Now the autoplotter works like charm

Author: mesonepigreco

scripts/sscha-plot-data.py

@@ -1,6 +1,5 @@
 #!python
 
-
 import numpy as np
 import matplotlib.pyplot as plt
 import sys, os
@@ -53,9 +52,20 @@ def main():
         assert os.path.exists(f), 'Error, file {} not found.'.format(f)
         assert os.path.exists(m), 'Error, file {} not found.'.format(m)
 
+    print("Reading the input...")
+
     # Load all the data
-    freqs_data = np.concatenate([f for f in freqs_files])
-    minim_data = np.concatenate([f for f in minim_files])
+    freqs_data = np.concatenate([np.loadtxt(f) for f in freqs_files])
+    minim_data = np.concatenate([np.loadtxt(f) for f in minim_files])
+
+    print("Plotting...")
+
+    # Insert the x axis in the plotting data
+    xsteps = np.arange(minim_data.shape[0])
+    new_data = np.zeros(( len(xsteps), 8), dtype = np.double)
+    new_data[:,0] = xsteps
+    new_data[:, 1:] = minim_data
+    minim_data = new_data
 
     fig_data, axarr = plt.subplots(nrows=2, ncols = 2, sharex = True, dpi = DPI)
 
@@ -66,10 +76,10 @@ def main():
     axarr[0,0].set_ylabel("Free energy / unit cell [meV]", fontsize = LBL_FS)
 
 
-    axarr[1,0].fill_between(minim_data[:,0], minim_data[:,3] - minim_data[:, 4]*.5 ,
+    axarr[0,1].fill_between(minim_data[:,0], minim_data[:,3] - minim_data[:, 4]*.5 ,
                             minim_data[:, 3] + minim_data[:, 4] * .5, color = "aquamarine")
-    axarr[1,0].plot(minim_data[:,0], minim_data[:,3], color = "k")
-    axarr[1,0].set_ylabel("FC gradient", fontsize = LBL_FS)
+    axarr[0,1].plot(minim_data[:,0], minim_data[:,3], color = "k")
+    axarr[0,1].set_ylabel("FC gradient", fontsize = LBL_FS)
 
     axarr[1,1].fill_between(minim_data[:,0], minim_data[:,5] - minim_data[:, 6]*.5 ,
                             minim_data[:, 5] + minim_data[:, 6] * .5, color = "aquamarine")
@@ -78,9 +88,9 @@ def main():
     axarr[1,1].set_xlabel("Good minimization steps", fontsize = LBL_FS)
 
 
-    axarr[0,1].plot(minim_data[:,0], minim_data[:,7], color = "k")
-    axarr[0,1].set_ylabel("Effective sample size", fontsize = LBL_FS)
-    axarr[0,1].set_xlabel("Good minimization steps", fontsize = LBL_FS)
+    axarr[1,0].plot(minim_data[:,0], minim_data[:,7], color = "k")
+    axarr[1,0].set_ylabel("Effective sample size", fontsize = LBL_FS)
+    axarr[1,0].set_xlabel("Good minimization steps", fontsize = LBL_FS)
     fig_data.tight_layout()