Progress Report
Simón Torres R.
Data Analyst
[email protected]
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La Serena Software Team
◦ Bruno Quint
◦ César Briceño
◦ Simón Torres
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See final slide for other people involved
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Goodman HTS Pipeline Overview
◦ We have something that works but still requires
some development
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Other SOAR Data Reduction Pipelines
◦ Just some info since I’m not personally involved
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Python-based tools to:
◦ Reduce Goodman’s raw data
 Imaging
 Spectroscopy
◦ Perform Spectroscopic Reduction
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Identification
Trace
Extract
Wavelength Calibration
(future plans) Flux Calibration
Full process is split in two sub-processes
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Very well documented software
Most processes transparent to the user
◦ Different levels of debug available
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Easy code maintenance
◦ We’ll see that but we keep that in mind as we work
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Group development in mind
◦ Keep in mind new developers
We we’ll need beta testers!
Users/Community input is required
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We use Python2.7 (Check compat. w/P3.5)
General Coding Standards
◦ PEP8 – Style Guide
◦ PEP257 – Docstrings Convention (in-code
documentation) – Google Style
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GIT + GitHub
PyCharm Development Platform
Open Source
Multiplatform Compatibility
“Modular Design”
◦ In theory could be used as a library
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Centos 7 64bits
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32GB RAM
i7 Processor
Solid State Drive
6TB Total Space, RAID 6
No benchmarking yet but…
◦ CCD Reduction: 286 Images, 98 Sci/Comp
 ~ 7:30 Minutes
◦ Spectroscopic Reduction 69 Science Images
 ~ 5:00 Minutes
 Including user input
 Only one spectroscopic configuration 400m2
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In-Code Documentation – Docstrings
◦ Updated version of ccd reduction is incomplete
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GitHub Hosted Wiki
◦ Not extensive but precise
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User Documentation
◦ Requires more work but working on it
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Works up to Wavelength Calibration
◦ Not ready for a release
◦ Important modules missing (Flux Calibration)
◦ Other important Features missing
 Automatic Wavelength Calibration
 User documentation
 Cross platform compatible GUI (Qt4/5?)
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Schedule
◦ Internal testing and quality controls
◦ June Start Beta Testing (ends August)
◦ First 1.0 Release by the end of year
 Complete and stable
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Developing a pipeline for an instrument with:
◦ “Infinite possible configurations”
◦ Two different cameras
 Headers and Keywords differ from each other
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Automatic Wavelength Solution
◦ There are some non-linearities in the data
 Maybe a characterization of them might help
◦ Graphical Interface to find w/solution Interactively
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Non-linear w/solution FITS documentation
◦ It was easier to linearize the spectrum
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https://github.com/simontorres/goodman/tree/development
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https://youtu.be/Ly1Mnx4MSy4
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Add Automatic Wavelength Calibration
Add Flux Calibration Module
Improve Multi-Target Capability
MOS mode
Create a Dedicated GUI
We will provide Data Reduction Computers
◦ Three i7 32GB RAM 6TB RAID 6 Storage Computers
◦ Pipeline will still be publicly available
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Instrument
Developer
Language
Status
SIFS
Luciano Fraga
Python
Development
STELES
Eder Martioli
C++/Python
Development*
Goodman
Simón Torres
Python
Development
SOI
Luciano Fraga
PyRAF
Production
SAMI
Luciano Fraga
PyRAF
Production
SAM-FP
Bruno Quint
Python
Production
SPARTAN
Patrick O’Brien
C++/Others
Development**
* Based on OPERA by CFHT. Eder is part of OPERA dev. team.
** THELI, Was developed by Mischa Schirmer
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