Python

Determination of coordination number of a metal using trajectory.

import os import pandas as pd import numpy as np

def big_f(fpath): df = pd.read_csv(fpath, sep = '\s+', header = None, names = ['n','x','y','z']) no_of_atoms = int(df.n[0]) no_of_frames = len(df)//(no_of_atoms + 2) result = [] for i in range(no_of_frames): result.append(df.iloc[i*(no_of_atoms+2)+2:(i+1)*(no_of_atoms+2)]) return result res = big_f("file")

Function to calculate Euclidean distance

def euclidean_distance(x1, y1, z1, x2, y2, z2): return np.sqrt((x2 - x1)**2 + (y2 - y1)**2 + (z2 - z1)**2)

test=0 with open("name.txt", "w") as f:

Function to calculate X metal distances in a dataframe

def calculate_li_distances(df, list_of_atoms = ['O', 'F'], threshold = 2.2): li_rows = df[df['n'] == 'X'] # Filter rows with 'X' Li_number=0 #Added print("Co-ordination number of Li for below frame", file=f) #Added for index, row in li_rows.iterrows(): test=0 #Added li_coords = row[[1, 2, 3]].values # Extract x, y, z values for Li li_name = f'X_{index}' # Create a unique name for the Li atom df[li_name] = np.nan # Create a new column with NaN values for storing distances for i, r in df.iterrows(): if i != index: # Skip the row for Li itself if r['n'] in list_of_atoms: atom_coords = r[[1, 2, 3]].values # Extract x, y, z values for other atoms distance = euclidean_distance(li_coords[0], li_coords[1], li_coords[2], atom_coords[0], atom_coords[1], atom_coords[2]) # Calculate Euclidean distance if distance <= threshold: test=test+1 # Added df.at[i, li_name] = distance # Store the distance in the corresponding column Li_number=Li_number+1 # Added print("Li{}_CN".format(Li_number),test, file=f) #Added return df.dropna(thresh=5)

count = 0 for df in res: df = calculate_li_distances(df) #print(df, file=f) count += 1 print('frame',count, file=f) print('-------------------------------------------------------------', file=f)