https://github.com/arendmoerman/d24_tools
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
-
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (7.7%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: arendMoerman
- Language: Python
- Default Branch: main
- Size: 1.32 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Data reduction pipeline for DESHIMA 2.0 data of the 2024 campaign
This Python package contains my data reduction and spectrum stacking for the DESHIMA 2.0 data.
Installation
Navigate to the directory containing this README, and type:
pip install .
In case you would like to edit the package to suit your own needs, install it in editable mode:
pip install -e .
Reduction of pswsc data
For pswsc data reduction, the flow is as follows: * despiking * nodding overshoot removal * atmosphere subtraction * grouping and averaging of ABBA cycles
This produces a single spectrum, which can be stacked together with other spectra. It can also be rebinned in case this is desired.
See example usage in examples/reduce_pswsc_example.py.
Reduction of daisy AB data
For daisy with AB chopping data, the procedure is as follows: * despiking * atmosphere subtraction * off-source residual removal
This is currently a work in progress. This repo will be updated when new updates come out.
Questions, remarks, and contact
Please see the CONTRIBUTING.md document for what to do when you want to contribute, report an issue/bug, etc.
Other inquiries, please send to:
A.Moerman (dash) 1 (at) tudelft (dot) nl
Owner
- Login: arendMoerman
- Kind: user
- Repositories: 3
- Profile: https://github.com/arendMoerman
GitHub Events
Total
- Watch event: 1
- Push event: 6
Last Year
- Watch event: 1
- Push event: 6
Dependencies
- numpy *