Andrew Saydjari (andrew-saydjari)

andrew-saydjari

Geek Repo

Company:@Harvard

Location:Cambridge, MA

Home Page:https://andrew-saydjari.github.io/

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Andrew Saydjari's repositories

EqWS.jl

Public package to compute translationally and rotationally invariant wavelet-based statistics on images.

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CloudCovErr.jl

Pipeline for debiasing and improving error bar estimates for photometry on top of structured/filamentary background.

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LowRankOps.jl

Type/method defintions for speeding up matrix computations for matrices built from low rank components.

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apMADGICS.jl

Pipeline for APOGEE spectra component separation

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andrew-saydjari.github.io

Personal Academic Website

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CloudClean.jl

Image infilling algorithm with focus on statistically accuracy

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crowdsource

Crowded field photometry pipeline

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dustmaps

A uniform interface for a number of 2D and 3D maps of interstellar dust reddening/extinction.

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KryburyCompress.jl

Compression method for storing large covariance matrices, which is also fast when they are built from low-rank factors.

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AdventOfCode2023.jl

My Julia solutions for Advent of Code 2023

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apogee_drp

SDSS-V APOGEE Reduction Pipeline

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brick-jwst-2221

Data reduction & analysis for the Brick JWST 2221 data

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crowdsourcephoto-feedstock

A conda-smithy repository for crowdsourcephoto.

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desi_retriever

Quick way of fetching DESI spectra in Python without logging to NERSC

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FITSIO.jl

Flexible Image Transport System (FITS) file support for Julia

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gspice

GSPICE: Gaussian Pixelwise Conditional Estimation

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Healpix.jl

Healpix library written in Julia

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IDL.jl

Call IDL from Julia

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Images.jl

An image library for Julia

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legacypipe

Image reduction pipeline for the DESI Legacy Imaging Surveys, using the Tractor framework

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legacyviewer_tools

Tools for working with the Legacy Survey Sky Browser.

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lsd

Large Survey Database

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mfouesneau.github.com

My personal website

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numpy

The fundamental package for scientific computing with Python.

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scikit-learn

scikit-learn: machine learning in Python

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SequencerJ.jl

Julia-language port of the Sequencer algorithm, originally developed in python (https://github.com/dalya/Sequencer). The Sequencer finds trends in 1-dimensional data sets and has been used by its original authors for data analysis in astrophysics, seismology, image processing, etc. Contributions are welcome!

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staged-recipes

A place to submit conda recipes before they become fully fledged conda-forge feedstocks

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wssa_utils

Utilities for reading WSSA tiles.

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