My Software

Software Development

My github repository can be found here:

TRIPPy: Trailed Image Photometry in Python

TRIPPy is a high precision photometry and PSF modelling package specifically designed for moving objects. Though it usually outperforms the standard IRAF phot/daophot packages for stellar images. TRIPPy was designed to maximize photometric signal-to-noise of trailed sources. It does this by using a pill-shaped aperture (example shown below), which minimizes background pixels included in the aperture, and ensures unbiased flux measurements. Effective aperture corrections are calculated from model trailed PSFs (or TSFs) which themselves are calculated by convolution of a stellar PSF model with a line representing the motion of the target on the image.

TRIPPy is easily installed with pip, and the source can be downloaded at the github. A full tutorial showing how easy it is to use TRIPPy is also available.

Example Pill Aperture

Wide Field Camera 3 PSF Fitter

This is a pair of (large) python modules. WFC3_PSFFits provides a class to handle the TinyTim PSF generation, and includes facilities for non-default image distortions, and generation of false images, and image differences. In addition, _PSFFits provides a class which uses CERN's Minuit package to allow PSF fitting (x,y position, brightness, zernicke distortions, and charge diffusion kernel.

WFC3_phot provides a class to handle aperture photometry using pyraf. It includes facilities for TinyTim PSF interpolation over known bad pixels and cosmic ray strikes.

This code can be found here: WFC3_PSFFitter.git.


This code has been developed to calculate the collisional evolution and resultant size distribution of a annulus of planetesimals. It has been developed in C and CUDA to utilize the computational prowess of CUDA-enabled GPUs. The first version was published in Fraser (2009). The current version includes velocity evolution using the recipe of Ohtsuki and Stewart (2002). Velocity damping due to collisions and the fragmentation model of Stewart and Leinhardt (2011) are being added.

This code is slowly being developed, and it's bones can be found here: CollVelEvo.git.

Hartigan's DIP test

Hartigan's DIP test is a non-parametric test of bimodality in single-variate data. This test is popular within the Kuiper belt community for analyzing observed colours. Despite this, no implementation of the software was previously available for the popular python scripted language. I have converted Ferenc Mechler's matlab implementation (available here ) to python utilizing the numpy package. Eventually this software will become part of the scipy statistics module. Before then, the simple module can be downloaded here: