82 lines
2.8 KiB
Python
Executable File
82 lines
2.8 KiB
Python
Executable File
#!/usr/bin/python
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#-*- coding:utf-8 -*-
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import numpy as np
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import matplotlib.pyplot as plt
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def annotation_line(ax, xmin, xmax, y, text, ytext=0, linecolor='black', linewidth=1, fontsize=8):
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ax.annotate('', xy=(xmin, y), xytext=(xmax, y), xycoords='data', textcoords='data',arrowprops={'arrowstyle': '|-|', 'color':linecolor, 'linewidth':linewidth})
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#ax.annotate('', xy=(xmin, y), xytext=(xmax, y), xycoords='data', textcoords='data',arrowprops={'arrowstyle': '<->', 'color':linecolor, 'linewidth':linewidth})
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xcenter = np.log10(xmin)+(np.log10(xmax)-np.log10(xmin))/2
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if ytext==0:
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ytext = y+(ax.get_ylim()[1]-ax.get_ylim()[0])/5
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ax.annotate( text, xy=(pow(10,xcenter),ytext), ha='center', va='center', fontsize=fontsize )
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z = 0.77
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Dl = 3407.27e6*3.0857e16
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SED = np.loadtxt('photandseds.tbl',comments='|')
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INT = np.loadtxt('Flux_modele.res')
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MOD = np.loadtxt('data_ord_p_3.res')
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n_val = len(MOD[0,:])
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n_point = len(SED[:,0])
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n_ratio = int(float(n_point)/2.5)
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X_sed = SED[:,0]
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Y_sed = SED[:,1]*1e-26
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yerr_sed = SED[:,2:3]*1e-26
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X_mod = MOD[1:,0]
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Y_mod = []
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val_test = []
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X_int = INT[1:,0]
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Y_int = []
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for i in range(1,n_val):
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val_test.append(MOD[0,i])
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ratio = Y_sed[n_ratio]/(INT[n_ratio+1,i]*pow(1+z,(val_test[i-1]+1.)/2.)/(4.*np.pi*Dl*Dl))
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Y_mod.append(ratio*MOD[1:,i]*pow(1+z,(val_test[i-1]+1.)/2.)/(4.*np.pi*Dl*Dl))
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Y_int.append(ratio*INT[1:,i]*pow(1+z,(val_test[i-1]+1.)/2.)/(4.*np.pi*Dl*Dl))
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fig,ax = plt.subplots(3,1,sharex=True,gridspec_kw={'height_ratios': [3,1,0.25]},figsize=(18,9))
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plt.subplots_adjust(left=0.10,bottom=0.10,right=0.90,top=0.85,wspace=0.5,hspace=0)
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ax[0].errorbar(X_sed,Y_sed,yerr_sed,fmt="ok")
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for i in range(n_val-1):
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ax[0].plot(X_mod,Y_mod[i],'--',color="C{}".format(i),label="p={}".format(val_test[i]))
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ax[0].plot(X_int,Y_int[i],'+',color="C{}".format(i))
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ax[0].set_yscale('log')
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ax[0].set_xscale('log')
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ax[0].set_xlim(1e7,1e15)
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ax[0].set_ylim(min(Y_sed[Y_sed != 0])*1e-3,max(Y_sed[Y_sed != 0])*1e1)
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ax[0].set_ylabel(r"Flux density ($W \cdot m^{-2} \cdot Hz^{-1}$)")
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ax[0].legend()
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for i in range(n_val-1):
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ax[1].errorbar(X_sed,(Y_sed/Y_int[i]),yerr_sed,fmt='o',color="C{}".format(i),label="p={}".format(val_test[i]))
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ax[1].plot([1e7,1e15],[1,1],'--k')
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ax[1].set_xscale('log')
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ax[1].set_yscale('log')
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ax[1].set_xlim(1e7,1e15)
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ax[1].set_ylabel('Ratio')
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ax[1].set_xlabel('Frequency (Hz)')
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ax[2].set_ylim(-1,2)
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ax[2].tick_params(labelleft=False,left=False)
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annotation_line(ax[2],1e7,3e8,0,"Radio Waves")
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annotation_line(ax[2],3e8,3e11,0,"Microwaves")
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annotation_line(ax[2],3e11,4e14,0,"IR")
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annotation_line(ax[2],4e14,7.5e14,0,"Visible")
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ax[2].set_xlabel('Frequency (Hz)')
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fig.suptitle(r"3C175 spectral energy distribution fit using a toy model and calibrating on photon index $p$."+"\n (SED source : NED/NASA)")
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plt.savefig("SED_fit.png",bbox_inches='tight')
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#plt.show()
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