def parseGFH(gfh):
"""Parses the GFH (general file header?) structure at the beginning of the file"""
## type
ftype = gfh[0:4].tostring()
## length & version
fhlen, fver = struct.unpack('ii', gfh[4:12])
### creation date
crdate = gfh[12:23].tostring()
### creation time
crtime = gfh[23:28].tostring()
### revision date
rrdate = gfh[28:39].tostring()
### revision time
rrtime = gfh[39:44].tostring()
### revision count
rcount = struct.unpack('i', gfh[44:48])
rcount = rcount[0]
### node name
nname = gfh[48:128].tostring()
### types
dattp = struct.unpack('B', gfh[128:129])[0]
link1, link2 = struct.unpack('ii', gfh[152:160])
### the remaining info is not needed
dprint(
1,
"read header type=%s, length=%d, version=%d, created=%s@%s, updated=%s@%s x %d, node name=%s, dattp=%d, link=%d,%d"
% (ftype, fhlen, fver, crdate, crtime, rrdate, rrtime, rcount, nname,
dattp, link1, link2))
return (ftype, fhlen, fver, crdate, crtime, rrdate, rrtime, rcount, nname)
def load (filename,center=None,**kw):
"""Imports an AIPS clean component list from FITS table
"""
srclist = [];
dprint(1,"importing AIPS clean component FITS table",filename);
# read file
ff = pyfits.open(filename);
if center is None:
ra = ff[0].header['CRVAL1'];
dec = ff[0].header['CRVAL2'];
print "Using FITS image centre (%.4f, %.4f deg) as field centre"%(ra,dec);
center = ra*DEG,dec*DEG;
# now process file line-by-line
cclist = ff[1].data;
for num,ccrec in enumerate(cclist):
stokes_i,dx,dy = map(float,ccrec);
# convert dx/dy to real positions
l,m = sin(dx*ARCSEC),sin(dy*ARCSEC);
ra,dec = lm_to_radec(l,m,*center);
pos = ModelClasses.Position(ra,dec);
flux = ModelClasses.Flux(stokes_i);
# now create a source object
src = SkyModel.Source('cc%d'%num,pos,flux);
src.setAttribute('r',math.sqrt(l*l+m*m));
srclist.append(src);
dprintf(2,"imported %d sources from file %s\n",len(srclist),filename);
# create model
model = ModelClasses.SkyModel(*srclist);
# setup model center
model.setFieldCenter(*center);
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter());
return model;
def parseGFH (gfh):
"""Parses the GFH (general file header?) structure at the beginning of the file""";
## type
ftype = gfh[0:4].tostring()
## length & version
fhlen,fver = struct.unpack('ii',gfh[4:12])
### creation date
crdate = gfh[12:23].tostring()
### creation time
crtime = gfh[23:28].tostring()
### revision date
rrdate = gfh[28:39].tostring()
### revision time
rrtime = gfh[39:44].tostring()
### revision count
rcount = struct.unpack('i',gfh[44:48])
rcount = rcount[0]
### node name
nname = gfh[48:128].tostring()
### types
dattp = struct.unpack('B',gfh[128:129])[0];
link1,link2 = struct.unpack('ii',gfh[152:160]);
### the remaining info is not needed
dprint(1,"read header type=%s, length=%d, version=%d, created=%s@%s, updated=%s@%s x %d, node name=%s, dattp=%d, link=%d,%d"%
(ftype,fhlen,fver,crdate,crtime,rrdate,rrtime,rcount,nname,dattp,link1,link2));
return (ftype,fhlen,fver,crdate,crtime,rrdate,rrtime,rcount,nname);
def load(filename, center=None, **kw):
"""Imports an AIPs clean component list file
"""
srclist = []
dprint(1, "importing AIPS clean component table", filename)
# read file
ff = open(filename)
if center is None:
raise ValueError("field centre must be specified")
# now process file line-by-line
linenum = 0
for line in ff:
linenum += 1
# parse one line
dprint(4, "read line:", line)
ff = line.split()
if len(ff) != 5:
continue
try:
num = int(ff[0])
dx, dy, i, i_tot = list(map(float, ff[1:]))
except:
continue
try:
# convert dx/dy to real positions
l, m = sin(dx * ARCSEC), sin(dy * ARCSEC)
ra, dec = lm_to_radec(l, m, *center)
pos = ModelClasses.Position(ra, dec)
except Exception as exc:
print("CC %d: error converting coordinates (%s), skipping" %
(num, str(exc)))
continue
flux = ModelClasses.Flux(i)
# now create a source object
src = SkyModel.Source('cc%d' % num, pos, flux)
src.setAttribute('r', math.sqrt(l * l + m * m))
srclist.append(src)
dprintf(2, "imported %d sources from file %s\n", len(srclist), filename)
# create model
model = ModelClasses.SkyModel(*srclist)
# setup model center
model.setFieldCenter(*center)
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter())
for src in model.sources:
l, m = projection.lm(src.pos.ra, src.pos.dec)
src.setAttribute('r', math.sqrt(l * l + m * m))
return model
def load(filename, center=None, **kw):
"""Imports an AIPS clean component list from FITS table
"""
srclist = []
dprint(1, "importing AIPS clean component FITS table", filename)
# read file
ff = pyfits.open(filename)
if center is None:
hdr = ff[0].header
ra = hdr['CRVAL1'] * _units[hdr.get('CUNIT1', 'DEG').strip()]
dec = hdr['CRVAL2'] * _units[hdr.get('CUNIT2', 'DEG').strip()]
print("Using FITS image centre (%.4f, %.4f deg) as field centre" %
(ra / DEG, dec / DEG))
center = ra, dec
# now process file line-by-line
cclist = ff[1].data
hdr = ff[1].header
ux = _units[hdr.get('TUNIT2', 'DEG').strip()]
uy = _units[hdr.get('TUNIT3', 'DEG').strip()]
for num, ccrec in enumerate(cclist):
stokes_i, dx, dy = list(map(float, ccrec))
# convert dx/dy to real positions
l, m = sin(dx * ux), sin(dy * uy)
ra, dec = lm_to_radec(l, m, *center)
pos = ModelClasses.Position(ra, dec)
flux = ModelClasses.Flux(stokes_i)
# now create a source object
src = SkyModel.Source('cc%d' % num, pos, flux)
src.setAttribute('r', math.sqrt(l * l + m * m))
srclist.append(src)
dprintf(2, "imported %d sources from file %s\n", len(srclist), filename)
# create model
model = ModelClasses.SkyModel(*srclist)
# setup model center
model.setFieldCenter(*center)
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter())
for src in model.sources:
l, m = projection.lm(src.pos.ra, src.pos.dec)
src.setAttribute('r', math.sqrt(l * l + m * m))
return model
def parseMDH (mdh):
"""Parses the MDH (model file header?) structure""";
maxlin,modptr,nsources,mtype = struct.unpack('iiii',mdh[12:28]);
mepoch = struct.unpack('f',mdh[28:32])[0];
ra0,dec0,freq0 = struct.unpack('ddd',mdh[32:56]);
### Max. # of lines in model or disk version
### pointer to model ???
### no of sources in model
### model type(0: no ra,dec, 1=app, 2=epoch)
### Epoch (e.g. 1950) if TYP=2 (float) : 4 bytes
### Model centre RA (circles) : double
ra0 *= math.pi*2;
dec0 *= math.pi*2;
### Model centre FRQ (MHz)
freq0 *= 1e6
### the remaining is not needed
dprint(1,"read model header maxlines=%d, pointer=%d, sources=%d, type=%d, epoch=%f RA=%f, DEC=%f (rad) Freq=%f Hz"%
(maxlin,modptr,nsources,mtype,mepoch,ra0,dec0,freq0));
return (maxlin,modptr,nsources,mtype,mepoch,ra0,dec0,freq0);
def parse(self, line, linenum=0):
"""Parses one line. Returns None for empty or commented lines, else returns a CatalogLine object"""
# strip whitespace
line = line.strip()
dprintf(3, "read line %d: %s\n", linenum, line)
# skip empty or commented lines
if not line or line[0] == '#':
return None
# split using separators, quit when no more separators
fields = []
for sep in self.separators:
ff = line.split(sep, 1)
if len(ff) < 2:
break
fields.append(ff[0])
line = ff[1]
fields.append(line)
dprint(4, "line %d: " % linenum, fields)
return CatalogLine(self, fields)
def parse(self, line, linenum=0):
"""Parses one line. Returns None for empty or commented lines, else returns a CatalogLine object"""
# strip whitespace
line = line.strip()
dprintf(3, "read line %d: %s\n", linenum, line)
# skip empty or commented lines
if not line or line[0] == "#":
return None
# split using separators, quit when no more separators
fields = []
for sep in self.separators:
ff = line.split(sep, 1)
if len(ff) < 2:
break
fields.append(ff[0])
line = ff[1]
fields.append(line)
dprint(4, "line %d: " % linenum, fields)
return CatalogLine(self, fields)
def parseMDH(mdh):
"""Parses the MDH (model file header?) structure"""
maxlin, modptr, nsources, mtype = struct.unpack('iiii', mdh[12:28])
mepoch = struct.unpack('f', mdh[28:32])[0]
ra0, dec0, freq0 = struct.unpack('ddd', mdh[32:56])
### Max. # of lines in model or disk version
### pointer to model ???
### no of sources in model
### model type(0: no ra,dec, 1=app, 2=epoch)
### Epoch (e.g. 1950) if TYP=2 (float) : 4 bytes
### Model centre RA (circles) : double
ra0 *= math.pi * 2
dec0 *= math.pi * 2
### Model centre FRQ (MHz)
freq0 *= 1e6
### the remaining is not needed
dprint(
1,
"read model header maxlines=%d, pointer=%d, sources=%d, type=%d, epoch=%f RA=%f, DEC=%f (rad) Freq=%f Hz"
% (maxlin, modptr, nsources, mtype, mepoch, ra0, dec0, freq0))
return (maxlin, modptr, nsources, mtype, mepoch, ra0, dec0, freq0)
def __init__(self, format):
# figure out fields and their separators
fields = []
self.separators = []
while True:
match = re.match("(\w[\w:]*(=(fixed)?'[^']*')?)(([^\w]+)(\w.*))?$", format)
if not match:
break
fields.append(match.group(1))
# if no group 4, then we've reached the last field
if not match.group(4):
break
self.separators.append(match.group(5))
format = match.group(6)
# now parse the format specification
# this is a dict of field name -> field index
self.field_number = {}
# this is a dict of field name -> default value
self.field_default = dict(Category='2', I='1')
# fill up the dicts
for num_field, field in enumerate(fields):
# is a default value given?
match = re.match("(.+)='(.*)'$", field)
if match:
field = match.group(1)
self.field_default[field] = match.group(2)
self.field_number[field] = num_field
dprint(2, "fields are", self.field_number)
dprint(2, "default values are", self.field_default)
dprint(2, "separators are", self.separators)
def load (filename,freq0=None,**kw):
"""Imports a gaul table
The 'freq0' argument supplies a default reference frequency (if one is not contained in the file.)
If 'center_on_brightest' is True, the mpodel field center will be set to the brightest source.
'min_extent' is minimal source extent (in radians), above which a source will be treated as a Gaussian rather than a point component.
