Spectroscopy reduction pipeline
Project description
SpecPiNk
Spectroscopic data reduction Pipeline for the Nordkuppel telescope
Functionality
This package is currently under development and shall provide a convenient and easily accessible way to process
spectroscopic data obtained with the LISA High luminosity spectrograph (Shelyak Instruments) on the 80cm telescope
situated in the northern dome (Nordkuppel) of the Institute for Astronomy's observatory in Vienna into a science-ready form.
The processing shall include the application of image correction with Bias-, Dark- and Flat-Frames and the wavelength
calibration.
User stories
As Alice, a Bachelor student with more interest in science than in programming, I want to check the produced science
frames of my self developed data reduction against the results of this (hopefully) very well crafted python package,
so I can hand in my lab report with some more confidence.
As Bob, who just found out about a niche case with transitional phenomena where this small telescope can actually be of
use for some serious science, I do not want to waste my time getting to know the peculiarities of the spectrograph
configuration, I only want my well defined images out of some sort of mostly pre-configured black box (this package).
However, I want some control over the final data reduction process, so I need both the correctional images (Bias, Dark,
Flat) and the science frames.
As Charly, who works on the same transitional phenoma, I do not want to just stare at the wall of the Nordkuppel while
an exposure is being made, I want some preliminary results, the details of the data reduction do not really
matter for now, I just want to use this package to get some processed science frames very fast. After all, I need to be faster than Bob.
As Dagobert, I am not in a particular rush, for I am only an amateur astronomer interested in spectroscopy. A student
friend of mine has provided me with observational data he recently obtained, but has not really explained to me how I
get something useful out of this. I want this package to produce nice science frames without having to learn all about
the mechanics of data reduction. Maybe the example given in the documentation is some sort of standard example?
Pseudo code example (minimal)
# simply importing the package
import specpink
# optional input settings file
input_file = ".\input"
# specify input directories
dark_dir = ".\Darks"
bias_dir = ".\Bias"
flat_dir = ".\Flats"
calib_dir = ".\Calibs"
science_dir = ".\Science"
# specify output directories (maybe differently structured)
final_dir = ".\Finals" #
specpink.dothemagic(directories)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file specpink-0.1.0.tar.gz.
File metadata
- Download URL: specpink-0.1.0.tar.gz
- Upload date:
- Size: 9.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.10.16
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
67013d00d383556ab32cbffb284cf179e591467e7d4f8299aaf26eee2b54ad47
|
|
| MD5 |
21ad78a823877a1c4e9996ab71331c16
|
|
| BLAKE2b-256 |
622adaedb449b39f354cd85537451aa96e85d009473f4cfd2e99830fad848886
|
File details
Details for the file specpink-0.1.0-py3-none-any.whl.
File metadata
- Download URL: specpink-0.1.0-py3-none-any.whl
- Upload date:
- Size: 9.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.10.16
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c1fc81545aba71233ad1f5f37a9469fc047ca2dcfea42e0a9de0b6b8417302ba
|
|
| MD5 |
2b618ece4961f6d1ad877681bdcfe796
|
|
| BLAKE2b-256 |
6c798f7eaa0d11a18aee9ed55cd42b2a4dfc7d811cc717a84475054884819e83
|