def cosmo(self):
try:
if self.kwargs['cosmology'] == 'survey':
# survey cosmology
cat = Catalog(self.cat_corr)
self.cosmo = cat.cosmo()
return self.cosmo
else:
# default fiducial cosmology (hardcoded)
omega_m = 0.31
except KeyError:
omega_m = 0.31 # default
# survey cosmology
cosmo = {}
cosmo['omega_M_0'] = omega_m
cosmo['omega_lambda_0'] = 1.0 - omega_m
cosmo['h'] = 0.676
cosmo = cosmos.distance.set_omega_k_0(cosmo)
self.cosmos = cosmo
return self.cosmos
def __init__(self, cat_corr, **kwargs):
""" A class describing galaxy catalog of simulations or BOSS data.
Corresponds to an ASCII file with galaxy/random catalog
Parameters
----------
cat_corr : Catalog correction Dictionary
"""
self.cat_corr = cat_corr.copy()
self.kwargs = kwargs
# catalog
self.catclass = Catalog(self.cat_corr)
# galaxy properties
self.ra = None
self.dec = None
self.z = None
self.wfc = None
self.weight = None
self.comp = None
self.cosmos = None # cosmology of catalog
self.file_name = self.file()
class Data(object):
def __init__(self, cat_corr, **kwargs):
""" A class describing galaxy catalog of simulations or BOSS data.
Corresponds to an ASCII file with galaxy/random catalog
Parameters
----------
cat_corr : Catalog correction Dictionary
"""
self.cat_corr = cat_corr.copy()
self.kwargs = kwargs
# catalog
self.catclass = Catalog(self.cat_corr)
# galaxy properties
self.ra = None
self.dec = None
self.z = None
self.wfc = None
self.weight = None
self.comp = None
self.cosmos = None # cosmology of catalog
self.file_name = self.file()
def read(self):
""" Read galaxy/random catalog data
"""
data_cols = self.datacolumns()
self.data_columns = self.datacolumns()
datah = np.loadtxt(
self.file_name,
skiprows=1,
unpack=True,
usecols=range(len(data_cols))
)
for i_col, col in enumerate(data_cols):
setattr(self, col, datah[i_col])
return None
def build(self):
''' Construct the default galaxy catalog.
Notes
-----
* Tiling Mock : Reads in true mock catalogs and imposes predetermined redshift
limits on them and attaches a flag mostly hardcoded since it's a simple procedure
* QPM: Handles messy weights
* PATCHY: Returns mocks with only necessary columns and w_fc = 1
* Everything is very hardcoded
'''
catalog = (self.cat_corr)['catalog']
output_file = self.file_name
if catalog['name'].lower() == 'nseries': # N Series
# read in original files from Jeremy and adjust them to make them
# easier to use for fiber collisions
# read rdzw file
data_dir = '/mount/riachuelo1/hahn/data/Nseries/'
orig_file = ''.join([
data_dir,
'CutskyN', str(catalog['n_mock']), '.rdzwc'
])
orig_ra, orig_dec, orig_z, orig_wfc, orig_zupw, orig_upw_index = np.loadtxt(
orig_file,
unpack = True,
usecols=[0,1,2,4,5,6]
)
# file with completeness
mask_file = ''.join([
data_dir,
'CutskyN', str(catalog['n_mock']), '.mask_info'
])
orig_wcomp = np.loadtxt(
mask_file,
unpack = True,
usecols = [0]
)
# true wfc
true_wfc = np.array([ 1.0 for i in range(len(orig_wfc)) ])
# write to file
data_list = [orig_ra, orig_dec, orig_z, true_wfc, orig_wcomp, orig_zupw, orig_upw_index]
elif catalog['name'].lower() == 'qpm': # QPM
# import original true data
orig_file = ''.join([
'/mount/riachuelo2/rs123/BOSS/QPM/cmass/mocks/dr12d/ngc/data/',
'a0.6452_', str("%04d" % catalog['n_mock']), '.dr12d_cmass_ngc.rdz'])
orig_data = np.loadtxt(orig_file)
orig_info_file = orig_file+'.info'
orig_info = np.loadtxt(orig_info_file) # gal_id, comp, z_real, z_red, mass_halo, flag_sta, id_halo
# consistency issue with #46
if catalog['n_mock'] in (46, 52, 53, 54, 56, 61, 707, 756, 794, 819, 831, 835, 838):
orig_veto_file = ''.join(['/mount/riachuelo1/hahn/data/QPM/dr12d/',
'a0.6452_', str("%04d" % catalog['n_mock']), '.dr12d_cmass_ngc.veto'])
else:
orig_veto_file = ''.join(['/mount/riachuelo2/rs123/BOSS/QPM/cmass/mocks/dr12d/ngc/data/',
'a0.6452_', str("%04d" % catalog['n_mock']), '.dr12d_cmass_ngc.veto'])
orig_veto = np.loadtxt(orig_veto_file)
n_gal = len(orig_veto)
# assign RA, Dec, z, and w_veto
true_ra = orig_data[:,0]
true_dec = orig_data[:,1]
true_z = orig_data[:,2]
true_wfkp = orig_data[:,3]
true_wfc = np.repeat(1.0, n_gal) # fiber collisions weights are all 1 for true
# check to make sure that the redshifts correspond btw rdz file and rdz.info file
if np.max(np.abs(orig_info[:,3]/true_z-1.0)) > 10**-5:
raise ValueError('redshifts between the data file and info file dont match')
true_comp = orig_info[:,1] # completness weights
