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Description:

loglammpsreader 0.2.5

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
Easily convert DataFrame into other formats like json, csv, parquet etc using polars
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 (e.g 'fix ...')

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 exclude minimization data, start with run_number = 1.

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 API
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)

Ensure you have maturin installed:
pip install maturin # or use conda or micromamba

Clone the repository
git clone https://github.com/GeordyJ/log_lammps_reader.git && cd log_lammps_reader

Compile the Rust packages and install the python module.
maturin develop --release