"""
srclist = [];
dprint(1,"importing PyBDSM gaul file",filename);
format = {};
# look for format string and reference freq, and build up format dict
for line in file(filename):
m = re.match("# Reference frequency .*\w([0-9.eE+-]+)\s*Hz",line);
if m:
freq0 = freq0 or float(m.group(1));
dprint(2,"found reference frequency %g"%freq0);
elif re.match("#(\s*[\w:]+\s+)+",line) and line.find("Gaus_id") > 0:
dprint(2,"found format string",line);
fields = dict([ (name,i) for i,name in enumerate(line[1:].split()) ]);
# map known fields to their ASCII equivalents, the rest copy as custom float attributes with
# a "pybdsm_" prefix
for i,name in enumerate(line[1:].split()):
if name in format_mapping:
format[format_mapping[name]] = i;
else:
format[":float:_pybdsm_%s"%name] = i;
if format and freq0:
break;
if not format:
raise ValueError,"this .gaul file does not appear to contain a format string"
# call ASCII.load() function now that we have the format dict
kw['format'] = format;
return ASCII.load(filename,**kw)
def __init__(self, format):
# figure out fields and their separators
fields = []
self.separators = []
while True:
match = re.match("(\w[\w:]*(=(fixed)?'[^']*')?)(([^\w]+)(\w.*))?$", format)
if not match:
break
fields.append(match.group(1))
# if no group 4, then we've reached the last field
if not match.group(4):
break
self.separators.append(match.group(5))
format = match.group(6)
# now parse the format specification
# this is a dict of field name -> field index
self.field_number = {}
# this is a dict of field name -> default value
self.field_default = dict(Category="2", I="1")
# fill up the dicts
for num_field, field in enumerate(fields):
# is a default value given?
match = re.match("(.+)='(.*)'$", field)
if match:
field = match.group(1)
self.field_default[field] = match.group(2)
self.field_number[field] = num_field
dprint(2, "fields are", self.field_number)
dprint(2, "default values are", self.field_default)
dprint(2, "separators are", self.separators)
def load (filename,center=None,**kw):
"""Imports an AIPs clean component list file
"""
srclist = [];
dprint(1,"importing AIPS clean component table",filename);
# read file
ff = file(filename);
if center is None:
raise ValueError,"field centre must be specified";
# now process file line-by-line
linenum = 0;
for line in ff:
linenum += 1;
# parse one line
dprint(4,"read line:",line);
ff = line.split();
if len(ff) != 5:
continue;
try:
num = int(ff[0]);
dx,dy,i,i_tot = map(float,ff[1:]);
except:
continue;
try:
# convert dx/dy to real positions
l,m = sin(dx*ARCSEC),sin(dy*ARCSEC);
ra,dec = lm_to_radec(l,m,*center);
pos = ModelClasses.Position(ra,dec);
except Exception,exc:
print "CC %d: error converting coordinates (%s), skipping"%(num,str(exc));
continue;
flux = ModelClasses.Flux(i);
# now create a source object
src = SkyModel.Source('cc%d'%num,pos,flux);
src.setAttribute('r',math.sqrt(l*l+m*m));
srclist.append(src);
def load(filename, center=None, **kw):
"""Imports an AIPS clean component list from FITS table
"""
srclist = []
dprint(1, "importing AIPS clean component FITS table", filename)
# read file
ff = pyfits.open(filename)
if center is None:
ra = ff[0].header['CRVAL1']
dec = ff[0].header['CRVAL2']
print "Using FITS image centre (%.4f, %.4f deg) as field centre" % (
ra, dec)
center = ra * DEG, dec * DEG
# now process file line-by-line
cclist = ff[1].data
for num, ccrec in enumerate(cclist):
stokes_i, dx, dy = map(float, ccrec)
# convert dx/dy to real positions
l, m = sin(dx * ARCSEC), sin(dy * ARCSEC)
ra, dec = lm_to_radec(l, m, *center)
pos = ModelClasses.Position(ra, dec)
flux = ModelClasses.Flux(stokes_i)
# now create a source object
src = SkyModel.Source('cc%d' % num, pos, flux)
src.setAttribute('r', math.sqrt(l * l + m * m))
srclist.append(src)
dprintf(2, "imported %d sources from file %s\n", len(srclist), filename)
# create model
model = ModelClasses.SkyModel(*srclist)
# setup model center
model.setFieldCenter(*center)
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter())
return model
def load(filename, freq0=None, **kw):
"""Imports a gaul table
The 'freq0' argument supplies a default reference frequency (if one is not contained in the file.)
If 'center_on_brightest' is True, the mpodel field center will be set to the brightest source.
'min_extent' is minimal source extent (in radians), above which a source will be treated as a Gaussian rather than a point component.
"""
srclist = []
id = None
dprint(1, "importing PyBDSM gaul/srl file", filename)
format = {}
extension = filename.split(".")[-1]
if extension == "srl":
format_mapping['Source_id'] = format_mapping.pop('Gaus_id')
id = "Source_id"
# look for format string and reference freq, and build up format dict
for line in open(filename):
m = re.match("# Reference frequency .*?([0-9.eE+-]+)\s*Hz", line)
if m:
freq0 = kw['freq0'] = freq0 or float(m.group(1))
dprint(2, "found reference frequency %g" % freq0)
elif re.match("#(\s*[\w:]+\s+)+",
line) and line.find(id if id else "Gaus_id") > 0:
dprint(2, "found format string", line)
fields = dict([(name, i)
for i, name in enumerate(line[1:].split())])
# map known fields to their ASCII equivalents, the rest copy as custom float attributes with
# a "pybdsm_" prefix
for i, name in enumerate(line[1:].split()):
if name in format_mapping:
dprint(2, "Field", format_mapping[name], name, "is column",
i)
format[format_mapping[name]] = i
else:
format[":float:_pybdsm_%s" % name] = i
if format and freq0:
break
if not format:
raise ValueError(
"this .gaul file does not appear to contain a format string")
# call ASCII.load() function now that we have the format dict
kw['format'] = format
return ASCII.load(filename, **kw)
def load(filename,
format=None,
freq0=None,
center_on_brightest=False,
min_extent=0,
**kw):
"""Imports an ASCII table
The 'format' argument can be either a dict (such as the DefaultDMSFormat dict above), or a string such as DefaultDMSFormatString.
(Other possible field names are "ra_d", "ra_rad", "dec_rad", "dec_sign".)
If None is specified, DefaultDMSFormat is used.
The 'freq0' argument supplies a default reference frequency (if one is not contained in the file.)
If 'center_on_brightest' is True, the mpodel field center will be set to the brightest source.
'min_extent' is minimal source extent (in radians), above which a source will be treated as a Gaussian rather than a point component.
"""
srclist = []
dprint(1, "importing ASCII DMS file", filename)
# brightest source and its coordinates
maxbright = 0
brightest_name = radec0 = None
# now process file line-by-line
linenum = 0
format_str = ''
for line in file(filename):
# for the first line, firgure out the file format
if not linenum:
if not format and line.startswith("#format:"):
format = line[len("#format:"):].strip()
dprint(1, "file contains format header:", format)
# set default format
if format is None:
format = DefaultDMSFormatString
# is the format a string rather than a dict? Turn it into a dict then
if isinstance(format, str):
format_str = format
# make list of fieldname,fieldnumber tuples
fields = [(field, i) for i, field in enumerate(format.split())]
if not fields:
raise ValueError, "illegal format string in file: '%s'" % format
# last fieldname can end with ... to indicate that it absorbs the rest of the line
if fields[-1][0].endswith('...'):
fields[-1] = (fields[-1][0][:-3],
slice(fields[-1][1], None))
# make format dict
format = dict(fields)
elif not isinstance(format, dict):
raise TypeError, "invalid 'format' argument of type %s" % (
type(format))
nf = max(format.itervalues()) + 1
fields = ['---'] * nf
for field, number in format.iteritems():
fields[number] = field
format_str = " ".join(fields)
# get minimum necessary fields from format
name_field = format.get('name', None)
# flux
try:
i_field = format['i']
except KeyError:
raise ValueError, "ASCII format specification lacks mandatory flux field ('i')"
# main RA field
if 'ra_h' in format:
ra_field, ra_scale = format['ra_h'], (math.pi / 12)
elif 'ra_d' in format:
ra_field, ra_scale = format['ra_d'], (math.pi / 180)
elif 'ra_rad' in format:
ra_field, ra_scale = format['ra_rad'], 1.
else:
raise ValueError, "ASCII format specification lacks mandatory Right Ascension field ('ra_h', 'ra_d' or 'ra_rad')"
# main Dec field
if 'dec_d' in format:
dec_field, dec_scale = format['dec_d'], (math.pi / 180)
elif 'dec_rad' in format:
dec_field, dec_scale = format['dec_rad'], 1.
else:
raise ValueError, "ASCII format specification lacks mandatory Declination field ('dec_d' or 'dec_rad')"
# polarization as QUV
try:
quv_fields = [format[x] for x in ['q', 'u', 'v']]
except KeyError:
quv_fields = None
# linear polarization as fraction and angle
polfrac_field = format.get('pol_frac', None)
if polfrac_field is not None:
polpa_field, polpa_scale = format.get('pol_pa_d',
None), (math.pi / 180)
if not polpa_field is not None:
polpa_field, polpa_scale = format.get('pol_pa_rad',
None), 1
# fields for extent parameters
ext_fields = []
for ext in 'emaj', 'emin', 'pa':
for field, scale in (ext, 1.), (ext + "_rad",
1.), (ext + '_d',
DEG), (ext + '_m', DEG /
60), (ext + '_s',
DEG / 3600):
if field in format:
ext_fields.append((format[field], scale))
break
# if not all three accumulated, ignore
if len(ext_fields) != 3:
ext_fields = None
# fields for reference freq and RM and SpI
freq0_field = format.get('freq0', None)
rm_field = format.get('rm', None)
spi_field = format.get('spi', None)
spi2_field = [format.get('spi%d' % i, None) for i in range(2, 10)]
tags_slice = format.get('tags', None)
# now go on to process the line
linenum += 1
try:
# strip whitespace
line = line.strip()
dprintf(4, "%s:%d: read line '%s'\n", filename, linenum, line)
# skip empty or commented lines
if not line or line[0] == '#':
continue
# split (at whitespace) into fields
fields = line.split()
# get name
name = fields[name_field] if name_field is not None else str(
len(srclist) + 1)
i = float(fields[i_field])
# get position: RA
ra = float(fields[ra_field])
if 'ra_m' in format:
ra += float(fields[format['ra_m']]) / 60.
if 'ra_s' in format:
ra += float(fields[format['ra_s']]) / 3600.
ra *= ra_scale
# position: Dec. Separate treatment of sign
dec = abs(float(fields[dec_field]))
if 'dec_m' in format:
dec += float(fields[format['dec_m']]) / 60.
if 'dec_s' in format:
dec += float(fields[format['dec_s']]) / 3600.
if fields[format.get('dec_sign', dec_field)][0] == '-':
dec = -dec
dec *= dec_scale
# see if we have freq0
try:
f0 = freq0 or (freq0_field and float(fields[freq0_field]))
except IndexError:
f0 = None
# set model refrence frequency
if f0 is not None and freq0 is None:
freq0 = f0
# see if we have Q/U/V
q = u = v = None
if quv_fields:
try:
q, u, v = map(float, [fields[x] for x in quv_fields])
except IndexError:
pass
if polfrac_field is not None:
pf = fields[polfrac_field]
pf = float(pf[:-1]) / 100 if pf.endswith("%") else float(pf)
ppa = float(fields[polpa_field]
) * polpa_scale if polpa_field is not None else 0
q = i * pf * math.cos(2 * ppa)
u = i * pf * math.sin(2 * ppa)
v = 0
# see if we have RM as well. Create flux object (unpolarized, polarized, polarized w/RM)
if q is None:
flux = ModelClasses.Polarization(i, 0, 0, 0)
elif f0 is None or rm_field is None or rm_field >= len(fields):
flux = ModelClasses.Polarization(i, q, u, v)
else:
flux = ModelClasses.PolarizationWithRM(i, q, u, v,
float(fields[rm_field]),
f0)
# see if we have a spectral index
if f0 is None or spi_field is None or spi_field >= len(fields):
spectrum = None
else:
spi = [ float(fields[spi_field]) ] + \
[ (float(fields[x]) if x is not None else 0) for x in spi2_field ]
# if any higher-order spectral terms are specified, include them here
# but trim off all trailing zeroes
while len(spi) > 1 and not spi[-1]:
del spi[-1]
if len(spi) == 1:
spi = spi[0]
spectrum = ModelClasses.SpectralIndex(spi, f0)
# see if we have extent parameters
ex = ey = pa = 0
if ext_fields:
try:
ex, ey, pa = [
float(fields[num]) * scale for num, scale in ext_fields
]
except IndexError:
pass
# form up shape object
if (ex or ey) and max(ex, ey) >= min_extent:
shape = ModelClasses.Gaussian(ex, ey, pa)
else:
shape = None
# get tags
tagdict = {}
if tags_slice:
try:
tags = fields[tags_slice]
except IndexError:
pass
for tagstr1 in tags:
for tagstr in tagstr1.split(","):
if tagstr[0] == "+":
tagname, value = tagstr[1:], True
elif tagstr[0] == "-":
tagname, value = tagstr[1:], False
elif "=" in tagstr:
tagname, value = tagstr.split("=", 1)
if value[0] in "'\"" and value[-1] in "'\"":
value = value[1:-1]
else:
try:
value = float(value)
except:
continue
else:
tagname, value = tagstr, True
tagdict[tagname] = value
# OK, now form up the source object
# position
pos = ModelClasses.Position(ra, dec)
# now create a source object
dprint(3, name, ra, dec, i, q, u, v)
src = SkyModel.Source(name,
pos,
flux,
shape=shape,
spectrum=spectrum,
**tagdict)
srclist.append(src)
# check if it's the brightest
brightness = src.brightness()
if brightness > maxbright:
maxbright = brightness
brightest_name = src.name
radec0 = ra, dec
except:
dprintf(0, "%s:%d: %s, skipping\n", filename, linenum,
str(sys.exc_info()[1]))
dprintf(2, "imported %d sources from file %s\n", len(srclist), filename)
# create model
model = ModelClasses.SkyModel(*srclist)
if freq0 is not None:
model.setRefFreq(freq0)
# set model format
model.setAttribute("ASCII_Format", format_str)
# setup model center
if center_on_brightest and radec0:
dprintf(2, "brightest source is %s (%g Jy) at %f,%f\n", brightest_name,
maxbright, *radec0)
model.setFieldCenter(*radec0)
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter())
for src in model.sources:
l, m = projection.lm(src.pos.ra, src.pos.dec)
src.setAttribute('r', math.sqrt(l * l + m * m))
return model
def load(filename, freq0=None, center_on_brightest=False, **kw):
"""Imports an BBS catalog file
The 'format' argument can be either a dict (such as the DefaultDMSFormat dict above), or a string such as DefaultDMSFormatString.
