full_output`` is False, only ``match`` is returned. """ # convert cat2 to Catalog object if not isinstance(cat2, Catalog): cat2_class = cat2.__class__ cat2 = Catalog(cat2, copy=False) else: cat2_class = None col1_ra, col1_dec = self._get_radec_colnames(colc1) col2_ra, col2_dec = cat2._get_radec_colnames(colc2) coord1 = self.to_skycoord(ra=col1_ra, dec=col1_dec) coord2 = cat2.to_skycoord(ra=col2_ra, dec=col2_dec) id2, d2d, d3d = coord1.match_to_catalog_sky(coord2, **kwargs) id1 = np.arange(len(self)) kmatch = d2d < radius * u.arcsec id2match = id2[kmatch] d2match = d2d[kmatch] id1match = id1[kmatch] # search non unique index m = np.zeros_like(id2match, dtype=bool) m[np.unique(id2match, return_index=True)[1]] = True duplicate = id2match[~m] if len(duplicate) > 0: self._logger.debug('Found %d duplicate in matching catalogs', len(duplicate)) to_remove = [] for k in duplicate: mask = id2match == k idlist = np.arange(len(id2match))[mask] to_remove += idlist[d2match[mask].argsort()[1:]].tolist() id2match = np.delete(id2match, to_remove) id1match = np.delete(id1match, to_remove) d2match = np.delete(d2match, to_remove) match1 = self[id1match] match2 = cat2[id2match] match = match1.hstack(match2, join_type='exact') match.add_column(Column(data=d2match.to(u.arcsec), name='Distance', dtype=float)) if full_output: id1notmatch = np.in1d(range(len(self)), id1match, assume_unique=True, invert=True) id2notmatch = np.in1d(range(len(cat2)), id2match, assume_unique=True, invert=True) nomatch2 = cat2[id2notmatch] nomatch1 = self[id1notmatch] self._logger.debug('Cat1 Nelt %d Matched %d Not Matched %d', len(self), len(match1), len(nomatch1)) self._logger.debug('Cat2 Nelt %d Matched %d Not Matched %d', len(cat2), len(match2), len(nomatch2)) # convert nomatch2 back to original cat2 type if cat2_class: nomatch2 = cat2_class(nomatch2, copy=False) return match, nomatch1, nomatch2 else: self._logger.debug('Cat1 Nelt %d Cat2 Nelt %d Matched %d', len(self), len(cat2), len(match1)) return match
[docs] def nearest(self, coord, colcoord=(None, None), ksel=1, maxdist=None, **kwargs): """Return the nearest sources with respect to the given coordinate. Parameters ---------- coord: tuple ra,dec in decimal degree, or HH:MM:SS,DD:MM:SS colcoord: tuple of str column names of coordinate: default ('RA','DEC') ksel: int Number of sources to return, default 1 (if None return all sources sorted by distance) maxdist: float Maximum distance to source in arcsec, default None **kwargs Other arguments are passed to `astropy.coordinates.match_coordinates_sky`. Returns ------- `astropy.table.Table` The corresponding catalog of matched sources with the additional Distance column (arcsec). """ if not isinstance(coord, SkyCoord): ra, dec = coord if isinstance(ra, str) and ':' in ra: unit = (u.hourangle, u.deg) else: unit = (u.deg, u.deg) coord = SkyCoord(ra, dec, unit=unit, frame='fk5') if coord.shape == (): coord = coord.reshape(1) col_ra, col_dec = self._get_radec_colnames(colcoord) src_coords = self.to_skycoord(ra=col_ra, dec=col_dec) idx, d2d, d3d = src_coords.match_to_catalog_sky(coord, **kwargs) dist = d2d.arcsec ksort = dist.argsort() cat = self[ksort] dist = dist[ksort] if maxdist is not None: kmax = dist <= maxdist cat = cat[kmax] dist = dist[kmax] cat['Distance'] = dist cat['Distance'].format = '.2f' if ksel is not None: cat = cat[:ksel] return cat
