Fix residual plots to handle more than 3 IFOs

BayesWaveUtils/scripts/megaplot.py

@@ -102,6 +102,7 @@ gcolor = 'darkgoldenrod'
 scolor = 'darkorchid'
 
 ifoColors = ['darkgoldenrod','darkkhaki','darkseagreen','olive','cadetblue','green','slategray','darkcyan']
+signal_ifoColorList = ['darkorchid','indigo','orchid','slateblue','mediumvioletred','palevioletred']
 
 injcolor = 'teal'
 
@@ -852,7 +853,7 @@ def plot_likelihood_2(modelList, plotsDir, fullOnly_flag=0):
 
 
 def plot_model_dims(modelList, ifoList, ifoNames, plotsDir, fullOnly_flag=0):
-    lineStyles = ['-', '--', ':']
+    lineStyles = ['-', '--', ':','-','--',':']
     lineColors = ifoColors
     glitchChains = []
     signalChains = []
@@ -1040,7 +1041,8 @@ def whitened_residual_plots(model,ifoList,ifoNames,fullOnly_flag=0):
     elif model == 'noise':
         colour = ncolor
     
-    hashlist = ['solid','dashed','dashdot']
+    lineColors = ifoColors
+    hashlist = ['solid','dashed','dashdot','solid','dashed','dashdot']
 
     plt.clf()
 
@@ -1081,7 +1083,7 @@ def whitened_residual_plots(model,ifoList,ifoNames,fullOnly_flag=0):
     #### --- Histograms
     plt.plot(x,scs.norm.pdf(x, mu, sigma),color='k',lw=1.4,label='$\mathcal{N}[0,1]$')
     for ifo in ifoList:
-        plt.hist(whitened[ifo][imin::],bins=50,normed=True,color=colour,label=ifoNames[int(ifo)],histtype='step',ls=hashlist[int(ifo)])
+        plt.hist(whitened[ifo][imin::],bins=50,normed=True,color=lineColors[int(ifo)],label=ifoNames[int(ifo)],histtype='step')
 
     plt.title(model)
     plt.yscale('log')
@@ -1098,7 +1100,7 @@ def whitened_residual_plots(model,ifoList,ifoNames,fullOnly_flag=0):
     plt.plot(x,cdf,color='k',lw=1.4,label='$\mathcal{N}[0,1]$')
     for ifo in ifoList:
         
-        plt.hist(whitened[ifo][imin::],bins=50,normed=True,color=colour,label=ifoNames[int(ifo)],histtype='step',ls=hashlist[int(ifo)],cumulative=-1)
+        plt.hist(whitened[ifo][imin::],bins=50,normed=True,color=lineColors[int(ifo)],label=ifoNames[int(ifo)],histtype='step',cumulative=-1)
 
     plt.title(model)
     plt.yscale('log')