(Other possible field names are "ra_d", "ra_rad", "dec_rad", "dec_sign".)
If None is specified, DefaultDMSFormat is used.
The 'freq0' argument supplies a default reference frequency (if one is not contained in the file.)
If 'center_on_brightest' is True, the mpodel field center will be set to the brightest source,
else to the center of the first patch.
"""
srclist = []
dprint(1, "importing BBS source table", filename)
# read file
ff = file(filename)
# first line must be a format string: extract it
line0 = ff.readline().strip()
match = re.match("#\s*\((.+)\)\s*=\s*format", line0)
if not match:
raise ValueError, "line 1 is not a valid format specification"
format_str = match.group(1)
# create format parser from this string
parser = CatalogParser(format_str)
# check for mandatory fields
for field in "Name", "Type":
if not parser.defines(field):
raise ValueError, "Table lacks mandatory field '%s'" % field
maxbright = 0
patches = []
ref_freq = freq0
# now process file line-by-line
linenum = 1
for line in ff:
linenum += 1
try:
# parse one line
dprint(4, "read line:", line)
catline = parser.parse(line, linenum)
if not catline:
continue
dprint(5, "line %d: " % linenum, catline.__dict__)
# is it a patch record?
patchname = getattr(catline, "Patch", "")
if not catline.Name:
dprintf(2, "%s:%d: patch %s\n", filename, linenum, patchname)
patches.append((patchname, catline.ra_rad, catline.dec_rad))
continue
# form up name
name = "%s:%s" % (patchname, catline.Name) if patchname else catline.Name
# check source type
stype = catline.Type.upper()
if stype not in ("POINT", "GAUSSIAN"):
raise ValueError, "unsupported source type %s" % stype
# see if we have freq0
if freq0:
f0 = freq0
elif hasattr(catline, "ReferenceFrequency"):
f0 = float(catline.ReferenceFrequency or "0")
else:
f0 = None
# set model refrence frequency
if f0 is not None and ref_freq is None:
ref_freq = f0
# see if we have Q/U/V
i, q, u, v = [float(getattr(catline, stokes, "0") or "0") for stokes in "IQUV"]
# see if we have RM as well. Create flux object (unpolarized, polarized, polarized w/RM)
if f0 is not None and hasattr(catline, "RotationMeasure"):
flux = ModelClasses.PolarizationWithRM(i, q, u, v, float(catline.RotationMeasure or "0"), f0)
else:
flux = ModelClasses.Polarization(i, q, u, v)
# see if we have a spectral index
if f0 is not None and hasattr(catline, "SpectralIndex:0"):
spectrum = ModelClasses.SpectralIndex(float(getattr(catline, "SpectralIndex:0") or "0"), f0)
else:
spectrum = None
# see if we have extent parameters
if stype == "GAUSSIAN":
ex = float(getattr(catline, "MajorAxis", "0") or "0")
ey = float(getattr(catline, "MinorAxis", "0") or "0")
pa = float(getattr(catline, "Orientation", "0") or "0")
shape = ModelClasses.Gaussian(ex, ey, pa)
else:
shape = None
# create tags
tags = {}
for field in "Patch", "Category":
if hasattr(catline, field):
tags["BBS_%s" % field] = getattr(catline, field)
# OK, now form up the source object
# position
pos = ModelClasses.Position(catline.ra_rad, catline.dec_rad)
# now create a source object
src = SkyModel.Source(name, pos, flux, shape=shape, spectrum=spectrum, **tags)
srclist.append(src)
# check if it's the brightest
brightness = src.brightness()
if brightness > maxbright:
maxbright = brightness
brightest_name = src.name
radec0 = catline.ra_rad, catline.dec_rad
except:
dprintf(0, "%s:%d: %s, skipping\n", filename, linenum, str(sys.exc_info()[1]))
dprintf(2, "imported %d sources from file %s\n", len(srclist), filename)
# create model
model = ModelClasses.SkyModel(*srclist)
if ref_freq is not None:
model.setRefFreq(ref_freq)
# setup model center
if center_on_brightest and radec0:
dprintf(2, "setting model centre to brightest source %s (%g Jy) at %f,%f\n", brightest_name, maxbright, *radec0)
model.setFieldCenter(*radec0)
elif patches:
name, ra, dec = patches[0]
dprintf(2, "setting model centre to first patch %s at %f,%f\n", name, ra, dec)
model.setFieldCenter(ra, dec)
# map patches to model tags
model.setAttribute("BBS_Patches", patches)
model.setAttribute("BBS_Format", format_str)
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter())
for src in model.sources:
l, m = projection.lm(src.pos.ra, src.pos.dec)
src.setAttribute("r", math.sqrt(l * l + m * m))
return model
def save(model, filename, freq0=None, sources=None, **kw):
"""Saves model to a NEWSTAR MDL file.
The MDL file must exist, since the existing header is reused.
'sources' is a list of sources to write, if None, then model.sources is used.
"""
if sources is None:
sources = model.sources
dprintf(2, "writing %s model sources to NEWSTAR file\n", len(sources),
filename)
ra0, dec0 = model.fieldCenter()
freq0 = freq0 or model.refFreq()
# if freq0 is not specified, scan sources
if freq0 is None:
for src in sources:
freq0 = (src.spectrum
and getattr(src.spectrum, 'freq0', None)) or getattr(
src.flux, 'freq0', None)
if freq0:
break
else:
raise ValueError(
"unable to determine NEWSTAR model reference frequency, please specify one explicitly."
)
ff = open(filename, mode="wb")
### create GFH header
gfh = numpy.zeros(512, dtype=numpy.uint8)
datestr = time.strftime("%d-%m-%Y")
timestr = time.strftime("%H:%M")
struct.pack_into("4sii11s5s11s5si80sB", gfh, 0, ".MDL", 512, 1, datestr,
timestr, datestr, timestr, 0,
os.path.splitext(os.path.basename(filename))[0], 6)
# 6=datatype
# link1/link2 gives the header size actually
struct.pack_into("ii", gfh, 152, 512, 512)
gfh.tofile(ff)
# create MDH header
mdh = numpy.zeros(64, dtype=numpy.uint8)
struct.pack_into('iiii', mdh, 12, 1, 576, 0, 2)
# maxlin,pointer,num_sources,mtype
struct.pack_into('f', mdh, 28, getattr(model, 'epoch', 2000))
struct.pack_into('ddd', mdh, 32, ra0 / (2 * math.pi), dec0 / (2 * math.pi),
freq0 * 1e-6)
mdh.tofile(ff)
# get the max ID, if specified
max_id = max([getattr(src, 'newstar_id', 0) for src in sources])
# now loop over model sources
# count how many are written out -- only point sources and gaussians are actually written out, the rest are skipped
nsrc = 0
for src in sources:
# create empty newstar source structure
mdl = numpy.zeros(56, dtype=numpy.uint8)
if src.shape and not isinstance(src.shape, ModelClasses.Gaussian):
dprint(
3, "skipping source '%s': non-supported type '%s'" %
(src.name, src.shape.typecode))
continue
stI = src.flux.I
# get l,m NCP position -- either from tag, or compute
lm = getattr(src, '_lm_ncp', None)
if lm:
if isinstance(lm, (tuple, list)) and len(lm) == 2:
l, m = lm
else:
dprint(
0,
"warning: skipping source '%s' because its _lm_ncp attribute is malformed (tuple of 2 values expected)"
% src.name)
continue
else:
l, m = radec_to_lm_ncp(ra0, dec0, src.pos.ra, src.pos.dec)
# update source count
nsrc += 1
# generate source id
src_id = getattr(src, 'newstar_id', None)
if src_id is None:
src_id = max_id = max_id + 1
# encode position, flux, identifier -- also, convert flux from Jy to WU to Jy (1WU=5mJy)
struct.pack_into('fffi', mdl, 0, stI / 0.005, l, m, src_id)
# encode fractional polarization
struct.pack_into(
'fff', mdl, 16,
*[getattr(src.flux, stokes, 0.0) / stI for stokes in "QUV"])
## encode flag & type bits
## Flag: bit 0= extended; bit 1= Q|U|V <>0 and no longer used according to Wim
## Type: bit 0= clean component; bit 3= beamed
beamed = getattr(src, 'flux_intrinsic', False) or getattr(
src, 'newstar_beamed', False)
struct.pack_into('BB', mdl, 52, 1 if src.shape else 0,
(1 if getattr(src, 'newstar_cc', False) else 0) |
(8 if beamed else 0))
### extended source parameters
if src.shape:
## the procedure is NMOEXF in nscan/nmoext.for
R0 = math.cos(src.shape.pa)
R1 = -math.sin(src.shape.pa)
R2 = (.5 * src.shape.ex)**2
R3 = (.5 * src.shape.ey)**2
ex = R2 * R1 * R1 + R3 * R0 * R0
ey = R2 * R0 * R0 + R3 * R1 * R1
pa = 2 * (R2 - R3) * R0 * R1
struct.pack_into('fff', mdl, 28, ex, ey, pa)
### spectral index
if isinstance(src.spectrum, ModelClasses.SpectralIndex):
struct.pack_into('f', mdl, 40, src.spectrum.spi)
if isinstance(src.flux, ModelClasses.PolarizationWithRM):
struct.pack_into('f', mdl, 44, src.flux.rm)
mdl.tofile(ff)
# update MDH header with the new number of sources
struct.pack_into('i', mdh, 20, nsrc)
ff.seek(512)
mdh.tofile(ff)
ff.close()
dprintf(1, "wrote %d sources to file %s\n", nsrc, filename)
def load(filename, import_src=True, import_cc=True, min_extent=0, **kw):
"""Imports a NEWSTAR MDL file.
min_extent is minimal source extent (in radians), above which a source will be treated as a Gaussian rather than a point component.
import_src=False causes source components to be omitted
import_cc=False causes clean components to be omitted
"""
srclist = []
dprint(1, "importing NEWSTAR file", filename)
# build the LSM from a NewStar .MDL model file
# if only_cleancomp=True, only clean components are used to build the LSM
# if no_cleancomp=True, no clean components are used to build the LSM
ff = open(filename, mode="rb")
### read GFH and MDH headers -- 512 bytes
try:
gfh = numpy.fromfile(ff, dtype=numpy.uint8, count=512)
mdh = numpy.fromfile(ff, dtype=numpy.uint8, count=64)
# parse headers
ftype, fhlen, fver, crdate, crtime, rrdate, rrtime, rcount, nname = parseGFH(
gfh)
if ftype != ".MDL":
raise TypeError
maxlin, modptr, nsources, mtype, mepoch, ra0, dec0, freq0 = parseMDH(
mdh)
beam_const = 65 * 1e-9 * freq0
## temp dict to hold unique nodenames
unamedict = {}
### Models -- 56 bytes
for ii in range(0, nsources):
mdl = numpy.fromfile(ff, dtype=numpy.uint8, count=56)
### source parameters
sI, ll, mm, id, sQ, sU, sV, eX, eY, eP, SI, RM = struct.unpack(
'fffiffffffff', mdl[0:48])
### type bits
bit1, bit2 = struct.unpack('BB', mdl[52:54])
# convert fluxes
sI *= 0.005 # convert from WU to Jy (1WU=5mJy)
