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# Ignore everything
*
# But track these files
!.gitignore
!dump2rotorang.py
!example.lammpstrj
!Readme.org
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#+TITLE: dump2rotorang.py
#+AUTHOR:
#+DATE:
* Overview
=dump2rotorang.py= analyzes LAMMPS trajectory files and calculates
orientation and z-position distributions of benzene molecules.
The script reads LAMMPS dump trajectory files =*.lammpstrj=, extracts the
coordinates of selected atoms in each molecule, and evaluates:
- the in-plane orientation angle of each benzene molecule
- the center z-position of each benzene molecule
The resulting histograms are saved as Python pickle files.
* Requirements
This script requires Python 3 and the following Python packages:
- numpy
- pandas
Install them, for example, using pip:
#+begin_src sh
pip install numpy pandas
#+end_src
* Input files
The script searches for trajectory files with the following filename
patterns:
#+begin_src text
D3d-o_*K.lammpstrj
D3d-p_*K.lammpstrj
#+end_src
For example:
#+begin_src text
D3d-o_300K.lammpstrj
D3d-o_400K.lammpstrj
D3d-p_300K.lammpstrj
D3d-p_400K.lammpstrj
#+end_src
The temperature is extracted from the filename using the pattern:
#+begin_src text
_(number)K.lammpstrj
#+end_src
For example, =D3d-o_300K.lammpstrj= is interpreted as 300 K.
* LAMMPS dump format
The trajectory file is assumed to be a LAMMPS dump file containing
unwrapped atomic coordinates:
#+begin_src text
xu yu zu
#+end_src
The script also assumes that the dump file contains a =mol= column, which
is used to identify molecules.
A typical header should include columns such as:
#+begin_src text
ITEM: ATOMS id mol type xu yu zu
#+end_src
* Analysis details
The benzene atoms are selected by the following atom indices within each
molecule:
#+begin_src python
benzene_id = [24, 25, 26, 27, 28, 29]
#+end_src
These indices are hard-coded in the script.
The orientation of each benzene molecule is calculated from the vector
between:
- the center of the selected benzene atoms
- the midpoint of atoms 25 and 26 in the selected benzene atom list
The orientation angle is calculated using:
#+begin_src python
np.arctan2(vec[:, 1], vec[:, 0])
#+end_src
The z-position is calculated as the mean z-coordinate of the selected
benzene atoms.
* Output files
The script creates the following pickle files:
#+begin_src text
D3d-o.pkl
D3d-p.pkl
#+end_src
Each pickle file contains a dictionary indexed by temperature.
For example:
#+begin_src python
dset[300]["orientation"]
#+end_src
contains a pandas DataFrame with the following columns:
| Column | Description |
|-----------+------------------------------------------|
| angle | Bin center of orientation angle |
| angle_y | Histogram count of orientation angle |
| zpos | Bin center of z-position |
| zpos_y | Histogram count of z-position |
* Usage
Place =dump2rotorang.py= in the directory containing the LAMMPS trajectory
files, then run:
#+begin_src sh
python dump2rotorang.py
#+end_src
If trajectory files matching the expected patterns exist, the script will
print the processed filenames and create pickle files.
Example:
#+begin_src text
D3d-o_300K.lammpstrj
D3d-o_400K.lammpstrj
D3d-o.pkl was created.
D3d-p_300K.lammpstrj
D3d-p_400K.lammpstrj
D3d-p.pkl was created.
#+end_src
* Example
If =example.lammpstrj= is included as a sample trajectory file, rename or
copy it to match the expected naming rule before running the script:
#+begin_src sh
cp example.lammpstrj D3d-o_300K.lammpstrj
python dump2rotorang.py
#+end_src
This will create:
#+begin_src text
D3d-o.pkl
#+end_src
* Notes
- The atom indices used for benzene are currently hard-coded.
- The script assumes that all molecules have the same number of atoms.
- The orientation histogram is calculated in the range from =-pi= to =pi=.
