"""
run this code to create the directories
"""
import os
import sys
sys.path.append(os.path.abspath('../'))
from shear_KL_source import params
params.load('base_params.dat')
for param_file in ('base_params.dat',
'params_f0.5.dat',
'params_sig0.1.dat',
'params_sig0.1_f0.5.dat',
'params_sig0.1_f0.35.dat'):
params.load(param_file)
for p in ['scratch_dir', 'shear_in_dir', 'shear_recons_dir', 'Map_dir',
'kappa_dir', 'mask_outdir', 'condorlog']:
F = params[p]
if not os.path.exists(F):
print "mkdir %s" % F
os.system('mkdir %s' % F)
if logplot:
pylab.semilogx(xvals,SN,label='Signal+Noise')
pylab.semilogx(xvals,S,label='Signal')
pylab.semilogx(xvals,N,'--k',label='Noise')
ax.xaxis.set_major_formatter(FuncFormatter(lambda x,*args: '%i'%x))
else:
pylab.plot(xvals,SN,label='Signal+Noise')
pylab.plot(xvals,S,label='Signal')
pylab.plot(xvals,N,'--k',label='Noise')
pylab.legend(loc=4)
pylab.xlim(1,4096)
pylab.grid(True,c='#AAAAAA')
pylab.xlabel('mode number')
pylab.ylabel('cumulative value')
if __name__ == '__main__':
import os
import sys
sys.path.append(os.path.abspath('../'))
from shear_KL_source import params
params.load('../run/base_params.dat')
from shear_KL_source.DES_tile.tools import get_basis_filename
plot_evals( get_basis_filename() )
pylab.savefig('figs/fig03_eigenvalues.eps')
pylab.savefig('figs/fig03_eigenvalues.pdf')
pylab.show()
def plot_reconstruction_2():
nmodes=900
alpha=0.15
RAmin=11.5
DECmin=36
xlim=(15,45)
ylim=(20,50)
RAlim = (RAmin,RAmin+1)
DEClim = (DECmin,DECmin+1)
RAside = (RAlim[1]-RAlim[0])
DECside = (DEClim[1]-DEClim[0])
params.load('../run/base_params.dat')
params.load('../run/params_sig0.1.dat')
gamma_out_masked_1, noise = get_reconstruction(nmodes,
alpha,
True,
RAmin,
DECmin)
gamma_out_unmasked_1, noise = get_reconstruction(nmodes,
alpha,
False,
RAmin,
DECmin)
mask_1 = get_mask(False,RAlim,DEClim)
params.load('../run/params_sig0.1_f0.35.dat')
gamma_out_masked_2, noise = get_reconstruction(nmodes,
alpha,
True,
RAmin,
DECmin)
mask_2 = get_mask(False,RAlim,DEClim)
params.load('../run/params_sig0.1_f0.5.dat')
gamma_out_masked_3, noise = get_reconstruction(nmodes,
alpha,
True,
RAmin,
DECmin)
mask_3 = get_mask(False,RAlim,DEClim)
offset = (RAmin,DECmin)
dtheta = params.dtheta/60.
xlim = (offset[0] + xlim[0]/60.,
offset[0] + xlim[1]/60.)
ylim = (offset[1] + ylim[0]/60.,
offset[1] + ylim[1]/60.)