sQ *= sI
sU *= sI
sV *= sI
# Interpret bitflags 1: bit 0= extended; bit 1= Q|U|V <>0 and no longer used according to Wim
fl_ext = bit1 & 1
# Interpret bitflags 2: bit 0= clean component; bit 3= beamed
fl_cc = bit2 & 1
fl_beamed = bit2 & 8
### extended source params: in arcsec, so multiply by ???
if fl_ext:
## the procedure is NMOEXT in nscan/nmoext.for
if eP == 0 and eX == eY:
r0 = 0
else:
r0 = .5 * math.atan2(-eP, eY - eX)
r1 = math.sqrt(eP * eP + (eX - eY) * (eX - eY))
r2 = eX + eY
eX = 2 * math.sqrt(abs(0.5 * (r2 + r1)))
eY = 2 * math.sqrt(abs(0.5 * (r2 - r1)))
eP = r0
# NEWSTAR MDL lists might have same source twice if they are
# clean components, so make a unique name for them
bname = 'N' + str(id)
if bname in unamedict:
uniqname = bname + '_' + str(unamedict[bname])
unamedict[bname] += 1
else:
uniqname = bname
unamedict[bname] = 1
# compose source information
pos = ModelClasses.Position(*lm_ncp_to_radec(ra0, dec0, ll, mm))
flux = ModelClasses.PolarizationWithRM(sI, sQ, sU, sV, RM, freq0)
spectrum = ModelClasses.SpectralIndex(SI, freq0)
tags = {}
# work out beam gain and apparent flux
tags['_lm_ncp'] = (ll, mm)
tags['_newstar_r'] = tags['r'] = r = math.sqrt(ll * ll + mm * mm)
tags['newstar_beamgain'] = bg = max(
math.cos(beam_const * r)**6, .01)
tags['newstar_id'] = id
if fl_beamed:
tags['Iapp'] = sI * bg
tags['newstar_beamed'] = True
tags['flux_intrinsic'] = True
else:
tags['flux_apparent'] = True
# make some tags based on model flags
if fl_cc:
tags['newstar_cc'] = True
# make shape if extended
if fl_ext and max(eX, eY) >= min_extent:
shape = ModelClasses.Gaussian(eX, eY, eP)
else:
shape = None
# compute apparent flux
src = SkyModel.Source(uniqname,
pos,
flux,
shape=shape,
spectrum=spectrum,
**tags)
srclist.append(src)
except:
traceback.print_exc()
raise TypeError("%s does not appear to be a valid NEWSTAR MDL file" %
filename)
dprintf(2, "imported %d sources from file %s\n", len(srclist), filename)
return ModelClasses.SkyModel(ra0=ra0,
dec0=dec0,
freq0=freq0,
pbexp='max(cos(65*1e-9*fq*r)**6,.01)',
*srclist)
def save(model, filename, sources=None, format=None, **kw):
"""Exports model to a BBS catalog file"""
if sources is None:
sources = model.sources
dprintf(2, "writing %d model sources to BBS file %s\n", len(sources), filename)
# create catalog parser based on either specified format, or the model format, or the default format
format = format or getattr(
model,
"BBS_Format",
"Name, Type, Patch, Ra, Dec, I, Q, U, V, ReferenceFrequency, SpectralIndexDegree='0', SpectralIndex:0='0.0', MajorAxis, MinorAxis, Orientation",
)
dprint(2, "format string is", format)
parser = CatalogParser(format)
# check for mandatory fields
for field in "Name", "Type":
if not parser.defines(field):
raise ValueError, "Output format lacks mandatory field '%s'" % field
# open file
ff = open(filename, mode="wt")
ff.write("# (%s) = format\n# The above line defines the field order and is required.\n\n" % format)
# write patches
for name, ra, dec in getattr(model, "BBS_Patches", []):
catline = parser.newline()
catline.Patch = name
catline.setPosition(ra, dec)
ff.write(catline.makeStr() + "\n")
ff.write("\n")
# write sources
nsrc = 0
for src in sources:
catline = parser.newline()
# type
if src.shape is None:
catline.Type = "POINT"
elif isinstance(src.shape, ModelClasses.Gaussian):
catline.Type = "GAUSSIAN"
else:
dprint(3, "skipping source '%s': non-supported type '%s'" % (src.name, src.shape.typecode))
continue
# name and patch
name = src.name
patch = getattr(src, "BBS_Patch", "")
if patch and name.startswith(patch + ":"):
name = name[(len(patch) + 1) :]
catline.Name = name
setattr(catline, "Patch", patch)
# position
catline.setPosition(src.pos.ra, src.pos.dec)
# fluxes
for stokes in "IQUV":
setattr(catline, stokes, str(getattr(src.flux, stokes, 0.0)))
# reference freq
freq0 = (src.spectrum and getattr(src.spectrum, "freq0", None)) or getattr(src.flux, "freq0", None)
if freq0 is not None:
setattr(catline, "ReferenceFrequency", str(freq0))
# RM, spi
if isinstance(src.spectrum, ModelClasses.SpectralIndex):
setattr(catline, "SpectralIndexDegree", "0")
setattr(catline, "SpectralIndex:0", str(src.spectrum.spi))
if isinstance(src.flux, ModelClasses.PolarizationWithRM):
setattr(catline, "RotationMeasure", str(src.flux.rm))
# shape
if isinstance(src.shape, ModelClasses.Gaussian):
setattr(catline, "MajorAxis", src.shape.ex)
setattr(catline, "MinorAxis", src.shape.ey)
setattr(catline, "Orientation", src.shape.pa)
# write line
ff.write(catline.makeStr() + "\n")
nsrc += 1
ff.close()
dprintf(1, "wrote %d sources to file %s\n", nsrc, filename)
def save(model, filename, sources=None, format=None, **kw):
"""
Exports model to a text file
"""
if sources is None:
sources = model.sources
dprintf(2, "writing %d model sources to text file %s\n", len(sources), filename)
# create catalog parser based on either specified format, or the model format, or the default format
format_str = format or getattr(model, 'ASCII_Format', DefaultDMSFormatString)
dprint(2, "format string is", format_str)
# convert this into format dict
fields = [[field, i] for i, field in enumerate(format_str.split())]
if not fields:
raise ValueError("illegal format string '%s'" % format)
# last fieldname can end with ... ("tags..."), so strip it
if fields[-1][0].endswith('...'):
fields[-1][0] = fields[-1][0][:-3]
# make format dict
format = dict(fields)
nfields = len(fields)
# get minimum necessary fields from format
name_field = format.get('name', None)
# main RA field
ra_rad_field, ra_d_field, ra_h_field, ra_m_field, ra_s_field = \
[format.get(x, None) for x in ('ra_rad', 'ra_d', 'ra_h', 'ra_m', 'ra_s')]
dec_rad_field, dec_d_field, dec_m_field, dec_s_field = \
[format.get(x, None) for x in ('dec_rad', 'dec_d', 'dec_m', 'dec_s')]
if ra_h_field is not None:
ra_scale = 15
ra_d_field = ra_h_field
else:
ra_scale = 1
# fields for reference freq and RM and SpI
freq0_field = format.get('freq0', None)
rm_field = format.get('rm', None)
spi_field = format.get('spi', None)
tags_field = format.get('tags', None)
# open file
ff = open(filename, mode="wt")
ff.write("#format: %s\n" % format_str)
# write sources
nsrc = 0
for src in sources:
# only write points and gaussians
if src.shape is not None and not isinstance(src.shape, ModelClasses.Gaussian):
dprint(3, "skipping source '%s': non-supported type '%s'" % (src.name, src.shape.typecode))
continue
# prepare field values
fval = ['0'] * nfields
# name
if name_field is not None:
fval[name_field] = src.name
# position: RA
ra, dec = src.pos.ra, src.pos.dec
# RA in radians
if ra_rad_field is not None:
fval[ra_rad_field] = str(ra)
ra /= ra_scale
# RA in h/m/s or d/m/s
if ra_m_field is not None:
ra, ram, ras = src.pos.ra_hms_static(ra, scale=180, prec=1e-4)
fval[ra_m_field] = str(ram)
if ra_s_field is not None:
fval[ra_s_field] = str(ras)
if ra_d_field is not None:
fval[ra_d_field] = str(ra)
elif ra_d_field is not None:
fval[ra_d_field] = str(ra * 180 / math.pi)
# position: Dec
if dec_rad_field is not None:
fval[dec_rad_field] = str(dec)
if dec_m_field is not None:
dsign, decd, decm, decs = src.pos.dec_sdms()
fval[dec_m_field] = str(decm)
if dec_s_field is not None:
fval[dec_s_field] = str(decs)
if dec_d_field is not None:
fval[dec_d_field] = dsign + str(decd)
elif dec_d_field is not None:
fval[dec_d_field] = str(dec * 180 / math.pi)
# fluxes
for stokes in "IQUV":
field = format.get(stokes.lower())
if field is not None:
fval[field] = str(getattr(src.flux, stokes, 0))
# fractional polarization
if 'pol_frac' in format:
i, q, u = [getattr(src.flux, stokes, 0) for stokes in "IQU"]
fval[format['pol_frac']] = str(math.sqrt(q * q + u * u) / i)
pa = math.atan2(u, q) / 2
for field, scale in ('pol_pa_rad', 1.), ('pol_pa_d', DEG):
ifield = format.get(field)
if ifield is not None:
fval[ifield] = str(pa / scale)
# shape
if src.shape:
for parm, sparm in ("emaj", "ex"), ("emin", "ey"), ("pa", "pa"):
for field, scale in (parm, 1.), (parm + '_rad', DEG), (parm + '_d', DEG), (parm + '_m', DEG / 60), (
parm + '_s', DEG / 3600):
ifield = format.get(field.lower())
if ifield is not None:
fval[ifield] = str(getattr(src.shape, sparm, 0) / scale)
# RM, spi, freq0
if freq0_field is not None:
freq0 = (src.spectrum and getattr(src.spectrum, 'freq0', None)) or getattr(src.flux, 'freq0', 0)
fval[freq0_field] = str(freq0)
if rm_field is not None:
fval[rm_field] = str(getattr(src.flux, 'rm', 0))
if spi_field is not None and hasattr(src, 'spectrum'):
fval[spi_field] = str(getattr(src.spectrum, 'spi', 0))
# tags
if tags_field is not None:
outtags = []
for tag, value in src.getTags():
if isinstance(value, str):
outtags.append("%s=\"%s\"" % (tag, value))
elif isinstance(value, bool):
if value:
outtags.append("+" + tag)
else:
outtags.append("-" + tag)
elif isinstance(value, (int, float)):
outtags.append("%s=%f" % (tag, value))
fval[tags_field] = ",".join(outtags)
# write the line
ff.write(" ".join(fval) + "\n")
nsrc += 1
ff.close()
dprintf(1, "wrote %d sources to file %s\n", nsrc, filename)
def load(filename, format=None, freq0=None, center_on_brightest=False, min_extent=0, verbose=0, **kw):
"""Imports an ASCII table
The 'format' argument can be either a dict (such as the DefaultDMSFormat dict above), or a string such as DefaultDMSFormatString.
(Other possible field names are "ra_d", "ra_rad", "dec_rad", "dec_sign".)
If None is specified, DefaultDMSFormat is used.
The 'freq0' argument supplies a default reference frequency (if one is not contained in the file.)
If 'center_on_brightest' is True, the mpodel field center will be set to the brightest source.
'min_extent' is minimal source extent (in radians), above which a source will be treated as a Gaussian rather than a point component.
