def select(self, data0):
from esutil.numpy_util import strmatch
from .select import Selector
selector=Selector()
logic=selector.get_logic(data0, self['setname'])
# these can be applied in addition to the set logic
if 'objtype' in self:
if self['objtype'] is not None:
logic=logic & strmatch(data0['model'],self['objtype'])
for name in ['sratio','s2n','Ts2n','s2','Tmean','mag','prob']:
rname='%s_range' % name
if name=='mag':
name='mag_auto_r'
if name=='prob':
name='fit_prob'
if name=='s2n':
name='s2n_w'
if rname in self:
r=self[rname]
logic=logic & ((data0[name] > r[0]) & (data0[name] < r[1]))
w,=where(logic)
if w.size == 0:
data=None
else:
data=data0[w]
return data
def get_logic(self, data, setname):
from esutil.numpy_util import strmatch
logic = (data['flags']==0) | (data['flags'] == 2**16)
logic=logic & (data['s2n_w'] > 10) & (data['s2n_w'] < 1.e6)
# has minimal effect for use1
#logic=logic & (data['Ts2n'] > 2) & (data['Ts2n'] < 1.e6)
# has minimal effect for use1
#logic=logic & (data['Tmean'] > 2) & (data['Ts2n'] < 1.e6)
if setname=='use0':
# default set
pass
elif setname=='use1':
isdev=strmatch(data['model'],'gdev')
isexp=strmatch(data['model'],'gexp')
Ts2n20=(data['Ts2n'] > 20)
logic=logic & (isexp | (isdev & Ts2n20) )
elif setname=='use2':
isexp=strmatch(data['model'],'gexp')
logic = logic & isexp
elif setname=='use3':
Ts2n20=(data['Ts2n'] > 20)
logic = logic & Ts2n20
elif setname=='use4':
isexp=strmatch(data['model'],'gexp')
Ts2n20=(data['Ts2n'] > 20)
logic = logic & isexp & Ts2n20
elif setname=='use5':
# same as use1 but with Ts2n > 3.5
isdev=strmatch(data['model'],'gdev')
isexp=strmatch(data['model'],'gexp')
Ts2n20=(data['Ts2n'] > 20)
Ts2n3_5=(data['Ts2n'] > 3.5)
logic=logic & ((isexp & Ts2n3_5) | (isdev & Ts2n20) )
else:
raise ValueError("bad use name: '%s'" % setname)
return logic
def read_output_set(run, psfnums, shnums,
objtype=None,
s2n_field='s2n_w',
s2n_min=None,
s2n_max=None,
s2_max=None,
gsens_min=None,
gerr_max=None,
columns=None,
subtract_mean=False,
progress=False):
"""
Read some data based on the input.
Multiple files may be read. If files are missing they will be skipped
Note only a single shear number is expected but many psfnums can
be sent.
Only those with flags==0 are kept.
parameters
----------
run: string
run id
psfnums: integers
the psf numbers to read
shnums: integers
The shear numbers to read.
objtype: string, optional
optionally select only objects with this best-fit model
columns: optional
only return these columns
subtract_mean: bool, optional
Calculate the mean g and subtract it
"""
from esutil.numpy_util import strmatch, combine_arrlist
psfnums=get_psfnums(psfnums)
shnums=get_shnums(shnums)
ntot=len(shnums)*len(psfnums)*62
itot=1
if progress:
from progressbar import ProgressBar
prog=ProgressBar(width=70, color='green')
#prog=ProgressBar(width=70, color='green', block='▣', empty='□')
#prog=ProgressBar(width=70, color='green', block='◧', empty='◫')
#prog=ProgressBar(width=70, color='green', block='■', empty='□')
#prog=ProgressBar(width=70, color='green', block='=', empty='-')
datalist=[]
for shnum in shnums:
shlist=[]
for psfnum in psfnums:
for ccd in xrange(1,62+1):
if progress:
#prog.update(frac=float(itot)/ntot,
# message='%s/%s' % (itot,ntot))
prog.update(frac=float(itot)/ntot)
itot += 1
fname=get_output_path(run=run, psfnum=psfnum, shnum=shnum,
ccd=ccd, ftype='shear')
if os.path.exists(fname):
data0=read_fits_output(run=run, psfnum=psfnum,
shnum=shnum, ccd=ccd,
ftype='shear',
columns=columns,
verbose=False)
logic=(data0['flags']==0) | (data0['flags']==65536)
if objtype:
logic=logic & strmatch(data0['model'],objtype)
if s2n_min is not None:
logic=logic & (data0[s2n_field] > s2n_min)
if s2n_max is not None:
logic=logic & (data0[s2n_field] < s2n_max)
if s2_max is not None:
logic=logic & (data0['s2'] < s2_max)
if gsens_min is not None:
logic=logic \
& (data0['gsens'][:,0] > gsens_min) \
& (data0['gsens'][:,1] > gsens_min)
if gerr_max is not None:
g1err=sqrt(data0['gcov'][:,0,0])
g2err=sqrt(data0['gcov'][:,1,1])
logic=logic \
& (g1err < gerr_max) & (g2err < gerr_max)
wkeep,=where(logic)
if wkeep.size==0:
print 'No objects passed cuts'
else:
data0=data0[wkeep]
shlist.append(data0)
shdata=combine_arrlist(shlist)
if subtract_mean:
g1mean = shdata['g'][:,0].mean()
g2mean = shdata['g'][:,1].mean()
shdata['g'][:,0] -= g1mean
shdata['g'][:,1] -= g2mean
datalist.append(shdata)
if len(datalist)==0:
raise RuntimeError("no outputs were found")
data=combine_arrlist(datalist)
return data
