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9.contributions.py
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9.contributions.py
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import numpy as np
import statistics
import matplotlib.pyplot as plt
from itertools import repeat
import os
show=##show##
division=##div##
condition1='../##file_pmf##'
arr1 = os.listdir(condition1)
arr1=sorted(arr1)
condition2='../##file_pmf_vdw##'
arr2 = os.listdir(condition2)
arr2=sorted(arr2)
arr=arr1+arr2
#######################################################################################
def make_substraction(common, reference_x, reference_y, target_x, target_y, dd, name, show):
# Making a new dict
dict_output={}
for i in common:
dict_output[i]=[]
for d in dict_output.keys():
cc=0
for t in reference_x:
if t == d:
dict_output[d].append(reference_y[cc])
cc+=1
for d in dict_output.keys():
cc=0
for t in target_x:
if t == d:
dict_output[d].append(target_y[cc])
cc+=1
# Making substraction
list_x=[]
list_y=[]
for i in dict_output.items():
x=i[0]
y=i[1][0]-i[1][1]
list_x.append(x)
list_y.append(y)
list_0=[]
list_0.extend(repeat(0,len(list_x)))
# Making plot
file1="0.average_"+name+"_div"+str(dd)+".pmf"
np.savetxt(file1,np.c_[list_x,list_y,list_0],fmt='%1.1f' '\t' '%1.5f' '\t' '%1.0f',header=name)
plt.plot(list_x,list_y)
plt.xlabel('Distance ($\AA$)')
plt.ylabel('Free energy ($k_B$$T$)')
if show == 1:
plt.show()
return list_x, list_y
#######################################################################################
for d in range(1,division+1):
main_target='div'+str(d)+'.pfm'
for f in arr:
if len(f.split('_')) > 1:
target=f.split('_')[-1]
condition=f.split('_')[0]
f1=condition1+'/'+f
f2=condition2+'/'+f
if target == main_target and condition == '0.average':
total_x=np.loadtxt(f1)[:, 0]
total_y=np.loadtxt(f1)[:, 1]
if target == main_target and condition == 'vdw':
vdw_x=np.loadtxt(f2)[:, 0]
vdw_y=np.loadtxt(f2)[:, 1]
common1=list(set(total_x).intersection(vdw_x))
common1=sorted(common1)
name='electrostatic'
list_x, list_y = make_substraction(common1, total_x, total_y, vdw_x, vdw_y, d, name, show)
print('electrostatic contribution calculated!')
#######################################################################################
############# Creating index #############
print("creating index based on x-axis (separation distance)")
arr3 = os.listdir()
arr3 = sorted(arr3)
list_x=[]
for f in arr3:
if len(f.split('_')) > 1:
pfm_x=np.loadtxt(f)[:, 0]
list_x.extend(pfm_x)
list_x=sorted(list_x)
dic_x=dict.fromkeys(list_x)
for n,m in dic_x.items(): dic_x[n]=[]
############# Adding KT values to each index #############
list_y=[]
list_name=[]
for f in arr3:
if len(f.split('_')) > 1:
x=np.loadtxt(f)[:, 0]
y=np.loadtxt(f)[:, 1]
#list_name.append(f)
j=0
tt=0
for g in dic_x:
try:
if g == x[j]:
dic_x[g].append(y[j])
j+=1
except IndexError:
if tt==0:
print(f'ATTENTION!!!: Problem in curve {f}, only {len(y)} points are detected')
tt+=1
############# Computing deviation #############
list_x=[]
list_y=[]
list_dev=[]
for n,m in dic_x.items():
x=n
h=(len(m))
y=statistics.mean(m)
dev=statistics.stdev(m)
list_x.append(x)
list_y.append(y)
list_dev.append(dev)
print("standard deviation calculated!\n")
file3="0.average_and_deviation_div"+str(division)+".pfm"
header_name="average electrostatic curves"
np.savetxt(file3,np.c_[list_x,list_y,list_dev],fmt='%1.1f' '\t' '%10.5f' '\t' '%10.5f',header=header_name)
plt.clf()
plt.plot(list_x,list_y)
plt.errorbar(list_x,list_y,yerr=list_dev,fmt='.k')
plt.xlabel('Distance ($\AA$)')
plt.ylabel('Free energy ($k_B$$T$)')
if show == 1:
plt.show()