"""
srclist = []
dprint(1, "importing ASCII DMS file", filename)
# brightest source and its coordinates
maxbright = 0
brightest_name = radec0 = None
# Get column number associated with field from format dict, as well as the error
# column number. Returns tuple of indices, with None index indicating no such column
def get_field(name):
return format.get(name, None), format.get(name + "_err", None)
# Get column number associated with field from format dict, as well as the error
# column number. Field is an angle thus will be suffixed with _{rad,d,h,m,s}.
# Returns tuple of
# column,scale,err_column,err_scale
# with None index indicating no such column. Scale is scaling factor to convert
# quantity in column to radians
def get_ang_field(name, units=ANGULAR_UNITS):
column = err_column = colunit = errunit = None
units = units or ANGULAR_UNITS
for unit, scale in units.items():
if column is None:
column = format.get("%s_%s" % (name, unit))
if column is not None:
colunit = scale
if err_column is None:
err_column = format.get("%s_err_%s" % (name, unit))
if err_column is not None:
errunit = scale
return column, colunit, err_column, errunit
# helper function: returns element #num from the fields list, multiplied by scale, or None if no such field
def getval(num, scale=1):
return None if (num is None or len(fields) <= num) else float(fields[num]) * scale
# now process file line-by-line
linenum = 0
format_str = ''
for line in open(filename):
# for the first line, figure out the file format
if not linenum:
if not format and line.startswith("#format:"):
format = line[len("#format:"):].strip()
dprint(1, "file contains format header:", format)
# set default format
if format is None:
format = DefaultDMSFormatString
# is the format a string rather than a dict? Turn it into a dict then
if isinstance(format, str):
format_str = format
# make list of fieldname,fieldnumber tuples
fields = [(field, i) for i, field in enumerate(format.split())]
if not fields:
raise ValueError("illegal format string in file: '%s'" % format)
# last fieldname can end with ... to indicate that it absorbs the rest of the line
if fields[-1][0].endswith('...'):
fields[-1] = (fields[-1][0][:-3], slice(fields[-1][1], None))
# make format dict
format = dict(fields)
elif not isinstance(format, dict):
raise TypeError("invalid 'format' argument of type %s" % (type(format)))
# nf = max(format.itervalues())+1
# fields = ['---']*nf
# for field,number in format.iteritems():
# fields[number] = field
# format_str = " ".join(fields)
# get list of custom attributes from format
custom_attrs = []
for name, col in format.items():
if name.startswith(":"):
m = re.match("^:(bool|int|float|complex|str):([\w]+)$", name)
if not m:
raise TypeError("invalid field specification '%s' in format string" % name)
custom_attrs.append((eval(m.group(1)), m.group(2), col))
# get minimum necessary fields from format
name_field = format.get('name', None)
# flux
i_field, i_err_field = get_field("i")
if i_field is None:
raise ValueError("ASCII format specification lacks mandatory flux field ('i')")
# main RA field
ra_field, ra_scale, ra_err_field, ra_err_scale = get_ang_field('ra', ANGULAR_UNITS_RA)
if ra_field is None:
raise ValueError("ASCII format specification lacks mandatory Right Ascension field ('ra_h', 'ra_d' or 'ra_rad')")
# main Dec field
dec_field, dec_scale, dec_err_field, dec_err_scale = get_ang_field('dec', ANGULAR_UNITS_DEC)
if dec_field is None:
raise ValueError("ASCII format specification lacks mandatory Declination field ('dec_d' or 'dec_rad')")
# polarization as QUV
quv_fields = [get_field(x) for x in ['q', 'u', 'v']]
# linear polarization as fraction and angle
polfrac_field = format.get('pol_frac', None)
if polfrac_field is not None:
polpa_field, polpa_scale = format.get('pol_pa_d', None), (math.pi / 180)
if not polpa_field is not None:
polpa_field, polpa_scale = format.get('pol_pa_rad', None), 1
# fields for extent parameters
extent_fields = [get_ang_field(x, ANGULAR_UNITS) for x in ('emaj', 'emin', 'pa')]
# all three must be present, else ignore
if any([x[0] is None for x in extent_fields]):
extent_fields = None
# fields for reference freq and RM and SpI
freq0_field = format.get('freq0', None)
rm_field, rm_err_field = get_field('rm')
spi_fields = [get_field('spi')] + [get_field('spi%d' % i) for i in range(2, 10)]
tags_slice = format.get('tags', None)
# now go on to process the line
linenum += 1
try:
# strip whitespace
line = line.strip()
dprintf(4, "%s:%d: read line '%s'\n", filename, linenum, line)
# skip empty or commented lines
if not line or line[0] == '#':
continue
# split (at whitespace) into fields
fields = line.split()
# get name
name = fields[name_field] if name_field is not None else str(len(srclist) + 1)
i = getval(i_field)
i_err = getval(i_err_field)
# get position: RA
ra = getval(ra_field)
ra_err = getval(ra_err_field, ra_scale)
if 'ra_m' in format:
ra += float(fields[format['ra_m']]) / 60.
if 'ra_s' in format:
ra += float(fields[format['ra_s']]) / 3600.
ra *= ra_scale
# position: Dec. Separate treatment of sign
dec = abs(getval(dec_field))
dec_err = getval(dec_err_field, dec_scale)
if 'dec_m' in format:
dec += float(fields[format['dec_m']]) / 60.
if 'dec_s' in format:
dec += float(fields[format['dec_s']]) / 3600.
if fields[format.get('dec_sign', dec_field)][0] == '-':
dec = -dec
dec *= dec_scale
# for up position object
pos = ModelClasses.Position(ra, dec, ra_err=ra_err, dec_err=dec_err)
# see if we have freq0
# Use explicitly provided reference frequency for this source if available
f0 = None
if freq0_field is not None:
try:
f0 = float(fields[freq0_field])
# If no default reference frequency for the model was supplied,
# initialise from first source with a reference frequency
if freq0 is None:
freq0 = f0
dprint(0, "Set default freq0 to %s "
"from source on line %s." % (f0, linenum))
except IndexError:
f0 = None
# Otherwise use default reference frequency (derived from args
# or first reference frequency found in source)
if f0 is None and freq0 is not None:
f0 = freq0
# see if we have Q/U/V
(q, q_err), (u, u_err), (v, v_err) = [(getval(x), getval(x_err)) for x, x_err in quv_fields]
if polfrac_field is not None:
pf = fields[polfrac_field]
pf = float(pf[:-1]) / 100 if pf.endswith("%") else float(pf)
ppa = float(fields[polpa_field]) * polpa_scale if polpa_field is not None else 0
q = i * pf * math.cos(2 * ppa)
u = i * pf * math.sin(2 * ppa)
v = 0
# see if we have RM as well. Create flux object (unpolarized, polarized, polarized w/RM)
rm, rm_err = getval(rm_field), getval(rm_err_field)
if q is None:
flux = ModelClasses.Polarization(i, 0, 0, 0, I_err=i_err)
elif f0 is None or rm is None:
flux = ModelClasses.Polarization(i, q, u, v, I_err=i_err, Q_err=q_err, U_err=u_err, V_err=v_err)
else:
flux = ModelClasses.PolarizationWithRM(i, q, u, v, rm, f0, I_err=i_err, Q_err=q_err, U_err=u_err,
V_err=v_err, rm_err=rm_err)
# see if we have a spectral index
if f0 is None:
spectrum = None
else:
spi = [getval(x) for x, xerr in spi_fields]
spi_err = [getval(xerr) for x, xerr in spi_fields]
dprint(4, name, "spi is", spi, "err is", spi_err)
# if any higher-order spectral terms are specified, include them here but trim off all trailing zeroes
while spi and not spi[-1]:
del spi[-1]
del spi_err[-1]
if not spi:
spectrum = None
elif len(spi) == 1:
spectrum = ModelClasses.SpectralIndex(spi[0], f0)
if spi_err[0] is not None:
spectrum.spi_err = spi_err[0]
else:
spectrum = ModelClasses.SpectralIndex(spi, f0)
if any([x is not None for x in spi_err]):
spectrum.spi_err = spi_err
# see if we have extent parameters
ex = ey = pa = 0
if extent_fields:
ex, ey, pa = [(getval(x[0], x[1]) or 0) for x in extent_fields]
extent_errors = [getval(x[2], x[3]) for x in extent_fields]
# form up shape object
if (ex or ey) and max(ex, ey) >= min_extent:
shape = ModelClasses.Gaussian(ex, ey, pa)
for ifield, field in enumerate(['ex', 'ey', 'pa']):
if extent_errors[ifield] is not None:
shape.setAttribute(field + "_err", extent_errors[ifield])
else:
shape = None
# get tags
tagdict = {}
if tags_slice:
try:
tags = fields[tags_slice]
except IndexError:
pass
for tagstr1 in tags:
for tagstr in tagstr1.split(","):
if tagstr[0] == "+":
tagname, value = tagstr[1:], True
elif tagstr[0] == "-":
tagname, value = tagstr[1:], False
elif "=" in tagstr:
tagname, value = tagstr.split("=", 1)
if value[0] in "'\"" and value[-1] in "'\"":
value = value[1:-1]
else:
try:
value = float(value)
except:
continue
else:
tagname, value = tagstr, True
tagdict[tagname] = value
# OK, now form up the source object
# now create a source object
dprint(3, name, ra, dec, i, q, u, v)
src = SkyModel.Source(name, pos, flux, shape=shape, spectrum=spectrum, **tagdict)
# get custom attributes
for type_, attr, column in custom_attrs:
if column is not None and len(fields) > column:
src.setAttribute(attr, type_(fields[column]))
# add to source list
srclist.append(src)
# check if it's the brightest
brightness = src.brightness()
if brightness > maxbright:
maxbright = brightness
brightest_name = src.name
radec0 = ra, dec
except:
dprintf(0, "%s:%d: %s, skipping\n", filename, linenum, str(sys.exc_info()[1]))
if verbose:
raise
dprintf(2, "imported %d sources from file %s\n", len(srclist), filename)
# create model
model = ModelClasses.SkyModel(*srclist)
if freq0 is not None:
model.setRefFreq(freq0)
# set model format
model.setAttribute("ASCII_Format", format_str)
# setup model center
if center_on_brightest and radec0:
dprintf(2, "brightest source is %s (%g Jy) at %f,%f\n", brightest_name, maxbright, *radec0)
model.setFieldCenter(*radec0)
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter())
for src in model.sources:
l, m = projection.lm(src.pos.ra, src.pos.dec)
src.setAttribute('r', math.sqrt(l * l + m * m))
return model
def save (model,filename,sources=None,format=None,**kw):
"""
Exports model to a text file
""";
if sources is None:
sources = model.sources;
dprintf(2,"writing %d model sources to text file %s\n",len(sources),filename);
# create catalog parser based on either specified format, or the model format, or the default format
format_str = format or getattr(model,'ASCII_Format',DefaultDMSFormatString);
dprint(2,"format string is",format_str);
# convert this into format dict
fields = [ [field,i] for i,field in enumerate(format_str.split()) ];
if not fields:
raise ValueError,"illegal format string '%s'"%format;
# last fieldname can end with ... ("tags..."), so strip it
if fields[-1][0].endswith('...'):
fields[-1][0] = fields[-1][0][:-3];
# make format dict
format = dict(fields);
nfields = len(fields);
# get minimum necessary fields from format
name_field = format.get('name',None);
# main RA field
ra_rad_field,ra_d_field,ra_h_field,ra_m_field,ra_s_field = \
[ format.get(x,None) for x in 'ra_rad','ra_d','ra_h','ra_m','ra_s' ];
dec_rad_field,dec_d_field,dec_m_field,dec_s_field = \
[ format.get(x,None) for x in 'dec_rad','dec_d','dec_m','dec_s' ];
if ra_h_field is not None:
ra_scale = 15;
ra_d_field = ra_h_field;
else:
ra_scale = 1;
# fields for reference freq and RM and SpI
freq0_field = format.get('freq0',None);
rm_field = format.get('rm',None);
spi_field = format.get('spi',None);
tags_field = format.get('tags',None);
# open file
ff = open(filename,mode="wt");
ff.write("#format: %s\n"%format_str);
# write sources
nsrc = 0;
for src in sources:
# only write points and gaussians
if src.shape is not None and not isinstance(src.shape,ModelClasses.Gaussian):
dprint(3,"skipping source '%s': non-supported type '%s'"%(src.name,src.shape.typecode));
continue;
# prepare field values
fval = ['0']*nfields;
# name
if name_field is not None:
fval[name_field] = src.name;
# position: RA
ra,dec = src.pos.ra,src.pos.dec;
# RA in radians
if ra_rad_field is not None:
fval[ra_rad_field] = str(ra);
ra /= ra_scale;
# RA in h/m/s or d/m/s
if ra_m_field is not None:
ra,ram,ras = src.pos.ra_hms_static(ra,scale=180,prec=1e-4);
fval[ra_m_field] = str(ram);
if ra_s_field is not None:
fval[ra_s_field] = str(ras);
if ra_d_field is not None:
fval[ra_d_field] = str(ra);
elif ra_d_field is not None:
fval[ra_d_field] = str(ra*180/math.pi);
# position: Dec
if dec_rad_field is not None:
fval[dec_rad_field] = str(dec);
if dec_m_field is not None:
dsign,decd,decm,decs = src.pos.dec_sdms();
fval[dec_m_field] = str(decm);
if dec_s_field is not None:
fval[dec_s_field] = str(decs);
if dec_d_field is not None:
fval[dec_d_field] = dsign+str(decd);
elif dec_d_field is not None:
fval[dec_d_field] = str(dec*180/math.pi);
# fluxes
for stokes in "IQUV":
field = format.get(stokes.lower());
if field is not None:
fval[field] = str(getattr(src.flux,stokes,0));
# fractional polarization
if 'pol_frac' in format:
i,q,u = [ getattr(src.flux,stokes,0) for stokes in "IQU" ];
fval[format['pol_frac']] = str(math.sqrt(q*q+u*u)/i);
pa = math.atan2(u,q)/2;
for field,scale in ('pol_pa_rad',1.),('pol_pa_d',DEG):
ifield = format.get(field);
if ifield is not None:
fval[ifield] = str(pa/scale);
# shape
if src.shape:
for parm,sparm in ("emaj","ex"),("emin","ey"),("pa","pa"):
for field,scale in (parm,1.),(parm+'_rad',DEG),(parm+'_d',DEG),(parm+'_m',DEG/60),(parm+'_s',DEG/3600):
ifield = format.get(field.lower());
if ifield is not None:
fval[ifield] = str(getattr(src.shape,sparm,0)/scale);
# RM, spi, freq0
if freq0_field is not None:
freq0 = (src.spectrum and getattr(src.spectrum,'freq0',None)) or getattr(src.flux,'freq0',0);
fval[freq0_field] = str(freq0);
if rm_field is not None:
fval[rm_field] = str(getattr(src.flux,'rm',0));
if spi_field is not None and hasattr(src,'spectrum'):
fval[spi_field] = str(getattr(src.spectrum,'spi',0));
# tags
if tags_field is not None:
outtags = [];
for tag,value in src.getTags():
if isinstance(value,str):
outtags.append("%s=\"%s\""%(tag,value));
elif isinstance(value,bool):
if value:
outtags.append("+"+tag);
else:
outtags.append("-"+tag);
elif isinstance(value,(int,float)):
outtags.append("%s=%f"%(tag,value));
fval[tags_field] = ",".join(outtags);
# write the line
ff.write(" ".join(fval)+"\n");
nsrc += 1;
ff.close();
dprintf(1,"wrote %d sources to file %s\n",nsrc,filename);
def load (filename,format=None,freq0=None,center_on_brightest=False,min_extent=0,verbose=0,**kw):
"""Imports an ASCII table
The 'format' argument can be either a dict (such as the DefaultDMSFormat dict above), or a string such as DefaultDMSFormatString.