[docs] def match3Dline(self, cat2, linecolc1, linecolc2, spatial_radius=1, spectral_window=5, suffix=('_1', '_2'), full_output=True, colc1=(None, None), colc2=(None, None), **kwargs): """3D Match elements of the current catalog with another using spatial (RA, DEC) and list of spectral lines location. Parameters ---------- cat2 : `astropy.table.Table` Catalog to match. linecolc1: list of float List of column names containing the wavelengths of the input catalog. linecolc2: list of float List of column names containing the wavelengths of the cat2. spatial_radius : float Matching radius size in arcsec (default 1). spectral_window : float (default 5) Matching wavelength window in spectral unit (default 5). colc1: tuple ('RA','DEC') name of ra,dec columns of input catalog. colc2: tuple ('RA','DEC') name of ra,dec columns of cat2. full_output: bool output flag **kwargs Other arguments are passed to `astropy.coordinates.match_coordinates_sky`. Returns ------- out : astropy.Table, astropy.Table, astropy.Table If ``full_output`` is True, return a tuple ``(match3d, match2d, nomatch1, nomatch2)`` where: - match3d, match2d: table of matched elements in RA,DEC. - nomatch1: sub-table of non matched elements of the current catalog. - nomatch2: sub-table of non matched elements of the catalog cat2. If ``full_output`` is False, only ``match`` is returned. """ # convert cat2 to Catalog object if not isinstance(cat2, Catalog): cat2_class = cat2.__class__ cat2 = Catalog(cat2, copy=False) else: cat2_class = None col1_ra, col1_dec = self._get_radec_colnames(colc1) col2_ra, col2_dec = cat2._get_radec_colnames(colc2) # rename all catalogs columns with _1 or _2 self._logger.debug('Rename Catalog columns with %s or %s suffix', suffix[0], suffix[1]) tcat1 = self.copy() tcat2 = cat2.copy() for name in tcat1.colnames: tcat1.rename_column(name, name + suffix[0]) for name in tcat2.colnames: tcat2.rename_column(name, name + suffix[1]) colc1 = (col1_ra + suffix[0], col1_dec + suffix[0]) linecolc1 = [col + suffix[0] for col in linecolc1] colc2 = (col2_ra + suffix[1], col2_dec + suffix[1]) linecolc2 = [col + suffix[1] for col in linecolc2] self._logger.debug('Performing spatial match') if full_output: match, unmatch1, unmatch2 = tcat1.match( tcat2, radius=spatial_radius, colc1=colc1, colc2=colc2, full_output=full_output, **kwargs) else: match = tcat1.match( tcat2, radius=spatial_radius, colc1=colc1, colc2=colc2, full_output=full_output, **kwargs) match.meta = self._merge_meta([tcat1, tcat2], suffix=suffix) tcat1._logger.debug('Performing line match') # create matched line colonnes match.add_column(MaskedColumn(length=len(match), name='NLMATCH', dtype='int'), index=1) # reorder columns match.add_column(match['Distance'], index=2, name='DIST') match['DIST'].format = '.2f' match.remove_column('Distance') for col in linecolc1: idx = tcat1.colnames.index(col) match.add_columns([MaskedColumn(length=len(match), dtype='bool'), MaskedColumn(length=len(match), dtype='S30'), MaskedColumn(length=len(match), dtype='float')], names=['M_' + col, 'L_' + col, 'E_' + col], indexes=[idx, idx, idx]) match['E_' + col].format = '.2f' match['M_' + col] = False # perform match for lines for r in match: # Match lines nmatch = 0 for c1 in linecolc1: l1 = r[c1] if np.ma.is_masked(l1): continue for c2 in linecolc2: l2 = r[c2] if np.ma.is_masked(l2): continue err = abs(l2 - l1) if err < spectral_window: nmatch += 1 r['M_' + c1] = True r['L_' + c1] = c2 r['E_' + c1] = err r['NLMATCH'] = nmatch if full_output: match3d = match[match['NLMATCH'] > 0] match2d = match[match['NLMATCH'] == 0] self._logger.info('Matched 3D: %d Matched 2D: %d Cat1 unmatched: ' '%d Cat2 unmatched: %d', len(match3d), len(match2d), len(unmatch1), len(unmatch2)) # convert unmatch2 back to original cat2 type if cat2_class: unmatch2 = cat2_class(unmatch2, copy=False) return match3d, match2d, unmatch1, unmatch2 else: self._logger.info('Matched 3D: %d', len(match[match['NLMATCH'] > 0])) return match
