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Jim Bosch's Projects

analysis icon analysis

Data analysis utility code for working with LSST/HSC stack outputs

astshim icon astshim

C++ shim for a subset of the AST astronomical library

bp3 icon bp3

early prototype for a successor to Boost.Python v2

eups icon eups

A version manager tracking product dependencies

fake-sources icon fake-sources

creates and adds GalSim created sources to HSC/LSST images

gbdes icon gbdes

Gary's DES instrumental signature removal / fitting programs

great4-general icon great4-general

Discussion, planning, and miscellaneous content for the 4th Gravitational Lensing Accuracy Testing project.

lsst-bot icon lsst-bot

Unpolished high-level tools for building and managing EUPS packages in the LSST software stack.

lsst-tkt-helper icon lsst-tkt-helper

Helper tool for managing Rubin Observatory LSST Data Management development with git, EUPS, and Jira.

mcpib icon mcpib

Modern C++/Python Interface Builder

meds icon meds

Python and C libraries to work with Multi Epoch Data Structures

piff icon piff

PSFs In the Full FOV. A software package for modeling the point-spread function (PSF) across the full field of view (FOV). Documentation:

pixregions icon pixregions

an Astropy affiliated package for pixel regions and threshold-based detection

pybind11 icon pybind11

Seamless operability between C++11 and Python

sphgeom icon sphgeom

C++ spherical geometry primitives for LSST Data Management

sympy icon sympy

A computer algebra system written in pure Python

thetractor icon thetractor

Please use the original tractor git page unless you're looking for my tinkering with the Gaussian mixture optimization code

tutorial-lsst-lyon-2017 icon tutorial-lsst-lyon-2017

Jupyter notebook tutorial for using the LSST Data Management software stack, created for the June 2017 meeting in Lyon

typeshed icon typeshed

Collection of library stubs for Python, with static types

umemofi icon umemofi

Unified Multi-Exposure Multi-Object Fitting Interface

usrp-school icon usrp-school

Lesson plans and materials for image-processing mini-course for Princeton USRP students

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