def process_fisher(self, filenames, prior, shear=True, sp=True, sgp=True, gp=True, sg=False, sec=None, do2d=False, param="sigma8_input"):
for filename in filenames:
f = fi.fisher(filename)
if not sec:
sec = "nz_shear_errors--bias"
nparam = str(list(np.unique(f.param))).count(sec)
sections=[]
for i in xrange(nparam):
sections.append(sec+"_%d"%(i+1))
f.remove_priors(sections, np.array(nparam*[prior]))
if param not in f.param:
param="omega_m"
x, y = fi.photoz_prior_width_plot(f, bias_name=sec, parameter=param)
err = {param_names[param][0]:y}
if "shear+ggl+pos" in filename:
self.sgp = [x, err]
if "shear+pos" in filename:
self.sp = [x, err]
if "ggl+pos" in filename:
self.gp = [x, err]
if ("shear+ggl" in filename) and ("pos" not in filename):
self.sg = [x, err]
if ("ggl" not in filename) and ("pos" not in filename):
self.shear_shear = [x, err]
if do2d:
err1, err2 = {}, {}
for p1 in f.param:
for p2 in f.param:
if p1==p2:
continue
else:
x, err1[(p1,p2)] = fi.photoz_prior_width_plot(f, bias_name=sec, parameter=[p1,p2])
x, err2[(p2,p1)] = fi.photoz_prior_width_plot(f, bias_name=sec, parameter=[p1,p2])
if "shear+ggl+pos" in filename:
self.sgp_2d = [x, err1]
self.sgp_2d = [x, err2]
if "shear+pos" in filename:
self.sp_2d = [x, err1]
self.sp_2d = [x, err2]
if "ggl+pos" in filename:
self.gp_2d = [x, err1]
self.gp_2d = [x, err2]
if ("shear+ggl" in filename) and ("pos" not in filename):
self.sg_2d = [x, err1]
self.sg_2d = [x, err2]
if ("ggl" not in filename) and ("pos" not in filename):
self.shear_shear_2d = [x, err1]
self.shear_shear_2d = [x, err2]
from tools import fisher as f
shear=f.fisher("shear-only-fisher-syst+cos.txt")
sg=f.fisher("shear+ggl-fisher-1dshift-syst+cos.txt")
sp=f.fisher("shear+pos-fisher-1dshift-cut-sys+cos.txt")
sgp=f.fisher("shear+ggl+pos-fisher-1dshift-syst+cos.txt")
shear.reset_priors("delta-priors-shear.ini")
sg.reset_priors("delta-priors-ggl.ini")
sgp.reset_priors("delta-priors-ggl.ini")
sp.reset_priors("delta-priors-ggl.ini")
x2,y = f.photoz_prior_width_plot(shear, lens=False)
x2,ysg = f.photoz_prior_width_plot(sg, lens=False)
x2,ysp = f.photoz_prior_width_plot(sp, lens=False)
x2,ysgp = f.photoz_prior_width_plot(sgp, lens=False, show=True)
x,y = f.photoz_prior_width_plot(shear, lens=True)
x,ysg = f.photoz_prior_width_plot(sg, lens=True)
x,ysp = f.photoz_prior_width_plot(sp, lens=True)
x,ysgp = f.photoz_prior_width_plot(sgp, lens=True)
plt.plot(x,y/0.82, 'm-', label='WL')
plt.plot(x,ysg/0.82, 'g-', label='WL+ggl')
plt.plot(x,ysp/0.82, 'r-', label='WL+LSS')
plt.plot(x,ysgp/0.82, 'b-', label='WL+ggl+LSS')
plt.xlim(0.,0.06)
plt.legend(loc='upper left')
plt.xlabel("prior width $\Delta \delta z$")
plt.ylabel("fractional error $\Delta \sigma_8 / \sigma_8$")
plt.show()
def prior_plot(self,
parameter='sigma8_input',
lens=True,
dimension=1,
bias='bias',
bias_2='none',
photoz_only=False,
plots=(1, 1)):
labels = {'bias': '\delta z', 's_z': 'S_z', 't_z': 'T_z'}
colours = {
'WL': 'm-',
'WL+ggl': 'g-',
'WL+LSS': 'r-',
'WL+ggl+LSS': 'b-'
}
import pylab as plt
import tools.fisher as f
y = []
if self.sh:
shear = f.fisher(self.config['shear']['file'])