[docs] def select(self, wcs, ra=None, dec=None, margin=0, mask=None): """Select all sources from catalog which are inside the given WCS and return a new catalog. Parameters ---------- wcs : `~mpdaf.obj.WCS` Image WCS ra : str Name of the column that contains RA values in degrees. dec : str Name of the column that contains DEC values in degrees. margin : int Margin from the edges (pixels). mask : array-like Mask used to filter sources (1 to mask). Returns ------- `mpdaf.sdetect.Catalog` The catalog with selected rows. """ ra, dec = self._get_radec_colnames((ra, dec)) arr = np.vstack([self[dec].data, self[ra].data]).T cen = wcs.sky2pix(arr, unit=u.deg).T cen = (cen + 0.5).astype(int) sel = ((cen[0] > margin) & (cen[0] < wcs.naxis2 - margin) & (cen[1] > margin) & (cen[1] < wcs.naxis1 - margin)) if mask is not None: # select sources that are not masked sel[sel] = ~mask[(cen[0, sel] + 0.5).astype(int), (cen[1, sel] + 0.5).astype(int)] return self[sel]
[docs] def edgedist(self, wcs, ra=None, dec=None): """Return the smallest distance of all catalog sources center to the edge of the WCS of the given image. Parameters ---------- wcs : `~mpdaf.obj.WCS` Image WCS ra : str Name of the column that contains RA values in degrees dec : str Name of the column that contains DEC values in degrees Returns ------- `numpy.ndarray` The distance in arcsec units. """ ra, dec = self._get_radec_colnames((ra, dec)) dim = np.array([wcs.naxis2, wcs.naxis1]) pix = wcs.sky2pix(np.array([self[dec], self[ra]]).T, unit=u.deg) dist = np.hstack([pix, dim - pix]).min(axis=1) return dist * wcs.get_step(unit=u.arcsec)[0]
[docs] def to_skycoord(self, ra=None, dec=None, frame='fk5', unit='deg'): """Return an `astropy.coordinates.SkyCoord` object.""" from astropy.coordinates import SkyCoord ra, dec = self._get_radec_colnames((ra, dec)) return SkyCoord(ra=self[ra], dec=self[dec], unit=(unit, unit), frame=frame)
[docs] def to_ds9_regions(self, outfile, ra=None, dec=None, radius=1, frame='fk5', unit_pos='deg', unit_radius='arcsec'): """Return an `astropy.coordinates.SkyCoord` object.""" try: from regions import CircleSkyRegion, Regions except ImportError: self._logger.error("the 'regions' package is needed for this") raise ra, dec = self._get_radec_colnames((ra, dec)) center = self.to_skycoord(ra=ra, dec=dec, frame=frame, unit=unit_pos) radius = radius * u.Unit(unit_radius) regions = Regions([CircleSkyRegion(center=c, radius=radius) for c in center]) regions.write(outfile, format='ds9')
[docs] def plot_symb(self, ax, wcs, label=False, esize=0.8, lsize=None, etype='o', ltype=None, ra=None, dec=None, id=None, ecol='k', lcol=None, alpha=1.0, fill=False, fontsize=8, expand=1.7, tcol='k', ledgecol=None, lfacecol=None, npolygon=3, extent=None, **kwargs): """This function plots the sources location from the catalog. Parameters ---------- ax : `matplotlib.axes.Axes` Matplotlib axis instance (eg ax = fig.add_subplot(2,3,1)). wcs : `mpdaf.obj.WCS` Image WCS. label: bool If True catalog ID are displayed. esize : float symbol size in arcsec if extent=None (used only if lsize is not set). if extent is not None, the size unit is in the extent referential lsize : str Column name containing the size in arcsec. etype : str Type of symbol: o (circle, size=diameter), s (square, size=length), p (polygon, size=diameter) used only if ltype is not set. ltype : str Name of column that contain the symbol to use. ra : str Name of the column that contains RA values (in degrees). dec : str Name of the column that contains DEC values (in degrees). id : str Name of the column that contains ID. lcol: str Name of the column that contains Color. ecol : str Symbol color (only used if lcol is not set). tcol: str Text label color alpha : float Symbol transparency. fill: bool If True filled symbol are used. expand: float