updating the plotting script wiht new location of results

plotting/agn_corner.py

@@ -8,29 +8,15 @@ matplotlib.rcParams.update({'font.size': 16})
 
 def getAGNPost(nFreqBins):
 
-    if nFreqBins==9: 
-        path0 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq9/posterior.dat'.format(nFreqBins)
-        path1 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq9_1/posterior.dat'.format(nFreqBins)
-        path2 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq9_2/posterior.dat'.format(nFreqBins)
-        post0 = np.genfromtxt(path0,names=True)
-        post1 = np.genfromtxt(path1,names=True)
-        post2 = np.genfromtxt(path2,names=True)
-    elif nFreqBins==5:
-        path0 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq5/posterior.dat'.format(nFreqBins)
-        path1 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq5_1/posterior.dat'.format(nFreqBins)
-        path2 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq5_2/posterior.dat'.format(nFreqBins)
-        post0 = np.genfromtxt(path0,names=True)
-        post1 = np.genfromtxt(path1,names=True)
-        post2 = np.genfromtxt(path2,names=True)
-    elif nFreqBins==3:
-        path0 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq3/posterior.dat'.format(nFreqBins)
-        path1 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq3_1/posterior.dat'.format(nFreqBins)
-        path2 = '/home/ADF/middlehr/Documents/PTA/EPTAInterp/results/agn_model/f{}/nFreq3_2/posterior.dat'.format(nFreqBins)
-        post0 = np.genfromtxt(path0,names=True)
-        post1 = np.genfromtxt(path1,names=True)
-        post2 = np.genfromtxt(path2,names=True)
-
-    #combine the ns 
+    # read in the posterior files for the chosen number of frequency bins 
+    path0 = '../results/agnosticPosterior/nFreq{}/posterior_0.dat'.format(nFreqBins)
+    path1 = '../results/agnosticPosterior/nFreq{}/posterior_1.dat'.format(nFreqBins)
+    path2 = '../results/agnosticPosterior/nFreq{}/posterior_2.dat'.format(nFreqBins)
+    post0 = np.genfromtxt(path0,names=True)
+    post1 = np.genfromtxt(path1,names=True)
+    post2 = np.genfromtxt(path2,names=True)
+
+    # combine the posteriors
     post0And1 = np.concatenate((post0['logn'], post1['logn']))
     logns = np.concatenate((post0And1, post2['logn']))
 
@@ -46,6 +32,7 @@ def getAGNPost(nFreqBins):
     post0And1 = np.concatenate((post0['gamma'], post1['gamma']))
     gammas = np.concatenate((post0And1, post2['gamma']))
 
+    # make a dictionary with the full results 
     posteriorCombined = {'logn': logns, 
                          'alpha': alphas, 
                          'delta': deltas,
@@ -70,26 +57,53 @@ def fiveDCorner(data,nFBins):
                         r'$\beta_z$', r'$z_0$', r'$\alpha_{\mathcal{M}}$',\
                         r'$\log_{10} \frac{\mathcal{M}_*}{ M_{\odot}}$'])
 
+    plt.clf()
     figure = corner.corner(d2,labels=parameterLabels,
                            quantiles=[0.05, 0.5, 0.95])
-    plt.savefig('forPaper/agn_fullCorner_fBins{}.pdf'.format(nFBins))
-    plt.savefig('forPaper/agn_fullCorner_fBins{}.png'.format(nFBins))
+    plt.savefig('agn_fullCorner_fBins{}.pdf'.format(nFBins))
+    plt.savefig('agn_fullCorner_fBins{}.png'.format(nFBins))
+    plt.show()
     return 
 
 
-n=9
-posterior = getAGNPost(n)#np.genfromtxt('posterior.dat', names=True)
-fiveDCorner(posterior,n)
+def oneDimensionalHistograms(data,nFBins):
 
+    # individual one dimensional plots
+    names = ['logn', 'beta', 'gamma', 'alpha', 'delta']
+    parameterLabels = ([r'$\log_{10}\frac{{\dot n}_0}{{\rm Mpc}^{3}{\rm Gyr}}$',\
+                        r'$\beta_z$', r'$z_0$', r'$\alpha_{\mathcal{M}}$',\
+                        r'$\log_{10} \frac{\mathcal{M}_*}{ M_{\odot}}$'])
+
+    for i in range(len(names)):
+
+        oneDData = data[names[i]]
+
+        plt.clf()
+        plt.hist(oneDData,histtype='step')
+        plt.xlabel(parameterLabels[i])
+        plt.ylabel('count')
+        plt.tight_layout()
+        plt.show()
+
+
+def main():
+
+    # choose the number of frequency bins to use
+    n=9
+
+    # full corner plot
+    posterior = getAGNPost(n)
+    fiveDCorner(posterior,n)
+
+    # one dimensional histograms
+    oneDimensionalHistograms(posterior,n)
 
-exit()
-names = ['logn', 'beta', 'gamma', 'alpha', 'delta']
-for i in range(5):
 
-    oneDData = posterior[names[i]]
-    
-    # percentile:
-    
     
-    plt.hist(oneDData)
-    plt.show()
+if __name__=='__main__':
+    main()
+
+
+
+
+