Jarvis-PLOT

Jarvis-PLOT is a lightweight, Python/Matplotlib-based plotting framework developed for Jarvis-HEP,
but it can also be used as a standalone scientific plotting tool.

It provides a simple command-line interface (CLI) to generate publication-quality figures from YAML configuration files, with most layout and style decisions handled by predefined profiles and style cards.

Current package version: 1.4.2.

Installation

pip install JarvisPLOT

The PyPI / distribution name is JarvisPLOT (normalized wheel name: jarvisplot). The product name remains Jarvis-PLOT. The Python import package and entrypoint remain unchanged:

import jarvisplot

jplot path/to/config.yaml

If you have an older environment that still uses a historical package name, replace:

pip uninstall jarvisplot Jarvis-PLOT JarvisPLOT
pip install JarvisPLOT

Command-Line Usage

Human help uses the same fixed-column Rich panels as Jarvis-HEP V2 / Portal:

jplot -h
jplot validate -h
jplot man                  # manual index
jplot man workflow         # topic page

Render (bare path — there is no jplot run):

jplot path/to/config.yaml
jplot path/to/config.yaml --rebuild-cache

Discover / judge (write YAML yourself in an editor):

jplot data describe samples.csv --json
jplot cap methods --json
jplot doctor plot.yaml --json
jplot man workflow --json          # agent-structured manual
jplot config expand plot.yaml --figure p --write   # type: → layers

Render a Jarvis-HEP flowchart scene JSON:

jplot flowchart path/to/scene.json
# optional output path:
jplot flowchart path/to/scene.json -o path/to/out.png

Library form:

from jarvisplot import render_flowchart, render_flowchart_file

Project Workdir and Cache

  • You can set project.workdir in YAML.
  • If output.dir is omitted, Jarvis-PLOT defaults to <workdir>/plots/.
  • Data cache is stored in <workdir>/.cache/.
  • Profiling pipelines are prebuilt once and reused from cache when source fingerprint and profile settings are unchanged.
  • Profiling uses a fast two-stage grid reduction (pregrid + render bin) for large datasets.

Example: SUSYRun2 Ternary Plots

jplot ./bin/SUSYRun2_EWMSSM.yaml
jplot ./bin/SUSYRun2_GEWMSSM.yaml

Note: The data file paths inside the YAML files must be updated to match your local setup.

Example: Dynesty Runplot

Jarvis-PLOT includes a reusable dynesty runplot format. With a dataset named dynesty, the figure can use the built-in card without writing axes or layer details:

DataSet:
- name: dynesty
  path: path/to/dynesty_result.csv
  type: csv

Figures:
- name: dynesty_logL_vs_logX
  enable: true
  style:
  - a4paper_2x1
  - dynesty_runplot

See docs/specs/DYNESTY_RUNPLOT.md for the default axes, KDE, scatter overlay, and evidence summary behavior.

Notes

  • Figures are saved automatically to the output paths defined in the YAML configuration.
  • Common output formats include PNG and PDF (backend-dependent).
  • Saved figures include file metadata such as Creator: Jarvis-PLOT, powered by Jarvis-HEP and Jarvis-PLOT version: X.Y.Z; the PNG Description also includes both fields for macOS Finder compatibility.
  • Jarvis-PLOT works in headless environments (SSH, batch jobs) without any GUI backend.

Requirements

Python

  • Python ≥ 3.10 (tested on 3.10–3.13)

Required Packages

  • numpy
  • pandas
  • polars
  • matplotlib
  • pyyaml
  • jsonschema
  • scipy — numerical utilities
  • h5py — required for loading HDF5 data files
  • shapely
  • sympy
  • loguru
  • deepmerge
  • Jarvis-Operas>=1.1.4

Github Page

https://github.com/Pengxuan-Zhu-Phys/Jarvis-PLOT

Documentation

https://pengxuan-zhu-phys.github.io/Jarvis-Docs/

Repository Docs

Tracked project docs live in docs/.

  • docs/README.md - repo doc index
  • docs/context/JARVIS_PLOT_CONTEXT.md - primary Codex-facing boundary doc
  • docs/context/CODE_MAP_JARVIS_PLOT.md - concrete code owner map
  • docs/context/JARVIS_PLOT_FRAMEWORK_LOGIC.md - runtime execution contract
  • docs/roadmap/IMPLEMENTATION_ROADMAP.md - active backlog and future work list
  • docs/specs/AGENT_DATA_API.md - planned agent bridge (spec only)
  • docs/dev/DEVELOPER_RULES.md - current pipeline and cache rules
  • docs/dev/MEMORY_OPTIMIZATION_GUIDE.md - narrow-table memory notes

Read the context docs and roadmap before changing parsing, transforms, rendering, or layout-related behavior.

License

MIT License

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (2.1.4)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for Buding-Phys from gravatar.com Buding-Phys

Requires

Python >=3.10

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