GAMSE
=====
<img src="https://github.com/wangleon/gamse/blob/master/docs/images/gamse.svg" width=250>
[![PyPI](https://img.shields.io/pypi/v/gamse.svg)](https://pypi.org/project/gamse/)
[![Read the Docs](https://img.shields.io/readthedocs/gamse.svg)](https://gamse.readthedocs.io/)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
`GAMSE` is a data reduction package for high-resolution échelle spectrographs.
It contains necessary subroutines in spectral reduction process, including
overscan correction, bias subtraction, order detection, flat-fielding
correction, background correction, and optimal extraction.
Dependencies
------------
`GAMSE` is based on Python 3.4 or later, and does not work in Python 2.x.
To use `GAMSE` the following packages are required:
* [Numpy](http://www.numpy.org/) 1.16.1 or later: A Python library for
multi-dimensional arrays and mathematics.
* [Scipy](https://www.scipy.org/) 0.17.0 or later: A Python library for
scientific computing.
* [Matplotlib](https://matplotlib.org/) 2.2.0 or later: To display and generate
output figures.
* [Astropy](http://www.astropy.org/) 3.1.1 or later: To read and write FITS
files and ASCII tables.
Installation
------------
To install `GAMSE` package with `pip`, simply use the following command:
```bash
sudo pip install gamse
```
Or alternatively, clone the whole repository with GIT:
```bash
git clone https://github.com/wangleon/gamse.git
```
Then run the setup script in the cloned directory:
```bash
sudo python3 setup.py install
```
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gamse-0.93.tar.gz (43个子文件)
gamse-0.93
PKG-INFO 244B
LICENSE 11KB
gamse
pipelines
common.py 12KB
feros.py 1KB
hires.py 31KB
levy.py 28KB
xinglong216hrs
common.py 22KB
flat.py 15KB
__init__.py 14KB
reduce_doublefiber.py 40KB
reduce_singlefiber.py 32KB
__init__.py 9KB
foces
common.py 49KB
flat.py 15KB
__init__.py 14KB
reduce_doublefiber.py 72KB
reduce_singlefiber.py 33KB
reduction.py 65KB
sarg.py 4KB
data
config
Levy.cfg 628B
linelist
thar.dat 31KB
cross_check.py 756B
thar-noao.dat 58KB
__init__.py 66B
echelle
trace.py 54KB
flat.py 77KB
__init__.py 151B
wlcalib.py 122KB
plot.py 3KB
imageproc.py 18KB
extract.py 21KB
background.py 49KB
utils
regression.py 6KB
obslog.py 14KB
regression2d.py 3KB
misc.py 3KB
__init__.py 137B
onedarray.py 8KB
config.py 2KB
setup.cfg 40B
setup.py 794B
README.md 2KB
scripts
gamse 733B
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