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code for analyzing light curves (classification, noisification, outlier detection)
R Python FORTRAN
branch: master

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data
data_analysis
data_processed
db
src
utils
.gitignore
README

README

by James Long
updated October 14, 2012

The purpose of this software suite is to apply noisification and denoisification methods on astronomical light curves. Run interp_test.py in src/ to get a feel for how the program works.

Folder descriptions (in order of importance):

:src:
python source code for getting light curves into data bases, noisifying light curves, outputting results in data_processed

:data_analysis:
mostly R code used for analyzing data in the data_processed folders. functions for running classifiers, EDA, ect.

:data:
contains raw data (light curves) from several surveys

:data_processed:
code in src outputs files that can be read into R. usually files with features and files with time,flux,error measurements for light curves

:db:
light curves are moved from data folder and put into databases where they can be manipulated. db holds these databases. most are created by code in src folder
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