# remove veto mask
# Only keep galaxies with veto = 0 (for veto values in .veto file)
vetomask = np.where(orig_veto == 0)
data_list = [true_ra[vetomask], true_dec[vetomask], true_z[vetomask], true_wfc[vetomask], true_comp[vetomask]]
elif catalog['name'].lower() == 'lasdamasgeo':
orig_true_file = ''.join(['/mount/chichipio2/rs123/MOCKS/LRGFull_zm_geo/gaussian/zspace/',
'sdssmock_gamma_lrgFull_zm_oriana', str("%02d" % catalog['n_mock']), catalog['letter'], '_no.rdcz.dat'])
orig_true_data = np.loadtxt(orig_true_file, unpack=True, usecols=[0,1,2]) # ra, dec, ***CZ***
true_ra = orig_true_data[0]
true_dec = orig_true_data[1]
true_z = orig_true_data[2]/299800.0 # convert cz to z
true_weight = np.array([1.0 for j in range(len(true_z))]) # no weights for true (all 1)
header_str = "Columns : ra, dec, z, weight"
data_list = [true_ra, true_dec, true_z, true_weight]
data_fmt = ['%10.5f', '%10.5f', '%10.5f', '%10.5f']
elif catalog['name'].lower() == 'patchy': # PATCHY mocks ------------------------
# read original mock data
orig_file = ''.join(['/mount/riachuelo1/hahn/data/PATCHY/dr12/v6c/',
'Patchy-Mocks-DR12CMASS-N-V6C-Portsmouth-mass_',
str("%04d" % catalog['n_mock']), '.dat'])
# ra, dec, z, nbar, wfc, veto
orig_ra, orig_dec, orig_z, orig_nbar, orig_veto = np.genfromtxt(orig_file,
unpack=True, usecols=[0, 1, 2, 4, 6])
n_gal = len(orig_ra)
new_wfc = np.array([1.0 for i in range(n_gal)]) # w_fc = 1.0 for true
vetomask = (orig_veto == 1) # only keep galaxies with w_veto = 1
header_str = "Columns : ra, dec, z, nz, wfc"
data_list = [orig_ra[vetomask], orig_dec[vetomask], orig_z[vetomask],
orig_nbar[vetomask], new_wfc[vetomask]]
data_fmt=['%10.5f', '%10.5f', '%10.5f', '%.5e', '%10.5f']
elif 'bigmd' in catalog['name'].lower(): # Big MultiDark ------------
P0 = 20000.0
# read rdzw file
data_dir = '/mount/riachuelo1/hahn/data/BigMD/'
if catalog['name'].lower() == 'bigmd':
orig_file = ''.join([data_dir, 'bigMD-cmass-dr12v4-wcp-veto.dat']) # hardcoded
elif catalog['name'].lower() == 'bigmd1':
orig_file = ''.join([data_dir, 'bigMD-cmass-dr12v4-RST-standardHAM-veto.dat'])
elif catalog['name'].lower() == 'bigmd2':
orig_file = ''.join([data_dir, 'bigMD-cmass-dr12v4-RST-quadru-veto.dat'])
elif catalog['name'].lower() == 'bigmd3':
orig_file = ''.join([data_dir, 'BigMD-cmass-dr12v4-RST-standHAM-Vpeak-veto.dat'])
else:
raise NotImplementedError('asdlfkjadf')
orig_ra, orig_dec, orig_z, orig_wfkp, orig_veto, orig_wfc = np.loadtxt(orig_file,
unpack=True, usecols=[0,1,2,3,4,5])
# true wfc = 1 for all galaxies
true_wfc = np.array([ 1.0 for i in range(len(orig_wfc)) ])
nbar = (1.0/P0) * (1.0/orig_wfkp - 1.0)
vetomask = np.where(orig_veto == 1) # if veto = 1 then keep; otherwise discard
# write to file
header_str = "Columns : ra, dec, z, nz, wfc"
data_list = [orig_ra[vetomask], orig_dec[vetomask], orig_z[vetomask], nbar[vetomask], true_wfc[vetomask]]
data_fmt=['%10.5f', '%10.5f', '%10.5f', '%.5e', '%10.5f']
else:
raise NameError('not yet coded')
# data columns, format and header are determined in util.catalog
# and are catalog specific
data_fmt = self.datacols_fmt()
header_str = self.datacols_header()
# write to file
np.savetxt(
self.file(),
(np.vstack(np.array(data_list))).T,
fmt=data_fmt,
delimiter='\t',
header=header_str)
return None
def file(self):
'''
Name of ASCII file of Data/Random catalogy
'''
file_list = self.catclass.file()
# cosmology string
try:
if self.kwargs['cosmology'] == 'survey':
cosmos_str = '.sureycosmo'
else:
cosmos_str = '.fidcosmo'
except KeyError:
cosmos_str = '.fidcosmo'
file_list.insert( -1, cosmos_str )
# correction string
return ''.join(file_list)
def cosmo(self):
try:
if self.kwargs['cosmology'] == 'survey':
# survey cosmology
self.cosmo = self.catclass.cosmo()
return self.cosmo
else:
# default fiducial cosmology (hardcoded)
omega_m = 0.31
except KeyError:
omega_m = 0.31 # default
# survey cosmology
cosmo = {}
cosmo['omega_M_0'] = omega_m
cosmo['omega_lambda_0'] = 1.0 - omega_m
cosmo['h'] = 0.676
cosmo = cosmos.distance.set_omega_k_0(cosmo)
self.cosmos = cosmo
return self.cosmos
def survey_zlimits(self):
''' Catalog survey limits
'''
return (self.catclass).survey_zlimits()
def datacolumns(self):
'''
Data columns for given catalog and correction
'''
return (self.catclass).datacolumns()
def datacols_fmt(self):
'''
Data format of columns of catalog data
'''
return (self.catclass).datacols_fmt()
def datacols_header(self):
'''
Header string that describes data columsn
'''
return (self.catclass).datacols_header()