(Other possible field names are "ra_d", "ra_rad", "dec_rad", "dec_sign".)
If None is specified, DefaultDMSFormat is used.
The 'freq0' argument supplies a default reference frequency (if one is not contained in the file.)
If 'center_on_brightest' is True, the mpodel field center will be set to the brightest source.
'min_extent' is minimal source extent (in radians), above which a source will be treated as a Gaussian rather than a point component.
"""
srclist = [];
dprint(1,"importing ASCII DMS file",filename);
# brightest source and its coordinates
maxbright = 0;
brightest_name = radec0 = None;
# Get column number associated with field from format dict, as well as the error
# column number. Returns tuple of indices, with None index indicating no such column
def get_field (name):
return format.get(name,None),format.get(name+"_err",None);
# Get column number associated with field from format dict, as well as the error
# column number. Field is an angle thus will be suffixed with _{rad,d,h,m,s}.
# Returns tuple of
# column,scale,err_column,err_scale
# with None index indicating no such column. Scale is scaling factor to convert
# quantity in column to radians
def get_ang_field (name,units=ANGULAR_UNITS):
column = err_column = colunit = errunit = None
units = units or ANGULAR_UNITS;
for unit,scale in units.iteritems():
if column is None:
column = format.get("%s_%s"%(name,unit));
if column is not None:
colunit = scale;
if err_column is None:
err_column = format.get("%s_err_%s"%(name,unit))
if err_column is not None:
errunit = scale;
return column,colunit,err_column,errunit;
# helper function: returns element #num from the fields list, multiplied by scale, or None if no such field
def getval (num,scale=1):
return None if ( num is None or len(fields) <= num ) else float(fields[num])*scale;
# now process file line-by-line
linenum = 0;
format_str = ''
for line in file(filename):
# for the first line, figure out the file format
if not linenum:
if not format and line.startswith("#format:"):
format = line[len("#format:"):].strip();
dprint(1,"file contains format header:",format);
# set default format
if format is None:
format = DefaultDMSFormatString;
# is the format a string rather than a dict? Turn it into a dict then
if isinstance(format,str):
format_str = format;
# make list of fieldname,fieldnumber tuples
fields = [ (field,i) for i,field in enumerate(format.split()) ];
if not fields:
raise ValueError,"illegal format string in file: '%s'"%format;
# last fieldname can end with ... to indicate that it absorbs the rest of the line
if fields[-1][0].endswith('...'):
fields[-1] = (fields[-1][0][:-3],slice(fields[-1][1],None));
# make format dict
format = dict(fields);
elif not isinstance(format,dict):
raise TypeError,"invalid 'format' argument of type %s"%(type(format))
# nf = max(format.itervalues())+1;
# fields = ['---']*nf;
# for field,number in format.iteritems():
# fields[number] = field;
# format_str = " ".join(fields);
# get list of custom attributes from format
custom_attrs = [];
for name,col in format.iteritems():
if name.startswith(":"):
m = re.match("^:(bool|int|float|complex|str):([\w]+)$",name);
if not m:
raise TypeError,"invalid field specification '%s' in format string"%name;
custom_attrs.append((eval(m.group(1)),m.group(2),col));
# get minimum necessary fields from format
name_field = format.get('name',None);
# flux
i_field,i_err_field = get_field("i");
if i_field is None:
raise ValueError,"ASCII format specification lacks mandatory flux field ('i')";
# main RA field
ra_field,ra_scale,ra_err_field,ra_err_scale = get_ang_field('ra',ANGULAR_UNITS_RA);
if ra_field is None:
raise ValueError,"ASCII format specification lacks mandatory Right Ascension field ('ra_h', 'ra_d' or 'ra_rad')";
# main Dec field
dec_field,dec_scale,dec_err_field,dec_err_scale = get_ang_field('dec',ANGULAR_UNITS_DEC);
if dec_field is None:
raise ValueError,"ASCII format specification lacks mandatory Declination field ('dec_d' or 'dec_rad')";
# polarization as QUV
quv_fields = [ get_field(x) for x in ['q','u','v'] ];
# linear polarization as fraction and angle
polfrac_field = format.get('pol_frac',None);
if polfrac_field is not None:
polpa_field,polpa_scale = format.get('pol_pa_d',None),(math.pi/180);
if not polpa_field is not None:
polpa_field,polpa_scale = format.get('pol_pa_rad',None),1;
# fields for extent parameters
extent_fields = [ get_ang_field(x,ANGULAR_UNITS) for x in 'emaj','emin','pa' ];
# all three must be present, else ignore
if any( [ x[0] is None for x in extent_fields ] ):
extent_fields = None;
# fields for reference freq and RM and SpI
freq0_field = format.get('freq0',None);
rm_field,rm_err_field = get_field('rm');
spi_fields = [ get_field('spi') ] + [ get_field('spi%d'%i) for i in range(2,10) ];
tags_slice = format.get('tags',None);
# now go on to process the line
linenum += 1;
try:
# strip whitespace
line = line.strip();
dprintf(4,"%s:%d: read line '%s'\n",filename,linenum,line);
# skip empty or commented lines
if not line or line[0] == '#':
continue;
# split (at whitespace) into fields
fields = line.split();
# get name
name = fields[name_field] if name_field is not None else str(len(srclist)+1);
i = getval(i_field);
i_err = getval(i_err_field);
# get position: RA
ra = getval(ra_field);
ra_err = getval(ra_err_field,ra_scale);
if 'ra_m' in format:
ra += float(fields[format['ra_m']])/60.;
if 'ra_s' in format:
ra += float(fields[format['ra_s']])/3600.;
ra *= ra_scale;
# position: Dec. Separate treatment of sign
dec = abs(getval(dec_field));
dec_err = getval(dec_err_field,dec_scale);
if 'dec_m' in format:
dec += float(fields[format['dec_m']])/60.;
if 'dec_s' in format:
dec += float(fields[format['dec_s']])/3600.;
if fields[format.get('dec_sign',dec_field)][0] == '-':
dec = -dec;
dec *= dec_scale;
# for up position object
pos = ModelClasses.Position(ra,dec,ra_err=ra_err,dec_err=dec_err);
# see if we have freq0
try:
f0 = freq0 or (freq0_field and float(fields[freq0_field]));
except IndexError:
f0 = None;
# set model refrence frequency
if f0 is not None and freq0 is None:
freq0 = f0;
# see if we have Q/U/V
(q,q_err),(u,u_err),(v,v_err) = [ (getval(x),getval(x_err)) for x,x_err in quv_fields ];
if polfrac_field is not None:
pf = fields[polfrac_field];
pf = float(pf[:-1])/100 if pf.endswith("%") else float(pf);
ppa = float(fields[polpa_field])*polpa_scale if polpa_field is not None else 0;
q = i*pf*math.cos(2*ppa);
u = i*pf*math.sin(2*ppa);
v = 0;
# see if we have RM as well. Create flux object (unpolarized, polarized, polarized w/RM)
rm,rm_err = getval(rm_field),getval(rm_err_field);
if q is None:
flux = ModelClasses.Polarization(i,0,0,0,I_err=i_err);
elif f0 is None or rm is None:
flux = ModelClasses.Polarization(i,q,u,v,I_err=i_err,Q_err=q_err,U_err=u_err,V_err=v_err);
else:
flux = ModelClasses.PolarizationWithRM(i,q,u,v,rm,f0,I_err=i_err,Q_err=q_err,U_err=u_err,V_err=v_err,rm_err=rm_err);
# see if we have a spectral index
if f0 is None:
spectrum = None;
else:
spi = [ getval(x) for x,xerr in spi_fields ];
spi_err = [ getval(xerr) for x,xerr in spi_fields ];
dprint(4,name,"spi is",spi,"err is",spi_err)
# if any higher-order spectral terms are specified, include them here but trim off all trailing zeroes
while spi and not spi[-1]:
del spi[-1];
del spi_err[-1]
if not spi:
spectrum = None;
elif len(spi) == 1:
spectrum = ModelClasses.SpectralIndex(spi[0],f0);
if spi_err[0] is not None:
spectrum.spi_err = spi_err[0];
else:
spectrum = ModelClasses.SpectralIndex(spi,f0);
if any([ x is not None for x in spi_err ]):
spectrum.spi_err = spi_err;
# see if we have extent parameters
ex = ey = pa = 0;
if extent_fields:
ex,ey,pa = [ ( getval(x[0],x[1]) or 0 ) for x in extent_fields ];
extent_errors = [ getval(x[2],x[3]) for x in extent_fields ];
# form up shape object
if (ex or ey) and max(ex,ey) >= min_extent:
shape = ModelClasses.Gaussian(ex,ey,pa);
for ifield,field in enumerate(['ex','ey','pa']):
if extent_errors[ifield] is not None:
shape.setAttribute(field+"_err",extent_errors[ifield]);
else:
shape = None;
# get tags
tagdict = {};
if tags_slice:
try:
tags = fields[tags_slice];
except IndexError:
pass;
for tagstr1 in tags:
for tagstr in tagstr1.split(","):
if tagstr[0] == "+":
tagname,value = tagstr[1:],True;
elif tagstr[0] == "-":
tagname,value = tagstr[1:],False;
elif "=" in tagstr:
tagname,value = tagstr.split("=",1);
if value[0] in "'\"" and value[-1] in "'\"":
value = value[1:-1];
else:
try:
value = float(value);
except:
continue;
else:
tagname,value = tagstr,True;
tagdict[tagname] = value;
# OK, now form up the source object
# now create a source object
dprint(3,name,ra,dec,i,q,u,v);
src = SkyModel.Source(name,pos,flux,shape=shape,spectrum=spectrum,**tagdict);
# get custom attributes
for type_,attr,column in custom_attrs:
if column is not None and len(fields) > column:
src.setAttribute(attr,type_(fields[column]));
# add to source list
srclist.append(src);
# check if it's the brightest
brightness = src.brightness();
if brightness > maxbright:
maxbright = brightness;
brightest_name = src.name;
radec0 = ra,dec;
except:
if verbose:
traceback.print_exc();
dprintf(0,"%s:%d: %s, skipping\n",filename,linenum,str(sys.exc_info()[1]));
dprintf(2,"imported %d sources from file %s\n",len(srclist),filename);
# create model
model = ModelClasses.SkyModel(*srclist);
if freq0 is not None:
model.setRefFreq(freq0);
# set model format
model.setAttribute("ASCII_Format",format_str);
# setup model center
if center_on_brightest and radec0:
dprintf(2,"brightest source is %s (%g Jy) at %f,%f\n",brightest_name,maxbright,*radec0);
model.setFieldCenter(*radec0);
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter());
for src in model.sources:
l,m = projection.lm(src.pos.ra,src.pos.dec);
src.setAttribute('r',math.sqrt(l*l+m*m));
return model;
def load(filename, freq0=None, center_on_brightest=False, **kw):
"""Imports an BBS catalog file
The 'format' argument can be either a dict (such as the DefaultDMSFormat dict above), or a string such as DefaultDMSFormatString.
(Other possible field names are "ra_d", "ra_rad", "dec_rad", "dec_sign".)
If None is specified, DefaultDMSFormat is used.
The 'freq0' argument supplies a default reference frequency (if one is not contained in the file.)
