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:

from craterpy import CraterDatabase, sample_data

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

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

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

Extract zonal statistics for crater regions of interest.

# Import lunar crater and define the floor and rim
cdb = CraterDatabase(sample_data['moon_craters.csv'], 'Moon', units='km')
cdb.add_annuli("floor", 0.4, 0.8)  # Crater floor (exclude central peak and rim)
cdb.add_annuli("rim", 0.9, 1.1)  # Thin annulus at crater rim

# Compute summary statistics for every ROI see docs for supported stats
stats = cdb.get_stats(sample_data['moon_dem.tif'], regions=['floor', 'rim'], stats=['median'])

# Compute crater depth as rim elevation - floor elevation
stats['depth (m)'] = (stats.median_rim - stats.median_floor)
print(stats.head(3).round(2))

# Name     Rad      Lat     Lon     median_floor  median_rim  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:

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.