unres paper list update

[django_unres.git] / files / matplotlib_hist.py

diff --git a/files/matplotlib_hist.py b/files/matplotlib_hist.py
index 47d7e72..69bf5b0 100755 (executable)
--- a/files/matplotlib_hist.py
+++ b/files/matplotlib_hist.py
@@ -13,16 +13,18 @@ with open('remd_all.stat','r') as f:
   ncolumns=len(line.split())
 
 if ncolumns==14:  
- x,y,s,r,ek,rms= np.loadtxt('remd_all.stat',usecols=(11,3,0,13,2,5),unpack=True)
- x0,s0,r0= np.loadtxt('remd_all0.stat',usecols=(11,0,13),unpack=True) 
+ x,y,s,r,ek,rms= np.loadtxt('remd_all.stat',usecols=(11,3,1,13,2,5),unpack=True)
+ x0,s0,r0,rms0= np.loadtxt('remd_all0.stat',usecols=(11,1,13,5),unpack=True) 
 else:
- x,y,s,r= np.loadtxt('remd_all.stat',usecols=(7,3,0,9),unpack=True)
- x0,s0,r0= np.loadtxt('remd_all0.stat',usecols=(7,0,9),unpack=True) 
+ x,y,s,r= np.loadtxt('remd_all.stat',usecols=(7,3,1,9),unpack=True)
+ x0,s0,r0= np.loadtxt('remd_all0.stat',usecols=(7,1,9),unpack=True) 
 
+s=s*0.0489
+s0=s0*0.0489
 hall,binall=np.histogram(y,bins=40,density=False)
 
 plt.xlim(min(binall), max(binall[hall>4]))
-plt.ylim(0,max(hall)/4)
+#plt.ylim(0,max(hall)/4)
 plt.ylabel('number of samples')
 plt.xlabel('potential energy [kcal/mol]')
 
@@ -34,7 +36,7 @@ Tremd=map(float,sys.argv[1].split())
 colors = cm.rainbow(np.linspace(0, 1, len(Tremd)))
 for T,c in zip(Tremd,colors):
  yt=y[x==T]
- h,bin=np.histogram(yt,bins=40,density=False)
+ h,bin=np.histogram(yt,bins=40,range=(min(binall),max(binall[hall>4])),density=False)
  center = (bin[:-1] + bin[1:]) / 2
  plt.plot(center,h,'-',color=c)
 # plt.bar(bin[:-1], h, width = bin[2]-bin[1],color=c)
@@ -59,10 +61,12 @@ plt.savefig('remd_Tene.png')
 
 plt.clf()
 plt.ylabel('bath temperature [K]')
-plt.xlabel('step*replica')
+plt.xlabel('time*replica')
 
 replica=range(int(sys.argv[2]))
-colors = cm.rainbow(np.linspace(0, 1, len(replica)))
+#colors = cm.rainbow(np.linspace(0, 1, len(replica)))
+cmap = plt.get_cmap('hot')
+colors = cmap(np.linspace(0, 1, len(replica)*1.4))
 for i,c in zip(replica,colors):
  yt=x0[r0==i]
  xt=(s0+r0*max(s0))[r0==i]
@@ -85,6 +89,16 @@ if ncolumns==14:
 
   plt.savefig('remd_ene_rms.png')
 
+  plt.clf()
+  plt.xlabel('time*replica')
+  plt.ylabel('rmsd')
+  for i in replica:
+    yt=rms0[r0==i]
+    xt=(s0+r0*max(s0))[r0==i]
+    tt=x0[r0==i]
+    plt.scatter(xt,yt,c=tt,edgecolors='face',s=0.1,cmap=cm.rainbow,vmin=Tremd[0],vmax=Tremd[-1])
+  plt.xlim(0,max(s)+max(s)*max(r))
+  plt.savefig('remd_step_rms.png')
   
 
 x,y,rms= np.loadtxt('file_wham.thermal',usecols=(0,6,4),unpack=True)
@@ -92,7 +106,7 @@ x,y,rms= np.loadtxt('file_wham.thermal',usecols=(0,6,4),unpack=True)
 plt.clf()
 plt.xlabel('bath temperature [K]')
 plt.ylabel('heat capacity')
-plt.xlim(Tremd[1]-10, Tremd[-1]+10)
+plt.xlim(Tremd[0]-10, Tremd[-1]+10)
 plt.plot(x,y,'-',color=c) 
 plt.savefig('remd_cv.png')
 
@@ -100,6 +114,7 @@ if ncolumns==14:
   plt.clf()
   plt.xlabel('bath temperature [K]')
   plt.ylabel('average RMSD')
-  plt.xlim(Tremd[1]-10, Tremd[-1]+10)
+  plt.xlim(Tremd[0]-10, Tremd[-1]+10)
   plt.plot(x,rms,'-')
   plt.savefig('remd_rmsd.png')
+