def main():
##
# Read arguments
opts = pycymatch_opts.get_opts().parse_args()
##
# Check input files
for file in opts.input_files:
errors.file_name_error(file)
pycymatch_extra.h_line()
##
# Read mock halo catalogue
mock = pycymatch_io.read_mock(opts)
##
# Read observed catalogue
obs = pycymatch_io.read_obs(opts)
pycymatch_extra.h_line()
##
# Find Matches
matches = pycymatch_match2.find_matches(mock, obs, 2.0 * opts.delta_z,
opts)
pycymatch_io.print_matches(mock[matches[2]], obs, matches[0], matches[1],
opts)
##
# Define completeness and purity of sample
c_matrix = pycymatch_cp.get_completeness(mock, matches, opts)
p_matrix = pycymatch_cp.get_purity(obs, matches, opts)
##
# Define mass-observable matrix for matched objects
matrix, hm_matrix, ranges = pycymatch_match2.mo_matrix(mock, obs, matches,
opts)
pycymatch_extra.h_line()
##
# Make plots
pycymatch_plot.make_plots(matrix, hm_matrix, ranges, opts)
pycymatch_plot.plot_complete(c_matrix[0], 'mass', opts)
pycymatch_plot.plot_complete(c_matrix[1], 'ngal', opts)
pycymatch_plot.plot_pure(p_matrix, opts)
##
# Save matrix to file
pycymatch_io.print_matrix(matrix, hm_matrix, ranges, opts)
pycymatch_extra.h_line()
def main():
##
# Read arguments
opts = get_opts().parse_args()
##
# Check input files
for file in opts.input_files:
errors.file_name_error(file)
h_line()
##
# Read mock halo catalogue
mock = read_mock(opts)
##
# Read observed catalogue
obs = read_obs(opts)
h_line()
##
# Find Matches
matches = find_matches(mock, obs, 2.0 * opts.delta_z, opts)
print_matches(mock[matches[2]], obs, matches[0], matches[1], opts)
##
# Define completeness and purity of sample
c_matrix = get_completeness(mock, matches, opts)
p_matrix = get_purity(obs, matches, opts)
##
# Define mass-observable matrix for matched objects
matrix, hm_matrix, ranges = mo_matrix(mock, obs, matches, opts)
h_line()
##
# Make plots
make_plots(matrix, hm_matrix, ranges, opts)
plot_complete(c_matrix[0], 'mass', opts)
plot_complete(c_matrix[1], 'ngal', opts)
plot_pure(p_matrix, opts)
##
# Save matrix to file
print_matrix(matrix, hm_matrix, ranges, opts)
h_line()
callback = opt_callback, default = range(0, 6),
help = c_col_help)
(opts, args) = parser.parse_args()
if not opts.cluster_file:
parser.error('Cluster file name not provided.')
if not opts.mock_file:
parser.error('Mock file name not provided.')
#############
# READ DATA #
#############
#make sure files exit
errors.file_name_error(opts.mock_file)
errors.file_name_error(opts.cluster_file)
print '================================================================='
#read mock catalogue
print 'Reading file:', opts.mock_file,
mock = np.genfromtxt(opts.mock_file, dtype="S", unpack = True)[opts.m_cols]
dtypes = [('id', 'S22'), ('cen', 'i4'), ('ra', 'f8'), ('dec', 'f8'),
('z', 'f8'), ('rich', 'f8'), ('mass', 'f8'), ('r200', 'f8'),
('minra', 'f8'), ('maxra', 'f8'), ('mindec', 'f8'), ('maxdec', 'f8')]
mock = np.core.records.fromarrays(mock, dtype = dtypes)
mock.rich = np.log10(mock.rich)
print '\tComplete:', len(mock)
#read cluster catalogue
parser = optparse.OptionParser()
options.single_input(parser)
options.single_output(parser)
options.catcut(parser)
(opts, args) = parser.parse_args()
if not opts.input_file:
parser.error('Input filename not provided.')
if (not opts.ra_bin) or (not opts.dec_bin):
parser.error('Number of RA or Dec bins not provided.')
if (opts.ra_bin == 1) and (opts.dec_bin == 1):
parser.error('Number of RA or Dec bins must be greater than one.')
