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High-performance Rust library and Python extension for reading LAMMPS log files

Project description

Log LAMMPS Reader

Log LAMMPS Reader is a high-performance Rust library and Python extension for reading LAMMPS log files and converting them into DataFrames using the Polars library. This project leverages PyO3 to create a Python module that interfaces with Rust code, ensuring both speed and efficiency.

This package returns a polars DataFrame allowing the user to use powerful data manipulations (e.g filters) provided through polars. The user can specify which specific thermo output given by run or mimimize that is required.

It also has the ability to get the lines in the log file that start with a certain string prefix, like fix or print extremely quickly using rust backend. This can be parsed using python to get information about the parameters set for the simulation.

Features

  • High-speed reading of LAMMPS log files
  • Converts log data into Polars DataFrames
  • Exposes functionality to Python through a PyO3 module
  • Gets thermo data for multiple thermo runs
  • Better data parsing, skips rows if they are invalid (e.g missing newline, non-numeric characters in the log)
  • Only stores the needed thermo run data specified by user
  • Also able to get lines in the log file which starts with a certain string prefix

Installation

Using pip:

pip install log-lammps-reader

Alternatively look at build instructions to build the project.

Usage Examples

  • Note the run_number = 0 gives the first data output which might include the minimization run.
  • To get the useful data start with run_number = 1.

Build For Python

import log_lammps_reader

thermo_number = 0 # Choose the nth number of thermo run
df = log_lammps_reader.new('log.lammps') # polars DataFrame for 1st thermo run
# usually the minimization run

# Or choose the nth number of thermo run (default n = 0)
# n = 0 might consider the MPI minimization data, so in most cases
# start with n = 1
df = log_lammps_reader.new('log.lammps', n) 
time = df.get_column('Time') # Get any thermo column
time_squared = time ** 2 # use broadcasting operations similar to numpy

# Use polars to filter the results.
import polars as pl
equilibrated_df = df.filter(pl.col('Time') > 1) 

# Convert data to numpy if needed
import numpy as np
step = np.array(df.get_column('Step'))

# Get lines in the log that start with a prefix string
fixes_list = log_lammps_reader.log_starts_with('log.lammps', 'fix')

Example of a DataFrame for a LAMMPS log file.

>>> import log_lammps_reader
>>> df = log_lammps_reader.new('log.lammps', 1)
>>> df
shape: (10_000_002, 10)
┌──────────────┬───────────┬───────────┬───────────┬───┬───────┬────────────┬───────────┬───────────┐
 Step          Time       Temp       Press        Atoms  PotEng      KinEng     TotEng    
 ---           ---        ---        ---           ---    ---         ---        ---       
 f64           f64        f64        f64           f64    f64         f64        f64       
╞══════════════╪═══════════╪═══════════╪═══════════╪═══╪═══════╪════════════╪═══════════╪═══════════╡
 61.0          0.0        298.0      57.20028     519.0  -14.776112  19.953113  5.1770012 
 70.0          0.009      296.73074  60.840723    519.0  -14.721924  19.868128  5.1462039 
 80.0          0.019      292.56952  72.565657    519.0  -14.530972  19.589506  5.0585341 
 90.0          0.029      285.36347  92.936408    519.0  -14.18668   19.107012  4.9203316 
 100.0         0.039      275.29149  121.91127    519.0  -13.681587  18.432625  4.7510379 
                                                                                  
 1.0000003e8   99999.969  301.90216  225.03035    519.0  -11.279288  20.214389  8.9351011 
 1.0000004e8   99999.979  301.99266  220.86566    519.0  -11.33326   20.220449  8.8871881 
 1.0000005e8   99999.989  302.04158  215.55467    519.0  -11.406581  20.223724  8.8171428 
 1.0000006e8   99999.999  301.61379  210.565      519.0  -11.471215  20.195081  8.723866  
 1.00000061e8  100000.0   301.52726  210.15164    519.0  -11.475823  20.189287  8.7134637 
└──────────────┴───────────┴───────────┴───────────┴───┴───────┴────────────┴───────────┴───────────┘
>>> df.get_column('Time')
shape: (10_000_002,)
Series: 'Time' [f64]
[
        0.0
        0.009
        0.019
        0.029
        0.039
        
        99999.969
        99999.979
        99999.989
        99999.999
        100000.0
]
>>> df.get_column('Time').mean()
50000.00399999919
>>> df.get_column('Time').std()
28867.520676357886
# Example of getting the lines that start with a certain prefix in the log file
# Returns a list of strings.
>>> log_lammps_reader.log_starts_with('log.lammps', 'fix')
['fix WALL methane wall/region/tjatjopoulos pore 0.005547314165349033 3.565 0.4824 ${radius}',
 'fix WALL methane wall/region/tjatjopoulos pore 0.005547314165349033 3.565 0.4824 30',
 'fix NVT all nvt temp ${temp_sim} ${temp_sim} $(100.0*dt)',
 'fix NVT all nvt temp 298 ${temp_sim} $(100.0*dt)',
 'fix NVT all nvt temp 298 298 $(100.0*dt)',
 'fix NVT all nvt temp 298 298 0.10000000000000000555']

Rust

Clone the repo and add it to your project

use log_lammps_reader::LogLammpsReader;

fn main() {
    let log_file_name = "log.lammps";
    // skipping minimization
    let run_number = Some(1);


    match LogLammpsReader::new(log_file_name.into(), run_number) {
        Ok(df) => println!("DataFrame read successfully: {:?}", df),
        Err(e) => eprintln!("Error reading DataFrame: {}", e),
    }
}

Build From Source

Alternatively, to build the Python module, follow these steps:

Requirements

  • Rust (latest stable version recommended)
  • Python 3.8 or later
  • Cargo (Rust package manager)
  1. Ensure you have maturin installed:

    pip install maturin # or use conda or micromamba
    
  2. Compile the Rust packages and install the python module.

    maturin develop --release
    

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