PyFOSC

Please note: This program is under active development. The documentation may be inconsistent with the latest codes.

IRAF/PyRAF installation guide for Mac with Apple Silicon (M1/M2) can be found here.

PyFOSC is a pipeline toolbox for long-slit spectroscopy data reduction written in Python. It can be used for FOSC (Faint Object Spectrograph and Camera) data from Xinglong/Lijiang 2-meter telescopes.

BFOSC (Beijing-Faint Object Spectrograph and Camera) is an instrument of the 2.16-m Telescope in Xinglong Observatory, National Astronomical Observatories, Chinese Academy of Sciences (NAOC) (IAU code: 327, coordinates: 40°23′39″ N, 117°34′30″ E). For more information about BFOSC, please see http://www.xinglong-naoc.cn/html/en/gcyq/216/detail-18.html. The details of the Xinglong 2.16-m telescope and BFOSC are also reported in Fan et al. 2016 and Zhao et al. 2018.

YFOSC (Yunnan-Faint Object Spectrograph and Camera) is an instrument of the 2.4-m Telescope in Lijiang Observatory, Yunnan Observatories, Chinese Academy of Sciences (YNAO) (IAU code: O44, coordinates: 26°42′33.1″ N, 100°1′51.6″ E). For more information about YFOSC, please see http://wiki.gmg.org.cn/pages/viewpage.action?pageId=557106. The details of the Lijiang 2.4-m telescope and YFOSC are also reported in Wang et al. 2019.

1. Installation

1.1. Dependencies

IRAF
PyRAF
pandas
ccdproc

pandas is already included in the Anaconda distribution. To install ccdproc with conda, you can use:

conda install -c astropy ccdproc

or

conda install -c conda-forge ccdproc

This package depends on IRAF and PyRAF. You can download and install the IRAF Community Distribution.

1.2. Install the IRAF/PyRAF Community Distribution

For detailed description on how to install IRAF and PyRAF, visit:

• https://iraf-community.github.io/install.html
• https://iraf-community.github.io/x11iraf.html
• https://iraf-community.github.io/pyraf.html

If you are using a Mac with Apple Silicon (M1/M2), you can follow the instructions in this blog post to install IRAF/PyRAF.

1.3. Download PyFOSC and set environment variable for it.

You can use git clone to download this package.

git clone https://github.com/rudolffu/pyfosc.git

In order to run PyFOSC commands in the terminal, you need to add the path of PyFOSC and its sub-directory src to $PATH, by editing ~/.bashrc (Linux, e.g., Ubuntu) or ~/.bash_profile (Mac OS). An example of this can be:

export PATH=/Your/Path/to/pyfosc:$PATH
export PATH=/Your/Path/to/pyfosc/src:$PATH

2. Usage

2.1 Preparation

2.1.1 Run pyfosc_init to begin

First go to the working directory which contains FOSC spectroscopic data. Run pyfosc_init from the terminal:

pyfosc_init

2.1.2 Generate lists of files

As PyFOSC pipeline reduce data grouped by different types (bias, flat, object, etc), make sure you have lists of fits files as follows:

zero.list --------------- List of bias files (e.g. bias*.fits).
flat.list --------------- List of flat field files (e.g. flat*.fits).
objall.list ------------- List of 2d spectra images of all objects (science targets and standard stars).
lampall.list ------------ List of all 2d lamp spectra images.
flatnall.list ----------- List of 2d images that need zero correction (flat.list + lampall.list + objall.list).
specall.list ------------ List of all 2d spectra images (objall.list + lampall.list).

2.2 Running the pipeline

You can run pyfosc_run.sh from the terminal:

pyfosc_run.sh

Alternatively, you can run the scripts step by step, following the order as:

makezero_ccdp.py     # Combine zero(bias) frames.
ccdotz.py         # Do zero(bias), overscan correction and trimming.
makeflat2m_ccdp.py     # Combine flat fields.
makereflat2m.py   # Do (illumination) normalization and get perfect flat.
divideflat2m.py   # Do flat correction.
removecr_ccdp.py  # Remove cosmic rays in two-d images using ccdproc. 
doapall.py        # Extract spectra.
reidentlamp2m.py  # Reidentify lamp spectra with previously stored ones.
#Can use identlamp2m.py instead to identify lamp by oneself.
wavecal2m.py      # Do wavelength calibration, flux calibration.
telluric_base2m.py # Telluric correction and one-d spectra extraction.

Plot all final 1d spectra with:

plotonedsp.py

Move some intermediate files into INTMD directory:

mvintmd.sh

3. Credits

This software uses BSD 3-Clause License.

Copyright (c) 2019-2024, Yuming Fu
All rights reserved.

This software contains sources from third-party softwares.

The pyfosc$iraf_data/onedstds directory is from IRAF, and it contains standard calibration data for extinction and sensitivity calibration.

The removecr_ccdp.py script uses the ccdproc.cosmicray_lacosmic module to remove cosmic rays. The ccdproc.cosmicray_lacosmic module is based on the L.A.Cosmic algorithm for Laplacian Cosmic Ray Identification by Pieter G. van Dokkum (Yale) from http://www.astro.yale.edu/dokkum/lacosmic/. L.A.Cosmic detects cosmic rays of arbitrary shapes and sizes, and distinguishes between undersampled point sources and cosmic rays. If you use this program please refer to P. G. van Dokkum, 2001, PASP, 113, 1420.

Please see COPYRIGHT file and pyfosc$doc/LICENSES directory for detailed copyright information.

4. How to cite

Yuming Fu. (2024, April 13). PyFOSC: a pipeline toolbox for BFOSC/YFOSC long-slit spectroscopy data reduction (Version v1.1.0). Zenodo. https://doi.org/10.5281/zenodo.10967240

Cite the current version (v1.1.0) with bibtex:

@software{yuming_fu_2024_10967240,
  author       = {Yuming Fu},
  title        = {{PyFOSC: a pipeline toolbox for BFOSC/YFOSC long-slit spectroscopy data reduction}},
  month        = apr,
  year         = 2024,
  publisher    = {Zenodo},
  version      = {v1.1.0},
  doi          = {10.5281/zenodo.10967240},
  url          = {https://doi.org/10.5281/zenodo.10967240}
}