- The z-position histogram is calculated in the range from =24= to =25=.
- If the target system or molecule definition is changed, the values of
=benzene_id= and the histogram range for z-position may need to be
modified.
* Files managed in this repository
This repository is intended to manage only the following files:
#+begin_src text
dump2rotorang.py
example.lammpstrj
README.org
.gitignore
#+end_src
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#!/usr/bin/env python
import numpy as np
import io
import re
import pickle
import glob
import pandas as pd
class LammpsTrj():
def __init__(self, trjfile):
self.fp = open(trjfile)
lines = [self.fp.readline() for i in range(4)]
self.atoms = int(lines[-1])
self.fp.seek(0)
self.getOnestep()
# print(self.df)
self.fp.seek(0)
self.molecules = np.unique(self.df["mol"]).shape[0]
def __del__(self):
self.fp.close()
def getOnestep(self):
block = self.atoms + 9
lines = [self.fp.readline() for i in range(block)]
if lines[0] == "":
return 0
self.step = int(lines[1])
self.lx = float(lines[5].split()[1])
self.ly = float(lines[6].split()[1])
self.lz = float(lines[7].split()[1])
header = lines[8].split()[2:]
data = io.StringIO(" ".join(lines[9:]))
self.df = pd.read_csv(data, delimiter=r"\s+", header=None)
self.df.columns = header
return 1
def getOrientation(self, benzene_id):
xyz = self.df[["xu", "yu", "zu"]].to_numpy()
xyz = xyz.reshape((self.molecules, -1, 3))
benzene_id = np.array(benzene_id, dtype=int) - 1
xyz = xyz[:, benzene_id, :]
g = xyz.mean(axis=1)
p = xyz[:, [1, 2], :].mean(axis=1)
vec = p - g
angle = np.arctan2(vec[:, 1], vec[:, 0])
return angle
# for i, xyz_i in enumerate(xyz):
# body = "{}\n\n".format(benzene_id.shape[0])
# for r in xyz_i:
# body += "C {} {} {}\n".format(*r)
# outfile = f"{i:04d}.xyz"
# with open(outfile, "w") as o:
# o.write(body)
def getZposition(self, benzene_id):
xyz = self.df[["xu", "yu", "zu"]].to_numpy()
xyz = xyz.reshape((self.molecules, -1, 3))
benzene_id = np.array(benzene_id, dtype=int) - 1
xyz = xyz[:, benzene_id, :]
zpos = xyz.mean(axis=1)[:, 2]
return zpos
def run(trjfile):
benzene_id = [24, 25, 26, 27, 28, 29]
lmp = LammpsTrj(trjfile)
orientation = np.empty((0, lmp.molecules))
zpos = np.empty((0, lmp.molecules))
while lmp.getOnestep():
# print(lmp.step)
orientation_ = lmp.getOrientation(benzene_id)
orientation = np.vstack((orientation, orientation_))
zpos_ = lmp.getZposition(benzene_id)
zpos = np.vstack((zpos, zpos_))
hist, x = np.histogram(orientation, bins=np.linspace(-np.pi, np.pi, 200))
df = pd.DataFrame()
df["angle"] = x[0:-1] + (x[1]-x[0])*0.5
df["angle_y"] = hist
hist, x = np.histogram(zpos, bins=np.linspace(24, 25, 200))
df["zpos"] = x[0:-1] + (x[1]-x[0])*0.5
df["zpos_y"] = hist
temp = int(re.search(r"_(\d+)K\.", trjfile).group(1))
dset[temp] = {}
dset[temp]["orientation"] = df
for k in ["D3d-o", "D3d-p"]:
dset = {}
files = sorted(glob.glob(f"{k}_*K.lammpstrj"))
for f in files:
print(f)
run(f)
outfile = f"{k}.pkl"
with open(outfile, "wb") as f:
pickle.dump(dset, f)
print(f"{outfile} was created.")
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