try:
upper_y = 1.1 * np.amax(
cosmic_variance[np.abs(cosmic_variance) > cutoff])
except:
upper_y = cutoff
plotrange_y.append([lower_y, upper_y])
# now set the appearence of the plot:
plotrange_x = np.array(plotrange_x)
plotrange_y = np.array(plotrange_y)
# log scale:
if not do_lin:
ax.set_xscale('log')
ax.set_yscale('log')
# ranges:
x_min = fu.v_nice_number(np.amin(plotrange_x[:, 0]), 1)
x_max = fu.v_nice_number(np.amax(plotrange_x[:, 1]), 1)
if (x_min != x_max):
ax.set_xlim([x_min, x_max])
y_min = fu.v_nice_number(np.amin(plotrange_y[:, 0]), 2)
y_max = fu.v_nice_number(np.amax(plotrange_y[:, 1]), 0)
if (y_min != y_max):
ax.set_ylim([y_min, y_max])
# labels
if (ind != num):
ax.set_xticklabels([])
if (ind == num):
ax.set_xlabel('$\ell$')
if (ind2 == 1):
ax.set_ylabel(
'$ \Delta C_{\ell} \,\, / \,\, C_{\ell} \,\, \%$')
elif params is not None:
fishers_temp = fishers_temp.marginalise(params=params)
for num, fish in enumerate(fishers_temp.get_fisher_list()):
#output fisher matrices again
fish.save_to_file(outroot + '__Fisher_Out_' + str(num) + "-" +
fish.name,
simple_header=True)
print(fish.name)
fishpars = fish.get_param_names()
print("parameter names")
print(str(fishpars))
# get the bounds:
Bounds_68 = list(
fu.v_nice_number(fish.get_confidence_bounds(0.680),
mode=1))
Bounds_95 = list(
fu.v_nice_number(fish.get_confidence_bounds(0.950),
mode=1))
Bounds_99 = list(
fu.v_nice_number(fish.get_confidence_bounds(0.997),
mode=1))
# get the fiducial:
fiducial = []
for num, par in enumerate(fish.get_param_fiducial()):
fiducial.append(
fu.significant_digits((par, Bounds_68[num]), mode=1))
# get the names:
if use_latex:
parameter_names_latex = copy.deepcopy(
fish.get_param_names_latex())
# do some first printing for Latex:
if use_latex:
out_file.write( '\\begin{tabular}{ |'+''.join(['l|' for i in range(latex_num_col) ])+' }\n' )
for key, params in numbounds:
params = Config.get("bounds", key).split(",")
fishers_temp = fishers
if eliminate is not False:
fishers_temp = fishers_temp.reshuffle( params=params )
elif params is not None:
fishers_temp = fishers_temp.marginalise( params=params )
for num, fish in enumerate(fishers_temp.get_fisher_list()):
# get the bounds:
Bounds_68 = list( fu.v_nice_number( fish.get_confidence_bounds( 0.680 ), mode=1 ) )
Bounds_95 = list( fu.v_nice_number( fish.get_confidence_bounds( 0.950 ), mode=1 ) )
Bounds_99 = list( fu.v_nice_number( fish.get_confidence_bounds( 0.997 ), mode=1 ) )
# get the fiducial:
fiducial = []
for num, par in enumerate(fish.get_param_fiducial()):
fiducial.append( fu.significant_digits( (par, Bounds_68[num]), mode=1 ) )
# get the names:
if use_latex:
parameter_names_latex = copy.deepcopy(fish.get_param_names_latex())
else:
parameter_names = copy.deepcopy(fish.get_param_names())
# do the printing:
if use_latex:
print_table = []
for par,fid,bound in zip( parameter_names_latex,fiducial,Bounds_68 ):
# get the plot bounds for cosmic variance:
try: lower_y = 0.9*np.amin(cosmic_variance[np.abs(cosmic_variance)>cutoff])
except: lower_y = cutoff
try: upper_y = 1.1*np.amax(cosmic_variance[np.abs(cosmic_variance)>cutoff])
except: upper_y = cutoff
plotrange_y.append( [ lower_y,upper_y ] )
# now set the appearence of the plot:
plotrange_x = np.array( plotrange_x )
plotrange_y = np.array( plotrange_y )
# log scale:
if not do_lin:
ax.set_xscale('log')
ax.set_yscale('log')
# ranges:
x_min = fu.v_nice_number( np.amin(plotrange_x[:,0]),1)
x_max = fu.v_nice_number( np.amax(plotrange_x[:,1]),1)
if ( x_min != x_max ):
ax.set_xlim( [ x_min,x_max ] )
y_min = fu.v_nice_number( np.amin(plotrange_y[:,0]),2)
y_max = fu.v_nice_number( np.amax(plotrange_y[:,1]),0)
if ( y_min != y_max ):
ax.set_ylim( [ y_min,y_max ] )
# labels
if ( ind != num ):
ax.set_xticklabels( [] )
if ( ind == num ):
ax.set_xlabel('$\ell$')
if ( ind2 == 1):
ax.set_ylabel( '$ \Delta C_{\ell} \,\, / \,\, C_{\ell} \,\, \%$' )
# open the file if wanted:
if outroot is not None:
out_file = open(outroot,"w")
# do some first printing for Latex:
if args.latex:
if outroot is not None:
out_file.write( '\\begin{tabular}{ |'+''.join(['l|' for i in range(latex_num_col) ])+' }\n' )
else:
print '\\begin{tabular}{ |'+''.join(['l|' for i in range(latex_num_col) ])+' }'
# print the confidence bounds on the Fisher matrices:
for num, fish in enumerate(fishers.get_fisher_list()):
# get the bounds:
Bounds_68 = list( fu.v_nice_number( fish.get_confidence_bounds( 0.680 ), mode=1 ) )
Bounds_95 = list( fu.v_nice_number( fish.get_confidence_bounds( 0.950 ), mode=1 ) )
Bounds_99 = list( fu.v_nice_number( fish.get_confidence_bounds( 0.997 ), mode=1 ) )
# get the fiducial:
fiducial = []
for num, par in enumerate(fish.get_param_fiducial()):
fiducial.append( fu.significant_digits( (par, Bounds_68[num]), mode=1 ) )
# get the names:
if args.latex:
parameter_names_latex = fish.get_param_names_latex()
else:
parameter_names = fish.get_param_names()
# do the printing:
if args.latex:
print_table = []
for par,fid,bound in zip( parameter_names_latex,fiducial,Bounds_68 ):