Skip to content

Analysis

This section documents the analysis layer in ReaxKit: functions that transform parsed ReaxFF data into metrics, summaries, plots, and exportable tables.

How this docs folder is organized

This folder is split into two documentation groups:

  • Per-file analyses → analyses tied to a single ReaxFF output file
    (for example: “what can I compute from xmolout alone?”)

  • Composed analyses → higher-level routines that combine multiple files/handlers
    (for example: “use xmolout + fort.7 connectivity to compute local dipoles / cluster properties”)

What you’ll find on each analysis page

Most pages follow the same structure so they are easy to scan:

  1. What it computes (metric/summary/plot)
  2. Inputs (which file(s), which handler(s), required columns/metadata)
  3. Outputs (DataFrame schema, plots, exported CSV structure)
  4. Python example (direct API usage)
  5. CLI example (the equivalent reaxkit <file> <task> ... usage)
  6. Notes / gotchas (units, frame/iteration mapping, alias resolution)

Quick usage patterns

Python

Typical usage is:

from reaxkit.io.xmolout_handler import XmoloutHandler
from reaxkit.analysis.xmolout_analyzer import get_xmolout_data  # example

xh = XmoloutHandler("xmolout")
df = get_xmolout_data(xh)
print(df.head())

CLI

Most analyses are also available as CLI workflows:

reaxkit <file-kind> <task> [--file ...] [--xaxis ...] [--yaxis ...] [--plot] [--save ...] [--export ...]

Exact subcommands/options are documented on the corresponding page under per_file/ or composed/.

Conventions used across analyses

  • Frames vs iterations
    ReaxFF often reports iterations while plotting is often easier in time or frame index. Many workflows support --xaxis iter|frame|time and convert using the run control file.

  • Column aliases
    Many files use different headers for the same concept (e.g., Density vs Dens(kg/dm3)). Workflows typically resolve these via the alias utilities so users can pass canonical names.