If 'center_on_brightest' is True, the mpodel field center will be set to the brightest source,
else to the center of the first patch.
"""
srclist = []
dprint(1, "importing BBS source table", filename)
# read file
ff = open(filename)
# first line must be a format string: extract it
line0 = ff.readline().strip()
match = re.match("#\s*\((.+)\)\s*=\s*format", line0)
if not match:
raise ValueError("line 1 is not a valid format specification")
format_str = match.group(1)
# create format parser from this string
parser = CatalogParser(format_str)
# check for mandatory fields
for field in "Name", "Type":
if not parser.defines(field):
raise ValueError("Table lacks mandatory field '%s'" % field)
maxbright = 0
patches = []
ref_freq = freq0
# now process file line-by-line
linenum = 1
for line in ff:
linenum += 1
try:
# parse one line
dprint(4, "read line:", line)
catline = parser.parse(line, linenum)
if not catline:
continue
dprint(5, "line %d: " % linenum, catline.__dict__)
# is it a patch record?
patchname = getattr(catline, 'Patch', '')
if not catline.Name:
dprintf(2, "%s:%d: patch %s\n", filename, linenum, patchname)
patches.append((patchname, catline.ra_rad, catline.dec_rad))
continue
# form up name
name = "%s:%s" % (patchname, catline.Name) if patchname else catline.Name
# check source type
stype = catline.Type.upper()
if stype not in ("POINT", "GAUSSIAN"):
raise ValueError("unsupported source type %s" % stype)
# see if we have freq0
if freq0:
f0 = freq0
elif hasattr(catline, 'ReferenceFrequency'):
f0 = float(catline.ReferenceFrequency or '0')
else:
f0 = None
# set model refrence frequency
if f0 is not None and ref_freq is None:
ref_freq = f0
# see if we have Q/U/V
i, q, u, v = [float(getattr(catline, stokes, '0') or '0') for stokes in "IQUV"]
# see if we have RM as well. Create flux object (unpolarized, polarized, polarized w/RM)
if f0 is not None and hasattr(catline, 'RotationMeasure'):
flux = ModelClasses.PolarizationWithRM(i, q, u, v, float(catline.RotationMeasure or '0'), f0)
else:
flux = ModelClasses.Polarization(i, q, u, v)
# see if we have a spectral index
if f0 is not None and hasattr(catline, 'SpectralIndex:0'):
spectrum = ModelClasses.SpectralIndex(float(getattr(catline, 'SpectralIndex:0') or '0'), f0)
else:
spectrum = None
# see if we have extent parameters
if stype == "GAUSSIAN":
ex = float(getattr(catline, "MajorAxis", "0") or "0")
ey = float(getattr(catline, "MinorAxis", "0") or "0")
pa = float(getattr(catline, "Orientation", "0") or "0")
shape = ModelClasses.Gaussian(ex, ey, pa)
else:
shape = None
# create tags
tags = {}
for field in "Patch", "Category":
if hasattr(catline, field):
tags['BBS_%s' % field] = getattr(catline, field)
# OK, now form up the source object
# position
pos = ModelClasses.Position(catline.ra_rad, catline.dec_rad)
# now create a source object
src = SkyModel.Source(name, pos, flux, shape=shape, spectrum=spectrum, **tags)
srclist.append(src)
# check if it's the brightest
brightness = src.brightness()
if brightness > maxbright:
maxbright = brightness
brightest_name = src.name
radec0 = catline.ra_rad, catline.dec_rad
except:
dprintf(0, "%s:%d: %s, skipping\n", filename, linenum, str(sys.exc_info()[1]))
dprintf(2, "imported %d sources from file %s\n", len(srclist), filename)
# create model
model = ModelClasses.SkyModel(*srclist)
if ref_freq is not None:
model.setRefFreq(ref_freq)
# setup model center
if center_on_brightest and radec0:
dprintf(2, "setting model centre to brightest source %s (%g Jy) at %f,%f\n", brightest_name, maxbright,
*radec0)
model.setFieldCenter(*radec0)
elif patches:
name, ra, dec = patches[0]
dprintf(2, "setting model centre to first patch %s at %f,%f\n", name, ra, dec)
model.setFieldCenter(ra, dec)
# map patches to model tags
model.setAttribute("BBS_Patches", patches)
model.setAttribute("BBS_Format", format_str)
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter())
for src in model.sources:
l, m = projection.lm(src.pos.ra, src.pos.dec)
src.setAttribute('r', math.sqrt(l * l + m * m))
return model
def save(model, filename, sources=None, format=None, **kw):
"""Exports model to a BBS catalog file"""
if sources is None:
sources = model.sources
dprintf(2, "writing %d model sources to BBS file %s\n", len(sources), filename)
# create catalog parser based on either specified format, or the model format, or the default format
format = format or getattr(model, 'BBS_Format',
"Name, Type, Patch, Ra, Dec, I, Q, U, V, ReferenceFrequency, SpectralIndexDegree='0', SpectralIndex:0='0.0', MajorAxis, MinorAxis, Orientation")
dprint(2, "format string is", format)
parser = CatalogParser(format)
# check for mandatory fields
for field in "Name", "Type":
if not parser.defines(field):
raise ValueError("Output format lacks mandatory field '%s'" % field)
# open file
ff = open(filename, mode="wt")
ff.write("# (%s) = format\n# The above line defines the field order and is required.\n\n" % format)
# write patches
for name, ra, dec in getattr(model, "BBS_Patches", []):
catline = parser.newline()
catline.Patch = name
catline.setPosition(ra, dec)
ff.write(catline.makeStr() + "\n")
ff.write("\n")
# write sources
nsrc = 0
for src in sources:
catline = parser.newline()
# type
if src.shape is None:
catline.Type = "POINT"
elif isinstance(src.shape, ModelClasses.Gaussian):
catline.Type = "GAUSSIAN"
else:
dprint(3, "skipping source '%s': non-supported type '%s'" % (src.name, src.shape.typecode))
continue
# name and patch
name = src.name
patch = getattr(src, 'BBS_Patch', '')
if patch and name.startswith(patch + ':'):
name = name[(len(patch) + 1):]
catline.Name = name
setattr(catline, 'Patch', patch)
# position
catline.setPosition(src.pos.ra, src.pos.dec)
# fluxes
for stokes in "IQUV":
setattr(catline, stokes, str(getattr(src.flux, stokes, 0.)))
# reference freq
freq0 = (src.spectrum and getattr(src.spectrum, 'freq0', None)) or getattr(src.flux, 'freq0', None)
if freq0 is not None:
setattr(catline, 'ReferenceFrequency', str(freq0))
# RM, spi
if isinstance(src.spectrum, ModelClasses.SpectralIndex):
setattr(catline, 'SpectralIndexDegree', '0')
setattr(catline, 'SpectralIndex:0', str(src.spectrum.spi))
if isinstance(src.flux, ModelClasses.PolarizationWithRM):
setattr(catline, 'RotationMeasure', str(src.flux.rm))
# shape
if isinstance(src.shape, ModelClasses.Gaussian):
setattr(catline, 'MajorAxis', src.shape.ex)
setattr(catline, 'MinorAxis', src.shape.ey)
setattr(catline, 'Orientation', src.shape.pa)
# write line
ff.write(catline.makeStr() + "\n")
nsrc += 1
ff.close()
dprintf(1, "wrote %d sources to file %s\n", nsrc, filename)
def load (filename,import_src=True,import_cc=True,min_extent=0,**kw):
"""Imports a NEWSTAR MDL file.
min_extent is minimal source extent (in radians), above which a source will be treated as a Gaussian rather than a point component.
import_src=False causes source components to be omitted
import_cc=False causes clean components to be omitted
""";
srclist = [];
dprint(1,"importing NEWSTAR file",filename);
# build the LSM from a NewStar .MDL model file
# if only_cleancomp=True, only clean components are used to build the LSM
# if no_cleancomp=True, no clean components are used to build the LSM
ff = open(filename,mode="rb");
### read GFH and MDH headers -- 512 bytes
try:
gfh = numpy.fromfile(ff,dtype=numpy.uint8,count=512);
mdh = numpy.fromfile(ff,dtype=numpy.uint8,count=64);
# parse headers
ftype,fhlen,fver,crdate,crtime,rrdate,rrtime,rcount,nname = parseGFH(gfh);
if ftype != ".MDL":
raise TypeError;
maxlin,modptr,nsources,mtype,mepoch,ra0,dec0,freq0 = parseMDH(mdh);
beam_const = 65*1e-9*freq0;
## temp dict to hold unique nodenames
unamedict={}
### Models -- 56 bytes
for ii in xrange(0,nsources):
mdl = numpy.fromfile(ff,dtype=numpy.uint8,count=56)
### source parameters
sI,ll,mm,id,sQ,sU,sV,eX,eY,eP,SI,RM = struct.unpack('fffiffffffff',mdl[0:48])
### type bits
bit1,bit2 = struct.unpack('BB',mdl[52:54]);
# convert fluxes
sI *= 0.005 # convert from WU to Jy (1WU=5mJy)
sQ *= sI;
sU *= sI;
sV *= sI;
# Interpret bitflags 1: bit 0= extended; bit 1= Q|U|V <>0 and no longer used according to Wim
fl_ext = bit1&1;
# Interpret bitflags 2: bit 0= clean component; bit 3= beamed
fl_cc = bit2&1;
fl_beamed = bit2&8;
### extended source params: in arcsec, so multiply by ???
if fl_ext:
## the procedure is NMOEXT in nscan/nmoext.for
if eP == 0 and eX == eY:
r0 = 0
else:
r0 = .5*math.atan2(-eP,eY-eX)
r1 = math.sqrt(eP*eP+(eX-eY)*(eX-eY))
r2 = eX+eY
eX = 2*math.sqrt(abs(0.5*(r2+r1)))
eY = 2*math.sqrt(abs(0.5*(r2-r1)))
eP = r0
# NEWSTAR MDL lists might have same source twice if they are
# clean components, so make a unique name for them
bname='N'+str(id);
if unamedict.has_key(bname):
uniqname = bname+'_'+str(unamedict[bname])
unamedict[bname] += 1
else:
uniqname = bname
unamedict[bname] = 1
# compose source information
pos = ModelClasses.Position(*lm_ncp_to_radec(ra0,dec0,ll,mm));
flux = ModelClasses.PolarizationWithRM(sI,sQ,sU,sV,RM,freq0);
spectrum = ModelClasses.SpectralIndex(SI,freq0);
tags = {};
# work out beam gain and apparent flux
tags['_lm_ncp'] = (ll,mm);
tags['_newstar_r'] = tags['r'] = r = math.sqrt(ll*ll+mm*mm);
tags['newstar_beamgain'] = bg = max(math.cos(beam_const*r)**6,.01);
tags['newstar_id'] = id;
if fl_beamed:
tags['Iapp'] = sI*bg;
tags['newstar_beamed'] = True;
tags['flux_intrinsic'] = True;
else:
tags['flux_apparent'] = True;
# make some tags based on model flags
if fl_cc:
tags['newstar_cc'] = True;
# make shape if extended
if fl_ext and max(eX,eY) >= min_extent:
shape = ModelClasses.Gaussian(eX,eY,eP);
else:
shape = None;
# compute apparent flux
src = SkyModel.Source(uniqname,pos,flux,shape=shape,spectrum=spectrum,**tags);
srclist.append(src);
except:
traceback.print_exc();
raise TypeError("%s does not appear to be a valid NEWSTAR MDL file"%filename);
dprintf(2,"imported %d sources from file %s\n",len(srclist),filename);
return ModelClasses.SkyModel(ra0=ra0,dec0=dec0,freq0=freq0,pbexp='max(cos(65*1e-9*fq*r)**6,.01)',*srclist);
def save (model,filename,freq0=None,sources=None,**kw):
"""Saves model to a NEWSTAR MDL file.
The MDL file must exist, since the existing header is reused.
'sources' is a list of sources to write, if None, then model.sources is used.
