Example #1
0
				

		#import triangle
		import corner as triangle
		Fsrc_fig = triangle.corner(Fsrc_flatchain, labels=Fsrc_param_names)			
		Fsrc_fig.savefig('../emcee_data/Fsrc_PG1302_Corner_Plot_%iwalkers.png' %clen)




		## Do some stats on the walkers
		from scipy.stats import scoreatpercentile as scoretpercentile

		## max posterior + percentiles
		Fsrc_MAP_vals = Fsrc_flatchain[Fsrc_flatlnprobs.argmax()]
		Fsrc_perc = scoretpercentile(Fsrc_flatchain, [15,85], axis=0)


		filename = "Fsrc_results_"+Shell_File+"%iwalkers.txt" %clen
		print "Printing Results"
		target = open(filename, 'w')
		target.truncate()


		for i,name in enumerate(Fsrc_param_names):
			Fsrc_diff_minus = Fsrc_MAP_vals[i] - Fsrc_perc[0,i]
			Fsrc_diff_plus = Fsrc_perc[1,i] - Fsrc_MAP_vals[i]
			target.write("Fsrc: {name}: {0:.4f} + {1:.4f} - {2:.4f}".format(Fsrc_MAP_vals[i], Fsrc_diff_plus, Fsrc_diff_minus, name=name))
			target.write("\n")

		
Example #2
0
    ###CORNER PLOT
    flatchain = np.vstack(chain[:, clen / 2:])
    flatlnprobs = np.vstack(lnprobs[:, clen / 2:])

    #import triangle
    import corner as triangle
    fig = triangle.corner(flatchain, labels=param_names)
    fig.savefig("../emcee_data/" + Shell_File +
                "_PG1302_Corner_Plot_%iwalkers.png" % clen)

    ## Do some stats on the walkers
    from scipy.stats import scoreatpercentile as scoretpercentile

    ## max posterior + percentiles
    MAP_vals = flatchain[flatlnprobs.argmax()]
    perc = scoretpercentile(flatchain, [15, 85], axis=0)

    filename = "MCMCResults_" + Shell_File + "%iwalkers.txt" % clen
    print "Printing Results"
    target = open(filename, 'w')
    target.truncate()

    for i, name in enumerate(param_names):
        diff_minus = MAP_vals[i] - perc[0, i]
        diff_plus = perc[1, i] - MAP_vals[i]
        target.write("W1: {name}: {0:.4f} + {1:.4f} - {2:.4f}".format(
            MAP_vals[i], diff_plus, diff_minus, name=name))
        target.write("\n")

    mxprbs = zeros(nwalkers)
Example #3
0
W1_sin_fig.savefig('../emcee_data/W1_'+Shell_File+'_PG1302_Corner_Plot_%iwalkers.png' %clen)


W2_sin_fig = triangle.corner(W2_sin_flatchain, labels=param_names, quantiles=[0.15, 0.5, 0.85],show_titles=True, title_kwargs={"fontsize": 14},label_kwargs={"fontsize": 18})			
W2_sin_fig.savefig('../emcee_data/W2_'+Shell_File+'_PG1302Corner_Plot_%iwalkers.png' %clen)



## Do some stats on the walkers
from scipy.stats import scoreatpercentile as scoretpercentile



## max posterior + percentiles
src_sin_MAP_vals = src_sin_flatchain[src_sin_flatlnprobs.argmax()]
src_sin_perc = scoretpercentile(src_sin_flatchain, [15,85], axis=0)

W1_sin_MAP_vals = W1_sin_flatchain[W1_sin_flatlnprobs.argmax()]
W1_sin_perc = scoretpercentile(W1_sin_flatchain, [15,85], axis=0)

W2_sin_MAP_vals = W2_sin_flatchain[W2_sin_flatlnprobs.argmax()]
W2_sin_perc = scoretpercentile(W2_sin_flatchain, [15,85], axis=0)



filename = "../emcee_Results/Sin_results_"+Shell_File+"%iwalkers.txt" %clen
print "Printing Results"
target = open(filename, 'w')
target.truncate()

Example #4
0
###CORNER PLOT	
BB_flatchain = np.vstack(BB_chain[:,clen/4:])
BB_flatlnprobs = np.vstack(BB_lnprobs[:,clen/4:])

#import triangle
import corner as triangle
BB_fig = triangle.corner(BB_flatchain, labels=param_names, quantiles=[0.15, 0.5, 0.85],show_titles=True, title_kwargs={"fontsize": 14},label_kwargs={"fontsize": 20})	
BB_fig.savefig('../emcee_data/BBCorfit_PG1302_Corner_Plot_%iwalkers'%clen+Shell_File+'.png')


## Do some stats on the walkers
from scipy.stats import scoreatpercentile as scoretpercentile
## max posterior + percentiles
BB_MAP_vals = BB_flatchain[BB_flatlnprobs.argmax()]
BB_perc = scoretpercentile(BB_flatchain, [15,85], axis=0)


filename = "BBfit_resuts_%iwalkers"%clen+Shell_File+".txt" 
print "Printing Results"
target = open(filename, 'w')
target.truncate()


for i,name in enumerate(param_names):
	BB_diff_minus = BB_MAP_vals[i] - BB_perc[0,i]
	BB_diff_plus = BB_perc[1,i] - BB_MAP_vals[i]
	target.write("BBfit: {name}: {0:.4f} + {1:.4f} - {2:.4f}".format(BB_MAP_vals[i], BB_diff_plus, BB_diff_minus, name=name))
	target.write("\n")

Example #5
0
                              label_kwargs={"fontsize": 18})
    if (TrimE):
        plt.savefig("plots/yeti/Obscured/subl_NoRegro_TrimE/Strt%i_End%i" %
                    (Strt_Rstrt, End_Rstrt) + Shell_File +
                    '_TDE_Corner_Plot_%iwalkers.png' % clen)
    else:
        plt.savefig("plots/yeti/Obscured/subl_NoRegro/Strt%i_End%i_" %
                    (Strt_Rstrt, End_Rstrt) + Shell_File +
                    '_TDE_Corner_Plot_%iwalkers.png' % clen)

## Do some stats on the walkers
from scipy.stats import scoreatpercentile as scoretpercentile

## max posterior + percentiles
All_MAP_vals = All_flatchain[All_flatlnprobs.argmax()]
All_perc = scoretpercentile(All_flatchain, [50 - perc_rng, 50 + perc_rng],
                            axis=0)

print "PRINTING RESULTS TO FILE"
filename = "emcee_Results/TDE_results" + Shell_File + "%iwalkers.txt" % clen
print "Printing Results"
target = open(filename, 'w')
target.truncate()

All_diff_minus = np.zeros(len(param_names))
All_diff_plus = np.zeros(len(param_names))
for i, name in enumerate(param_names):
    All_diff_minus[i] = All_MAP_vals[i] - All_perc[0, i]
    All_diff_plus[i] = All_perc[1, i] - All_MAP_vals[i]
    target.write("TDE_All: {name}: {0:.4f} + {1:.4f} - {2:.4f}".format(
        All_MAP_vals[i], All_diff_plus[i], All_diff_minus[i], name=name))
    target.write("\n")