#Check for errors
errors.file_name_error(opts.input_file)
#Read catalogue
print 'Reading data from ' + opts.input_file
if opts.input_type == 'fits':
catalogue = fileio.read_fits(opts.input_file)
else:
catalogue = fileio.read_ascii(opts.input_file)
id = np.array(catalogue[opts.id_col - 1, :])
ra = np.array(catalogue[opts.ra_col - 1, :], dtype="float")
dec = np.array(catalogue[opts.dec_col - 1, :], dtype="float")
z = np.array(catalogue[opts.z_col - 1, :], dtype="float")
if opts.mode == 'phot':
dz = np.array(catalogue[opts.dz_col - 1, :], dtype="float")
if not opts.input_file:
parser.error('Input file name not provided.')
if not opts.output_file:
opts.output_file = opts.input_file + '_clusters.dat'
if not opts.link_r:
parser.error('Transverse linking length not provided.')
if not opts.link_z:
parser.error('Line-of-sight linking length not provided.')
#############
# READ DATA #
#############
#make sure files exit
errors.file_name_error(opts.input_file)
#read input file
print 'Reading file:', opts.input_file
data = np.genfromtxt(opts.input_file, unpack = True, dtype="S")
################
# SET DEFAULTS #
################
all_gal_z = np.array(data[opts.z_col - 1]).astype('float')
#set redshift limits
if not opts.z_min or not opts.z_max:
if not opts.z_min: opts.z_min = np.min(all_gal_z)
if not opts.z_max: opts.z_max = np.max(all_gal_z)
from functions import errors
from pymemmatch_lib.pymemmatch_opts import get_opts
from pycymatch_lib.pycymatch_extra import h_line
from pymemmatch_lib.pymemmatch_match import mo_matrix
from pymemmatch_lib.pymemmatch_io import *
from pycymatch_lib.pycymatch_plot import *
# READ ARGUMENTS
opts = get_opts().parse_args()
# READ DATA
# - check files
for file in opts.input_files:
errors.file_name_error(file)
h_line()
# - read mock catalogue
mock = read_mock(opts)
# - read observed catalogue
obs = read_obs(opts)
h_line()
# FIND MATCHES
matrix, x_range, z_range = mo_matrix(mock, obs, opts)
default=range(0, 6),
help=c_col_help)
(opts, args) = parser.parse_args()
if not opts.cluster_file:
parser.error('Cluster file name not provided.')
if not opts.mock_file:
parser.error('Mock file name not provided.')
#############
# READ DATA #
#############
#make sure files exit
errors.file_name_error(opts.mock_file)
errors.file_name_error(opts.cluster_file)
print '================================================================='
#read mock catalogue
print 'Reading file:', opts.mock_file,
mock = np.genfromtxt(opts.mock_file, dtype="S", unpack=True)[opts.m_cols]
dtypes = [('id', 'S22'), ('cen', 'i4'), ('ra', 'f8'), ('dec', 'f8'),
('z', 'f8'), ('rich', 'f8'), ('mass', 'f8'), ('r200', 'f8'),
('minra', 'f8'), ('maxra', 'f8'), ('mindec', 'f8'), ('maxdec', 'f8')]
mock = np.core.records.fromarrays(mock, dtype=dtypes)
mock.rich = np.log10(mock.rich)
print '\tComplete'
#read cluster catalogue
from functions import errors
from pymemmatch_lib.pymemmatch_opts import get_opts
from pycymatch_lib.pycymatch_extra import h_line
from pymemmatch_lib.pymemmatch_match import mo_matrix
from pymemmatch_lib.pymemmatch_io import *
from pycymatch_lib.pycymatch_plot import *
# READ ARGUMENTS
opts = get_opts().parse_args()
# READ DATA
# - check files
for file in opts.input_files:
errors.file_name_error(file)
h_line()
# - read mock catalogue
mock = read_mock(opts)
# - read observed catalogue
obs = read_obs(opts)
h_line()
# FIND MATCHES
matrix, x_range, z_range = mo_matrix(mock, obs, opts)