pr = get_option(self.config['shear'], 'priors', default=None)
if pr:
shear.reset_priors(pr)
if photoz_only:
shear.reset_priors(case='delta')
print "shear-shear"
x, ys = f.photoz_prior_width_plot(shear,
lens=lens,
bias_name=bias,
parameter=parameter,
dimension=dimension,
bias_name2=bias_2)
y += [ys]
if self.sh_ggl:
sg = f.fisher(self.config['shear_ggl']['file'])
pr = get_option(self.config['shear_ggl'], 'priors', default=None)
if pr:
sg.reset_priors(pr)
if photoz_only:
sg.reset_priors(case='delta')
print "shear+ggl"
x, ysg = f.photoz_prior_width_plot(sg,
lens=lens,
bias_name=bias,
parameter=parameter,
dimension=dimension,
bias_name2=bias_2)
y += [ysg]
if self.sh_pos:
sp = f.fisher(self.config['shear_pos']['file'])
pr = get_option(self.config['shear_pos'], 'priors', default=None)
if pr:
sp.reset_priors(pr)
if photoz_only:
sp.reset_priors(case='delta')
print "shear+pos"
x, ysp = f.photoz_prior_width_plot(sp,
lens=lens,
bias_name=bias,
parameter=parameter,
dimension=dimension,
bias_name2=bias_2)
y += [ysp]
if self.sh_ggl_pos:
sgp = f.fisher(self.config['shear_ggl_pos']['file'])
pr = get_option(self.config['shear_ggl_pos'],
'priors',
default=None)
if pr:
sgp.reset_priors(pr)
if photoz_only:
sgp.reset_priors(case='delta')
print "shear+ggl+pos"
x, ysgp = f.photoz_prior_width_plot(sgp,
lens=lens,
bias_name=bias,
parameter=parameter)
y += [ysgp]
#import pdb ; pdb.set_trace()
if parameter == 'sigma8_input':
f = 0.82
else:
f = 1.
if dimension == 2:
return x, ys, ysg, ysp, ysgp
# Statistical error relative to true value
if plots[0]:
for i, pl in enumerate(self.plots):
plt.plot(x, y[i] / f, '%s' % colours[pl], label=pl)
plt.legend(loc='upper left')
plt.xlabel("prior width $\Delta %s$" % labels[bias])
if parameter == 'sigma8_input':
plt.ylabel("fractional error $\Delta \sigma_8 / \sigma_8$")
else:
plt.ylabel("statistical error $\Delta %s$" % parameter)
plt.show()
plt.close()
# degradation in errorbar relative to 0 prior width
if plots[1]:
for i, pl in enumerate(self.plots):
plt.plot(x, y[i] / y[i][0], '%s' % colours[pl], label=pl)
plt.legend(loc='upper left')
plt.xlabel("prior width $\Delta %s$" % labels[bias])
if parameter == 'sigma8_input':
plt.ylabel(
"degradation in statistical error $\Delta \sigma_8 / \Delta \sigma_{8,0}$"
)
else:
plt.ylabel("statistical error $\Delta %s / \Delta %s _0$" %
(parameter, parameter))
plt.show()
plt.close()
return 0
def prior_plot(self, parameter='sigma8_input', lens=True, dimension=1, bias='bias', bias_2= 'none',photoz_only=False, plots=(1,1)):
labels={'bias': '\delta z', 's_z': 'S_z', 't_z': 'T_z'}
colours={'WL':'m-', 'WL+ggl':'g-', 'WL+LSS':'r-', 'WL+ggl+LSS':'b-'}
import pylab as plt
import tools.fisher as f
y=[]
if self.sh:
shear=f.fisher(self.config['shear']['file'])
pr = get_option(self.config['shear'], 'priors', default=None)
if pr:
shear.reset_priors(pr)
if photoz_only:
shear.reset_priors(case='delta')
print "shear-shear"
x,ys = f.photoz_prior_width_plot(shear, lens=lens, bias_name=bias, parameter=parameter, dimension = dimension, bias_name2 = bias_2)
y+=[ys]
if self.sh_ggl:
sg=f.fisher(self.config['shear_ggl']['file'])
pr = get_option(self.config['shear_ggl'], 'priors', default=None)
