#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt

env="complex"

def GetdUs(lo,hi):
    df1=np.loadtxt("%s/unified/t1/dats/efep_%.8f_%.8f.dat"%(env,lo,hi))[:,1]
    df2=np.loadtxt("%s/unified/t1/dats/efep_%.8f_%.8f.dat"%(env,lo,lo))[:,1]
    
    df3=np.loadtxt("%s/unified/t1/dats/efep_%.8f_%.8f.dat"%(env,hi,hi))[:,1]
    df4=np.loadtxt("%s/unified/t1/dats/efep_%.8f_%.8f.dat"%(env,hi,lo))[:,1]
   
    return df1-df2, df3-df4


fig, ax = plt.subplots(nrows=5, ncols=4,
                       sharex=False, sharey=True,
                       figsize=(8, 8))
ax = ax.flatten()

for iplt,lo in enumerate(np.arange(0.0,1.0,0.05)):
    #icol = iplt % 4
    #irow = iplt // 4    
    a,b = GetdUs(lo,lo+0.05)
    
    xmin = min(np.amin(a),np.amin(b))
    xmax = max(np.amax(a),np.amax(b))
    xmin, xmax = xmin-(xmax-xmin)*0.1, xmax+(xmax-xmin)*0.1
    ax[iplt].hist(a, bins=35, range=(xmin,xmax), color="red", alpha=0.7)
    ax[iplt].hist(b, bins=35, range=(xmin,xmax), color="blue",alpha=0.7)
    ax[iplt].set_xlim(xmin,xmax)
    ax[iplt].set_title("%.2f and %.2f"%(lo,lo+0.05))

plt.tight_layout()
plt.savefig("%s.png"%(env))