Skip to content

An automated pipeline for the 2.16m BFOSC data reduction.

License

Notifications You must be signed in to change notification settings

lidihei/pyexspec

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

76 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

pyexspec

An automated pipeline for reducing 2D spectra of instruments and is a modified version of bfosc

Authors:

  • Jiao Li
  • Zhang Bo

Installation

  1. install songcn package
    • pip install -U git+git://github.com/lidihei/songcn
    • pip show songcn should be at least 0.0.9
    • or install 'songcn' package by
    • git clone https://github.com/lidihei/songcn.git
    • bash install.sh
  2. install pyexspec package
    • git clone https://github.com/lidihei/pyexspec.git
    • cd pyexspec
    • pip install .

Extracting spectrum of E9G10 of Xinglong 216cm

- cd pyexspec/bfoscE9G10/gui
- python app.py
    • if extract BFOSC the rot90 must be selected

    • bfosc orders reference

yfosc E9G10

Manually callibrate wavelength

  • cd wvcalib
  • $python wvclib_app.py
    • when set value of emission line, you shoud press "Enter/Return" keyboard after input the value into the table.
    • Finding the emission line automatically:
      • BFOSC E9G10
        • npix_chunck = 8; CCF_Kernel Width = 1.5; num_sigma_clip = 3
        • Fitting Function: Poly2DFitter; Parameter : deg(X) = 4; deg(Y) = 6
      • YFOSC E9G10
        • npix_chunck = 5; CCF_Kernel Width = 1.5; num_sigma_clip = 3
        • Fitting Function: Poly2DFitter; Parameter : deg(X) = 4; deg(Y) = 6

About

An automated pipeline for the 2.16m BFOSC data reduction.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 94.4%
  • Python 5.6%