Curls

In preparation.

   # /usr/bin/env python3
   # coding: utf-8
   import numpy as np
   import pandas as pd
   import sys
   file=sys.argv[1]
   cell_vec=pd.read_csv(file, delim_whitespace=True,skiprows=2,nrows=3,names=['x','y','z'])
   cell_vec.head()
   a1=np.array([float(cell_vec.loc[0].x),float(cell_vec.loc[0].y),float(cell_vec.loc[0].z)])
   a2=np.array([float(cell_vec.loc[1].x),float(cell_vec.loc[1].y),float(cell_vec.loc[1].z)])
   a3=np.array([float(cell_vec.loc[2].x),float(cell_vec.loc[2].y),float(cell_vec.loc[2].z)])
   atoms_n=pd.read_csv(file, delim_whitespace=True,skiprows=5,nrows=1)
   data=pd.read_csv(file, delim_whitespace=True,skiprows=7,names=['x','y','z'], index_col=False)
   nloops=data.x.value_counts().loc["Direct"]
   n_atoms=atoms_n.T.sum().loc[0]
   n1=int(sys.argv[2])
   n2=int(sys.argv[3])
   low=1
   for i in range(nloops):
       up=low+n_atoms
       frame=data[low:up]
       low=low+n_atoms+1
       atom_pos1=frame.iloc[n1-1]
       coord1=(float(atom_pos1.x)*a1)+(float(atom_pos1.y)*a2)+(float(atom_pos1.z)*a3)
       atom_pos2=frame.iloc[n2-1]
       coord2=(float(atom_pos2.x)*a1)+(float(atom_pos2.y)*a2)+(float(atom_pos2.z)*a3)
       distance=min(np.linalg.norm(coord1-coord2),
           np.linalg.norm(coord1-(coord2+a1)),
           np.linalg.norm(coord1-(coord2+a2)),
           np.linalg.norm(coord1-(coord2+a1+a2)),
           np.linalg.norm(coord1-(coord2-a1)),
           np.linalg.norm(coord1-(coord2-a2)),
           np.linalg.norm(coord1-(coord2-a1-a2))
          )
       print(distance)

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