if pr:
sg.reset_priors(pr)
if photoz_only:
sg.reset_priors(case='delta')
print "shear+ggl"
x,ysg = f.photoz_prior_width_plot(sg, lens=lens, bias_name=bias, parameter=parameter, dimension = dimension, bias_name2 = bias_2)
y+=[ysg]
if self.sh_pos:
sp=f.fisher(self.config['shear_pos']['file'])
pr = get_option(self.config['shear_pos'], 'priors', default=None)
if pr:
sp.reset_priors(pr)
if photoz_only:
sp.reset_priors(case='delta')
print "shear+pos"
x,ysp = f.photoz_prior_width_plot(sp, lens=lens, bias_name=bias, parameter=parameter, dimension = dimension, bias_name2 = bias_2)
y+=[ysp]
if self.sh_ggl_pos:
sgp=f.fisher(self.config['shear_ggl_pos']['file'])
pr = get_option(self.config['shear_ggl_pos'], 'priors', default=None)
if pr:
sgp.reset_priors(pr)
if photoz_only:
sgp.reset_priors(case='delta')
print "shear+ggl+pos"
x,ysgp = f.photoz_prior_width_plot(sgp, lens=lens, bias_name=bias, parameter=parameter)
y+=[ysgp]
#import pdb ; pdb.set_trace()
if parameter=='sigma8_input':
f=0.82
else:
f=1.
if dimension==2:
return x, ys, ysg, ysp, ysgp
# Statistical error relative to true value
if plots[0]:
for i, pl in enumerate(self.plots):
plt.plot(x,y[i]/f, '%s'%colours[pl], label=pl )
plt.legend(loc='upper left')
plt.xlabel("prior width $\Delta %s$"%labels[bias])
if parameter=='sigma8_input':
plt.ylabel("fractional error $\Delta \sigma_8 / \sigma_8$")
else:
plt.ylabel("statistical error $\Delta %s$"%parameter)
plt.show()
plt.close()
# degradation in errorbar relative to 0 prior width
if plots[1]:
for i, pl in enumerate(self.plots):
plt.plot(x,y[i]/y[i][0], '%s'%colours[pl], label=pl)
plt.legend(loc='upper left')
plt.xlabel("prior width $\Delta %s$"%labels[bias])
if parameter=='sigma8_input':
plt.ylabel("degradation in statistical error $\Delta \sigma_8 / \Delta \sigma_{8,0}$")
else:
plt.ylabel("statistical error $\Delta %s / \Delta %s _0$"%(parameter,parameter))
plt.show()
plt.close()
return 0
from tools import fisher as f
shear = f.fisher("shear-only-fisher-syst+cos.txt")
sg = f.fisher("shear+ggl-fisher-1dshift-syst+cos.txt")
sp = f.fisher("shear+pos-fisher-1dshift-cut-sys+cos.txt")
sgp = f.fisher("shear+ggl+pos-fisher-1dshift-syst+cos.txt")
shear.reset_priors("delta-priors-shear.ini")
sg.reset_priors("delta-priors-ggl.ini")
sgp.reset_priors("delta-priors-ggl.ini")
sp.reset_priors("delta-priors-ggl.ini")
x2, y = f.photoz_prior_width_plot(shear, lens=False)
x2, ysg = f.photoz_prior_width_plot(sg, lens=False)
x2, ysp = f.photoz_prior_width_plot(sp, lens=False)
x2, ysgp = f.photoz_prior_width_plot(sgp, lens=False, show=True)
x, y = f.photoz_prior_width_plot(shear, lens=True)
x, ysg = f.photoz_prior_width_plot(sg, lens=True)
x, ysp = f.photoz_prior_width_plot(sp, lens=True)
x, ysgp = f.photoz_prior_width_plot(sgp, lens=True)
plt.plot(x, y / 0.82, 'm-', label='WL')
plt.plot(x, ysg / 0.82, 'g-', label='WL+ggl')
plt.plot(x, ysp / 0.82, 'r-', label='WL+LSS')
plt.plot(x, ysgp / 0.82, 'b-', label='WL+ggl+LSS')
plt.xlim(0., 0.06)
plt.legend(loc='upper left')
plt.xlabel("prior width $\Delta \delta z$")
plt.ylabel("fractional error $\Delta \sigma_8 / \sigma_8$")
plt.show()