extent=(offset[0],offset[0]+RAside,
offset[1],offset[1]+DECside)
#--------------------------------------------------
pylab.figure(figsize=(8,8))
ax = pylab.subplot(221)
pylab.imshow(mask_1.T*0,
origin='lower',
extent=extent,
interpolation='nearest',
cmap=pylab.cm.binary)
whiskerplot(gamma_out_unmasked_1,dtheta,dtheta,offset=offset)
pylab.xlim(xlim)
pylab.ylim(ylim)
#pylab.title(r'$\mathdefault{unmasked\ KL}$')
#pylab.xlabel('')
pylab.text(0.97,0.97,'no mask',
transform = ax.transAxes,
va = 'top',
ha = 'right',
bbox=dict(facecolor='w',edgecolor='w') )
ax.xaxis.set_major_locator(MultipleLocator(0.2))
ax.yaxis.set_major_locator(MultipleLocator(0.2))
#--------------------------------------------------
ax = pylab.subplot(222)
pylab.imshow(mask_1.T,
origin='lower',
extent=extent,
interpolation='nearest',
cmap=GreyWhite)
pylab.clim(0,1)
whiskerplot(gamma_out_masked_1,dtheta,dtheta,offset=offset)
pylab.xlim(xlim)
pylab.ylim(ylim)
#pylab.title(r'$\mathdefault{masked\ KL}$')
#pylab.xlabel('')
pylab.ylabel('')
pylab.text(0.97,0.97,'20% mask',
transform = ax.transAxes,
va = 'top',
ha = 'right',
bbox=dict(facecolor='w',edgecolor='w') )
ax.xaxis.set_major_locator(MultipleLocator(0.2))
ax.yaxis.set_major_locator(MultipleLocator(0.2))
#--------------------------------------------------
ax = pylab.subplot(223)
pylab.imshow(mask_2.T,
origin='lower',
extent=extent,
interpolation='nearest',
cmap=GreyWhite)
pylab.clim(0,1)
whiskerplot(gamma_out_masked_2,dtheta,dtheta,offset=offset)
pylab.xlim(xlim)
pylab.ylim(ylim)
#pylab.title(r'$\mathdefault{masked\ KL}$')
pylab.text(0.97,0.97,'35% mask',
transform = ax.transAxes,
va = 'top',
ha = 'right',
bbox=dict(facecolor='w',edgecolor='w') )
ax.xaxis.set_major_locator(MultipleLocator(0.2))
ax.yaxis.set_major_locator(MultipleLocator(0.2))
#--------------------------------------------------
ax = pylab.subplot(224)
pylab.imshow(mask_3.T,
origin='lower',
extent=extent,
interpolation='nearest',
cmap=GreyWhite)
pylab.clim(0,1)
whiskerplot(gamma_out_masked_3,dtheta,dtheta,offset=offset)
pylab.xlim(xlim)
pylab.ylim(ylim)
#pylab.title(r'$\mathdefault{masked\ KL}$')
pylab.ylabel('')
pylab.text(0.97,0.97,'50% mask',
transform = ax.transAxes,
va = 'top',
ha = 'right',
bbox=dict(facecolor='w',edgecolor='w') )
ax.xaxis.set_major_locator(MultipleLocator(0.2))
ax.yaxis.set_major_locator(MultipleLocator(0.2))
#--------------------------------------------------
pylab.figtext(0.5,0.97,r'$\mathdefault{KL\ Reconstructions}$',
ha='center',va='top',
fontsize=16)
pylab.figtext(0.5,0.94,r'$\mathdefault{n=900\ modes,\ \ n_{gal}=100/arcmin^2}$',
ha='center',va='top',
fontsize=14)
"""
run this code to compute the aperture mass map from the input shear
"""
import os
import sys
sys.path.append(os.path.abspath('../'))
from shear_KL_source import params
params.load('base_params.dat')
from shear_KL_source.DES_tile.mass_maps import compute_Map_input
for usemask in ['y','n']:
for normed in [True,False]:
if usemask=='n' and normed: continue
for add_signal in (True, False):
for add_noise in (True, False):
if add_signal == False and add_noise == False:
continue
compute_Map_input(add_signal = add_signal,
add_noise = add_noise,
usemask = usemask,
normed = normed)
"""
run this code to create the cfg file for the condor runs
"""
import os
import sys
sys.path.append(os.path.abspath('../'))
from shear_KL_source import params
params.load('base_params.dat')
from shear_KL_source.DES_tile.setup_utils import create_cfg_file
create_cfg_file( cfg_file = 'DES_tile.cfg',
alphas = (0.15,),
NMODES = (900,),
use_noise = (True,),
use_mask = (True,False),
noise_only = False,
compute_shear_noise = False,
compute_Map = True,
compute_Map_noise = True,
)
create_cfg_file( cfg_file = 'DES_tile_noiseonly.cfg',
alphas = (0.15,),
NMODES = (900,),
use_noise = (True,),
use_mask = (True,False),
noise_only = True,
compute_shear_noise = False,
compute_Map = True,
"""
run this to create the mask tiles for the condor runs
This creates masks with different mask fractions
"""
import os
import sys
sys.path.append(os.path.abspath('../'))
from shear_KL_source import params
from shear_KL_source.DES_tile.setup_utils import create_mask_tiles
import numpy
params.load('base_params.dat')
params.load('params_f0.5.dat')
numpy.random.seed(3)
create_mask_tiles( params.mask_outdir,
fmask = params.fmask )
params.load('params_f0.35.dat')
numpy.random.seed(3)
create_mask_tiles( params.mask_outdir,
fmask = params.fmask )
