craterpy

A python library for impact crater data science

https://github.com/cjtu/craterpy

Science Score: 100.0%

This score indicates how likely this project is to be science-related based on various indicators:

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Published in Journal of Open Source Software

Keywords

data-science open-science planetary python

Keywords from Contributors

mesh interpretability sequences generic projection interactive optim hacking network-simulation

Last synced: 4 months ago · JSON representation ·

Repository

A python library for impact crater data science

Basic Info

Host: GitHub
Owner: cjtu
License: mit
Language: Python
Default Branch: main
Homepage: https://craterpy.readthedocs.io/
Size: 14 MB

Statistics

Stars: 20
Watchers: 5
Forks: 8
Open Issues: 13
Releases: 14

Topics

data-science open-science planetary python

Created over 8 years ago · Last pushed 4 months ago

Metadata Files

Readme Contributing License Code of conduct Citation Authors

Craterpy: Impact crater data science in Python

Overview

Craterpy makes it easier to work with impact crater data in Python. Highlights:

convert a table of crater data to a GeoDataFrame or GIS-ready shapefile
extract zonal statistics associated with each crater in circlular or annular regions (rasterstats)
eliminate some pain points of planetary GIS analysis (antimeridian wrapping, projection conversions, etc.)

Note: Craterpy is not a crater detection algorithm (e.g. PyCDA), nor is it a crater count age dating tool (see craterstats).

Note: Craterpy is in development. We appreciate bug reports and feature requests on the issues board.

Quickstart

Install with pip install craterpy then follow the full worked example in the docs Getting Started.

Demo

Quickly import tabluar crater data from a CSV and visualize it on a geotiff in 2 lines of code:

```python from craterpy import CraterDatabase, sample_data

cdb = CraterDatabase(sampledata['vestacraters.csv'], 'Vesta', units='m') cdb.plot(sample_data['vesta.tif'], alpha=0.5, color='tab:green') ```

Vesta map plot

Clip and plot targeted regions around each crater from large raster datasets.

python cdb.add_circles('crater_rois', 3) cdb.plot_rois(sample_data['vesta.tif'], 'crater_rois', range(1500, 1503))

Vesta plot rois

Extract zonal statistics for crater regions of interest.

```python

Import lunar crater and define the floor and rim

cdb = CraterDatabase(sampledata['mooncraters.csv'], 'Moon', units='km') cdb.addannuli("floor", 0.4, 0.8) # Crater floor (exclude central peak and rim) cdb.addannuli("rim", 0.9, 1.1) # Thin annulus at crater rim

Compute summary statistics for every ROI see docs for supported stats

stats = cdb.getstats(sampledata['moon_dem.tif'], regions=['floor', 'rim'], stats=['median'])

Compute crater depth as rim elevation - floor elevation

stats['depth (m)'] = (stats.medianrim - stats.medianfloor) print(stats.head(3).round(2))

Name Rad Lat Lon medianfloor medianrim depth (m)