"""
if sources is None:
sources = model.sources;
dprintf(2,"writing %s model sources to NEWSTAR file\n",len(sources),filename);
ra0,dec0 = model.fieldCenter();
freq0 = freq0 or model.refFreq();
# if freq0 is not specified, scan sources
if freq0 is None:
for src in sources:
freq0 = (src.spectrum and getattr(src.spectrum,'freq0',None)) or getattr(src.flux,'freq0',None);
if freq0:
break;
else:
raise ValueError("unable to determine NEWSTAR model reference frequency, please specify one explicitly.");
ff = open(filename,mode="wb");
### create GFH header
gfh = numpy.zeros(512,dtype=numpy.uint8);
datestr = time.strftime("%d-%m-%Y");
timestr = time.strftime("%H:%M");
struct.pack_into("4sii11s5s11s5si80sB",gfh,0,".MDL",512,1,
datestr,timestr,datestr,timestr,0,
os.path.splitext(os.path.basename(filename))[0],6); # 6=datatype
# link1/link2 gives the header size actually
struct.pack_into("ii",gfh,152,512,512);
gfh.tofile(ff);
# create MDH header
mdh = numpy.zeros(64,dtype=numpy.uint8);
struct.pack_into('iiii',mdh,12,1,576,0,2); # maxlin,pointer,num_sources,mtype
struct.pack_into('f',mdh,28,getattr(model,'epoch',2000));
struct.pack_into('ddd',mdh,32,ra0/(2*math.pi),dec0/(2*math.pi),freq0*1e-6);
mdh.tofile(ff);
# get the max ID, if specified
max_id = max([ getattr(src,'newstar_id',0) for src in sources ]);
# now loop over model sources
# count how many are written out -- only point sources and gaussians are actually written out, the rest are skipped
nsrc = 0;
for src in sources:
# create empty newstar source structure
mdl = numpy.zeros(56,dtype=numpy.uint8);
if src.shape and not isinstance(src.shape,ModelClasses.Gaussian):
dprint(3,"skipping source '%s': non-supported type '%s'"%(src.name,src.shape.typecode));
continue;
stI = src.flux.I;
# get l,m NCP position -- either from tag, or compute
lm = getattr(src,'_lm_ncp',None);
if lm:
if isinstance(lm,(tuple,list)) and len(lm) == 2:
l,m = lm;
else:
dprint(0,"warning: skipping source '%s' because its _lm_ncp attribute is malformed (tuple of 2 values expected)"%src.name);
continue;
else:
l,m = radec_to_lm_ncp(ra0,dec0,src.pos.ra,src.pos.dec);
# update source count
nsrc += 1;
# generate source id
src_id = getattr(src,'newstar_id',None);
if src_id is None:
src_id = max_id = max_id+1;
# encode position, flux, identifier -- also, convert flux from Jy to WU to Jy (1WU=5mJy)
struct.pack_into('fffi',mdl,0,stI/0.005,l,m,src_id);
# encode fractional polarization
struct.pack_into('fff',mdl,16,*[ getattr(src.flux,stokes,0.0)/stI for stokes in "QUV" ]);
## encode flag & type bits
## Flag: bit 0= extended; bit 1= Q|U|V <>0 and no longer used according to Wim
## Type: bit 0= clean component; bit 3= beamed
beamed = getattr(src,'flux_intrinsic',False) or getattr(src,'newstar_beamed',False);
struct.pack_into('BB',mdl,52,
1 if src.shape else 0,
(1 if getattr(src,'newstar_cc',False) else 0) | (8 if beamed else 0));
### extended source parameters
if src.shape:
## the procedure is NMOEXF in nscan/nmoext.for
R0 = math.cos(src.shape.pa);
R1 = -math.sin(src.shape.pa);
R2 = (.5*src.shape.ex)**2;
R3 = (.5*src.shape.ey)**2;
ex = R2*R1*R1+R3*R0*R0
ey = R2*R0*R0+R3*R1*R1
pa = 2*(R2-R3)*R0*R1
struct.pack_into('fff',mdl,28,ex,ey,pa);
### spectral index
if isinstance(src.spectrum,ModelClasses.SpectralIndex):
struct.pack_into('f',mdl,40,src.spectrum.spi);
if isinstance(src.flux,ModelClasses.PolarizationWithRM):
struct.pack_into('f',mdl,44,src.flux.rm);
mdl.tofile(ff);
# update MDH header with the new number of sources
struct.pack_into('i',mdh,20,nsrc);
ff.seek(512);
mdh.tofile(ff);
ff.close();
dprintf(1,"wrote %d sources to file %s\n",nsrc,filename);
def load (filename,format=None,freq0=None,center_on_brightest=False,min_extent=0,**kw):
"""Imports an ASCII table
The 'format' argument can be either a dict (such as the DefaultDMSFormat dict above), or a string such as DefaultDMSFormatString.
(Other possible field names are "ra_d", "ra_rad", "dec_rad", "dec_sign".)
If None is specified, DefaultDMSFormat is used.
The 'freq0' argument supplies a default reference frequency (if one is not contained in the file.)
If 'center_on_brightest' is True, the mpodel field center will be set to the brightest source.
'min_extent' is minimal source extent (in radians), above which a source will be treated as a Gaussian rather than a point component.
"""
srclist = [];
dprint(1,"importing ASCII DMS file",filename);
# brightest source and its coordinates
maxbright = 0;
brightest_name = radec0 = None;
# now process file line-by-line
linenum = 0;
format_str = ''
for line in file(filename):
# for the first line, firgure out the file format
if not linenum:
if not format and line.startswith("#format:"):
format = line[len("#format:"):].strip();
dprint(1,"file contains format header:",format);
# set default format
if format is None:
format = DefaultDMSFormatString;
# is the format a string rather than a dict? Turn it into a dict then
if isinstance(format,str):
format_str = format;
# make list of fieldname,fieldnumber tuples
fields = [ (field,i) for i,field in enumerate(format.split()) ];
if not fields:
raise ValueError,"illegal format string in file: '%s'"%format;
# last fieldname can end with ... to indicate that it absorbs the rest of the line
if fields[-1][0].endswith('...'):
fields[-1] = (fields[-1][0][:-3],slice(fields[-1][1],None));
# make format dict
format = dict(fields);
elif not isinstance(format,dict):
raise TypeError,"invalid 'format' argument of type %s"%(type(format))
nf = max(format.itervalues())+1;
fields = ['---']*nf;
for field,number in format.iteritems():
fields[number] = field;
format_str = " ".join(fields);
# get minimum necessary fields from format
name_field = format.get('name',None);
# flux
try:
i_field = format['i'];
except KeyError:
raise ValueError,"ASCII format specification lacks mandatory flux field ('i')";
# main RA field
if 'ra_h' in format:
ra_field,ra_scale = format['ra_h'],(math.pi/12);
elif 'ra_d' in format:
ra_field,ra_scale = format['ra_d'],(math.pi/180);
elif 'ra_rad' in format:
ra_field,ra_scale = format['ra_rad'],1.;
else:
raise ValueError,"ASCII format specification lacks mandatory Right Ascension field ('ra_h', 'ra_d' or 'ra_rad')";
# main Dec field
if 'dec_d' in format:
dec_field,dec_scale = format['dec_d'],(math.pi/180);
elif 'dec_rad' in format:
dec_field,dec_scale = format['dec_rad'],1.;
else:
raise ValueError,"ASCII format specification lacks mandatory Declination field ('dec_d' or 'dec_rad')";
# polarization as QUV
try:
quv_fields = [ format[x] for x in ['q','u','v'] ];
except KeyError:
quv_fields = None;
# linear polarization as fraction and angle
polfrac_field = format.get('pol_frac',None);
if polfrac_field is not None:
polpa_field,polpa_scale = format.get('pol_pa_d',None),(math.pi/180);
if not polpa_field is not None:
polpa_field,polpa_scale = format.get('pol_pa_rad',None),1;
# fields for extent parameters
ext_fields = [];
for ext in 'emaj','emin','pa':
for field,scale in (ext,1.),(ext+"_rad",1.),(ext+'_d',DEG),(ext+'_m',DEG/60),(ext+'_s',DEG/3600):
if field in format:
ext_fields.append((format[field],scale));
break;
# if not all three accumulated, ignore
if len(ext_fields) != 3:
ext_fields = None;
# fields for reference freq and RM and SpI
freq0_field = format.get('freq0',None);
rm_field = format.get('rm',None);
spi_field = format.get('spi',None);
spi2_field = [ format.get('spi%d'%i,None) for i in range(2,10) ];
tags_slice = format.get('tags',None);
# now go on to process the line
linenum += 1;
try:
# strip whitespace
line = line.strip();
dprintf(4,"%s:%d: read line '%s'\n",filename,linenum,line);
# skip empty or commented lines
if not line or line[0] == '#':
continue;
# split (at whitespace) into fields
fields = line.split();
# get name
name = fields[name_field] if name_field is not None else str(len(srclist)+1);
i = float(fields[i_field]);
# get position: RA
ra = float(fields[ra_field]);
if 'ra_m' in format:
ra += float(fields[format['ra_m']])/60.;
if 'ra_s' in format:
ra += float(fields[format['ra_s']])/3600.;
ra *= ra_scale;
# position: Dec. Separate treatment of sign
dec = abs(float(fields[dec_field]));
if 'dec_m' in format:
dec += float(fields[format['dec_m']])/60.;
if 'dec_s' in format:
dec += float(fields[format['dec_s']])/3600.;
if fields[format.get('dec_sign',dec_field)][0] == '-':
dec = -dec;
dec *= dec_scale;
# see if we have freq0
try:
f0 = freq0 or (freq0_field and float(fields[freq0_field]));
except IndexError:
f0 = None;
# set model refrence frequency
if f0 is not None and freq0 is None:
freq0 = f0;
# see if we have Q/U/V
q=u=v=None;
if quv_fields:
try:
q,u,v = map(float,[fields[x] for x in quv_fields]);
except IndexError:
pass;
if polfrac_field is not None:
pf = fields[polfrac_field];
pf = float(pf[:-1])/100 if pf.endswith("%") else float(pf);
ppa = float(fields[polpa_field])*polpa_scale if polpa_field is not None else 0;
q = i*pf*math.cos(2*ppa);
u = i*pf*math.sin(2*ppa);
v = 0;
# see if we have RM as well. Create flux object (unpolarized, polarized, polarized w/RM)
if q is None:
flux = ModelClasses.Polarization(i,0,0,0);
elif f0 is None or rm_field is None or rm_field >= len(fields):
flux = ModelClasses.Polarization(i,q,u,v);
else:
flux = ModelClasses.PolarizationWithRM(i,q,u,v,float(fields[rm_field]),f0);
# see if we have a spectral index
if f0 is None or spi_field is None or spi_field >= len(fields):
spectrum = None;
else:
spi = [ float(fields[spi_field]) ] + \
[ (float(fields[x]) if x is not None else 0) for x in spi2_field ];
# if any higher-order spectral terms are specified, include them here
# but trim off all trailing zeroes
while len(spi)>1 and not spi[-1]:
del spi[-1];
if len(spi) == 1:
spi = spi[0];
spectrum = ModelClasses.SpectralIndex(spi,f0);
# see if we have extent parameters
ex=ey=pa=0;
if ext_fields:
try:
ex,ey,pa = [ float(fields[num])*scale for num,scale in ext_fields ];
except IndexError:
pass;
# form up shape object
if (ex or ey) and max(ex,ey) >= min_extent:
shape = ModelClasses.Gaussian(ex,ey,pa);
else:
shape = None;
# get tags
tagdict = {};
if tags_slice:
try:
tags = fields[tags_slice];
except IndexError:
pass;
for tagstr1 in tags:
for tagstr in tagstr1.split(","):
if tagstr[0] == "+":
tagname,value = tagstr[1:],True;
elif tagstr[0] == "-":
tagname,value = tagstr[1:],False;
elif "=" in tagstr:
tagname,value = tagstr.split("=",1);
if value[0] in "'\"" and value[-1] in "'\"":
value = value[1:-1];
else:
try:
value = float(value);
except:
continue;
else:
tagname,value = tagstr,True;
tagdict[tagname] = value;
# OK, now form up the source object
# position
pos = ModelClasses.Position(ra,dec);
# now create a source object
dprint(3,name,ra,dec,i,q,u,v);
src = SkyModel.Source(name,pos,flux,shape=shape,spectrum=spectrum,**tagdict);
srclist.append(src);
# check if it's the brightest
brightness = src.brightness();
if brightness > maxbright:
maxbright = brightness;
brightest_name = src.name;
radec0 = ra,dec;
except:
dprintf(0,"%s:%d: %s, skipping\n",filename,linenum,str(sys.exc_info()[1]));
dprintf(2,"imported %d sources from file %s\n",len(srclist),filename);
# create model
model = ModelClasses.SkyModel(*srclist);
if freq0 is not None:
model.setRefFreq(freq0);
# set model format
model.setAttribute("ASCII_Format",format_str);
# setup model center
if center_on_brightest and radec0:
dprintf(2,"brightest source is %s (%g Jy) at %f,%f\n",brightest_name,maxbright,*radec0);
model.setFieldCenter(*radec0);
# setup radial distances
projection = Coordinates.Projection.SinWCS(*model.fieldCenter());
for src in model.sources:
l,m = projection.lm(src.pos.ra,src.pos.dec);
src.setAttribute('r',math.sqrt(l*l+m*m));
return model;