STDPipe - Simple Transient Detection Pipeline¶
AKA: random codes noone else will ever use
STDPipe is a set of Python routines for astrometry, photometry and transient detection related tasks, intended for quick and easy implementation of custom pipelines, as well as for interactive data analysis.
- Design principles:
implemented as a library of routines covering most common tasks
operates on standard Python objects: NumPy arrays for images, Astropy Tables for catalogs and object lists, etc
does not try to re-implement the things already implemented in other Python packages
conveniently wraps external codes that do not have their own Python interfaces (SExtractor, SCAMP, PSFEx, HOTPANTS, Astrometry.Net, …):
wrapping is transparent: all data passed from Python, all options customizable from Python, all (or most of) outputs available back
everything operates on temporary files, nothing is kept after the run unless explicitly asked for
Quick Start¶
See notebooks/stdpipe_tutorial.ipynb for an example notebook demonstrating basic steps of a typical image processing with STDPipe. This notebook uses the image available here.
User Guide¶
- About
- Installation
- Using STDPipe
- Data processing
- Pre-processing the data
- Object detection and measurement
- Real-Bogus Classification
- Reference catalogues
- Astrometric calibration
- Photometric calibration
- Object flags
- Image subtraction
- Transient detection and filtering
- Image cutouts
- Point Spread Function (PSF) models
- Lightcurves
- Image Simulation
- Convenience utilities
- Common principles
- Examples
- Data processing
- How to Contribute
- TODO list
- API documentation
Contributing¶
STDPipe is released under the MIT license. We encourage you to modify it, reuse it, and contribute changes back for the benefit of others. We follow standard open source development practices: changes are submitted as pull requests and, once they pass the test suite, reviewed by the team before inclusion. Please also see our contributing guide.