Expand factor to write label. ledgecol: str Name of the column that contains the edge color. lfacecol: str Name of the column that contains the fqce color. npolygon: int Number of polygone to use with etype='p extent: list of float [x1,y1,x2,y2] axis limits used with image.plot(extent=extent), default None (use spaxels) **kwargs kwargs can be used to set additional plotting properties. """ ra, dec = self._get_radec_colnames((ra, dec)) id = id or self.meta.get('idname', self._idname_default) if ltype is None and etype not in ('o', 's', 'p'): raise IOError('Unknown symbol %s' % etype) if ltype is not None and ltype not in self.colnames: raise IOError('column %s not found in catalog' % ltype) if lsize is not None and lsize not in self.colnames: raise IOError('column %s not found in catalog' % lsize) if lcol is not None and lcol not in self.colnames: raise IOError('column %s not found in catalog' % lcol) if ledgecol is not None and ledgecol not in self.colnames: raise IOError('column %s not found in catalog' % ledgecol) if lfacecol is not None and lfacecol not in self.colnames: raise IOError('column %s not found in catalog' % lfacecol) if ra not in self.colnames: raise IOError('column %s not found in catalog' % ra) if dec not in self.colnames: raise IOError('column %s not found in catalog' % dec) if label and id not in self.colnames: raise IOError('column %s not found in catalog' % id) from matplotlib.patches import Circle, Rectangle, RegularPolygon texts = [] step = wcs.get_step(unit=u.arcsec) arr = np.vstack([self[dec].data, self[ra].data]).T arr = wcs.sky2pix(arr, unit=u.deg) if extent is not None: dl = [(extent[1]-extent[0])/wcs.naxis1,(extent[3]-extent[2])/wcs.naxis2] arr = arr*dl + np.array([extent[0],extent[2]]) for src, cen in zip(self, arr): yy, xx = cen if (xx < 0) or (yy < 0) or (xx > wcs.naxis1) or (yy > wcs.naxis2): continue vsize = esize if lsize is None else src[lsize] pixsize = vsize / step[0] if extent is None else vsize vtype = etype if ltype is None else src[ltype] vcol = None vedgecol = 'none' vfacecol = 'none' vfill = True if lcol is None and ledgecol is None and lfacecol is None: vcol = ecol vfill = fill if lcol is not None: vcol = src[lcol] if ledgecol is not None: vcol = None vfill = False vedgecol = src[ledgecol] if lfacecol is not None: vfill = True vcol = None vfacecol = src[lfacecol] if vtype == 'o': if vcol is not None: s = Circle((xx, yy), 0.5 * pixsize, fill=fill, ec=vcol.rstrip(), alpha=alpha, **kwargs) else: s = Circle((xx, yy), 0.5 * pixsize, fill=vfill, edgecolor=vedgecol.rstrip(), facecolor=vfacecol.rstrip(), alpha=alpha, **kwargs) elif vtype == 's': if vcol is not None: s = Rectangle((xx - pixsize / 2, yy - pixsize / 2), pixsize, pixsize, fill=fill, ec=vcol.rstrip(), alpha=alpha, **kwargs) else: s = Rectangle((xx - pixsize / 2, yy - pixsize / 2), pixsize, pixsize, fill=vfill, edgecolor=vedgecol.rstrip(), facecolor=vfacecol.rstrip(), alpha=alpha, **kwargs) elif vtype == 'p': if vcol is not None: s = RegularPolygon((xx, yy), npolygon, 0.5 * pixsize, fill=fill, ec=vcol.rstrip(), alpha=alpha, **kwargs) else: s = RegularPolygon((xx, yy), npolygon, 0.5 * pixsize, fill=vfill, edgecolor=vedgecol.rstrip(), facecolor=vfacecol.rstrip(), alpha=alpha, **kwargs) ax.add_artist(s) if label and (not np.ma.is_masked(src[id])): texts.append((ax.text(xx, yy, src[id], ha='center', fontsize=fontsize, color=tcol), cen[1], cen[0])) s.set_clip_box(ax.bbox) if label and len(texts) > 0: text, x, y = zip(*texts) try: from adjustText import adjust_text except ImportError: self._logger.error("the 'adjustText' package is needed to " "avoid labels overlap") else: adjust_text(text, x=x, y=y, ax=ax, only_move={text: 'xy'}, expand_points=(expand, expand))