Olbers D 50.015 10.23 -78.03 -1452.50 -1322.88 129.62

Schuster 50.04 4.44 146.42 445.58 1976.97 1531.39

Gilbert 50.125 -3.20 76.16 -2213.66 -731.64 1482.02

```

Documentation

Full API documentation and usage examples are available at ReadTheDocs.

Installation

We recommend pip installing craterpy into a virtual environment, e.g. with conda or venv:

bash pip install craterpy - Note: Craterpy is currently only tested on Ubuntu and OS X but may work on some versions of Windows.

Contributing

There are two major ways you can help improve craterpy:

Report bugs or request new features on the issues board.
Contributing directly. See CONTRIBUTING.rst for full details. First time open source contributors are welcome!

Citing craterpy

Craterpy is MIT Licenced and is free to use with attribution. Citation information can be found here.

Owner

Name: Christian J. Tai Udovicic
Login: cjtu
Kind: user
Location: Honolulu, HI

Website: cjtu.github.io
Repositories: 26
Profile: https://github.com/cjtu

Open planetary science, software dev, data science @openplanetary

JOSS Publication

Craterpy: Impact crater data science in Python

Published

September 29, 2025

DOI

10.21105/joss.08663

Volume 10, Issue 113, Page 8663

Authors

Christian J. Tai Udovicic

Hawaiʻi Institute of Geophysics and Planetology, School of Ocean and Earth Science and Technology, University of Hawaiʻi at Manoa, Honolulu, HI, United States of America

Ari Essunfeld

Los Alamos National Laboratory, Los Alamos, NM, United States of America

Emily S. Costello

Hawaiʻi Institute of Geophysics and Planetology, School of Ocean and Earth Science and Technology, University of Hawaiʻi at Manoa, Honolulu, HI, United States of America

Editor

James Gaboardi

Citation (CITATION.cff)

cff-version: 1.2.0
type: software
message: "If you use this software, please cite it as below."
authors:
- family-names: "Tai Udovicic"
  given-names: "Christian J."
  affiliation: University of Hawaii at Manoa
  orcid: "https://orcid.org/0000-0001-9972-1534"
- family-names: "Essunfeld"
  given-names: "Ari"
  orcid: "https://orcid.org/0000-0001-8689-0734"
title: "Craterpy"
doi: 10.5281/zenodo.830057
url: "https://github.com/cjtu/craterpy"
license: MIT

GitHub Events

Total

Create event: 17
Release event: 5
Issues event: 34
Watch event: 4
Delete event: 16
Member event: 1
Issue comment event: 50
Push event: 56
Pull request review event: 17
Pull request review comment event: 30
Pull request event: 41

Last Year

Create event: 17
Release event: 5
Issues event: 34
Watch event: 4
Delete event: 16
Member event: 1
Issue comment event: 50
Push event: 56
Pull request review event: 17
Pull request review comment event: 30
Pull request event: 41

Committers

Last synced: almost 2 years ago

All Time

Total Commits: 266
Total Committers: 8
Avg Commits per committer: 33.25
Development Distribution Score (DDS): 0.195

Past Year

Commits: 0
Committers: 0
Avg Commits per committer: 0.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Christian	c**c@g**m	214
Cjtu	c**i@r**m	41
Cong	c**s@g**m	3
Cailin Gallinger	c**r@m**a	3
Cjtu	c**c@m**a	2
Alex Boivin	a**n@m**a	1
Dylan Hickson	d**n@g**m	1
dependabot[bot]	4****]	1

Committer Domains (Top 20 + Academic)

mail.utoronto.ca: 3 rogers.com: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 34
Total pull requests: 87
Average time to close issues: almost 2 years
Average time to close pull requests: 4 months
Total issue authors: 7
Total pull request authors: 7
Average comments per issue: 0.65
Average comments per pull request: 1.09
Merged pull requests: 31
Bot issues: 0
Bot pull requests: 51

Past Year

Issues: 24
Pull requests: 42
Average time to close issues: 22 days
Average time to close pull requests: 12 days
Issue authors: 4
Pull request authors: 3
Average comments per issue: 0.63
Average comments per pull request: 1.24
Merged pull requests: 21
Bot issues: 0
Bot pull requests: 15

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Top Authors

Issue Authors

cjtu (22)
ESCostello (4)
marcsit (3)
athulpg007 (2)
cgallinger (1)
ghentr (1)
cxong (1)

Pull Request Authors

dependabot[bot] (51)
cjtu (17)
ariessunfeld (15)
boivinalex (1)
graduateddylinder (1)
cgallinger (1)
cxong (1)

Top Labels

Issue Labels

Status: Available (5) Type: Enhancement (5) Status: In Progress (3) Priority: Medium (3) Type: Bug (2) Priority: High (2) help wanted (2) Hacktoberfest (2) Easy (2) Type: Investigate (1) Priority: Critical (1) Status: Completed (1) Priority: Low (1) Type: Feature Request (1) good first issue (1) Maintenance (1)

Pull Request Labels

dependencies (48) python (2)

Packages

Total packages: 1
Total downloads:
- pypi 271 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 12
Total maintainers: 1

pypi.org: craterpy

Impact crater data science in Python.

Documentation: https://craterpy.readthedocs.io/
License: MIT
Latest release: 0.9.4
published 5 months ago

Versions: 12
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 271 Last month

Rankings

Dependent packages count: 10.1%

Forks count: 12.6%

Stargazers count: 14.6%

Average: 18.1%

Dependent repos count: 21.5%

Downloads: 31.8%

Maintainers (1)

cjtu

Last synced: 4 months ago

Dependencies

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.github/workflows/pypi_publish.yml actions

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.github/workflows/test_pypi_publish.yml actions

actions/checkout v2 composite
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craterpy

Science Score: 100.0%

Keywords

Keywords from Contributors

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

Craterpy: Impact crater data science in Python

Overview

Quickstart

Demo

Import lunar crater and define the floor and rim

Compute summary statistics for every ROI see docs for supported stats

Compute crater depth as rim elevation - floor elevation

Name Rad Lat Lon medianfloor medianrim depth (m)

Olbers D 50.015 10.23 -78.03 -1452.50 -1322.88 129.62

Schuster 50.04 4.44 146.42 445.58 1976.97 1531.39

Gilbert 50.125 -3.20 76.16 -2213.66 -731.64 1482.02

Documentation

Installation

Contributing

Citing craterpy

Owner

JOSS Publication

Craterpy: Impact crater data science in Python

Authors

Editor

Tags

Citation (CITATION.cff)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

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Committer Domains (Top 20 + Academic)

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Packages

pypi.org: craterpy

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Maintainers (1)

Dependencies