laspec 2021.1122.0

Modules for LAMOST spectra.

laspec

A toolkit for LAMOST spectra.

citation

If you make use of this package in your research, please cite the paper below:

• Self-consistent Stellar Radial Velocities from LAMOST Medium-Resolution Survey (MRS) DR7
• Deriving the Stellar Labels of LAMOST Spectra with the Stellar LAbel Machine (SLAM)

bibtex:

@ARTICLE{2021arXiv210511624Z,
       author = {{Zhang}, Bo and {Li}, Jiao and {Yang}, Fan and {Xiong}, Jian-Ping and {Fu}, Jian-Ning and {Liu}, Chao and {Tian}, Hao and {Li}, Yin-Bi and {Wang}, Jia-Xin and {Liang}, Cai-Xia and {Zhou}, Yu-Tao and {Zong}, Wei-kai and {Yang}, Cheng-Qun and {Liu}, Nian and {Hou}, Yong-Hui},
        title = "{Self-consistent Stellar Radial Velocities from LAMOST Medium-Resolution Survey (MRS) DR7}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics},
         year = 2021,
        month = may,
          eid = {arXiv:2105.11624},
        pages = {arXiv:2105.11624},
archivePrefix = {arXiv},
       eprint = {2105.11624},
 primaryClass = {astro-ph.SR},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv210511624Z},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2020ApJS..246....9Z,
       author = {{Zhang}, Bo and {Liu}, Chao and {Deng}, Li-Cai},
        title = "{Deriving the Stellar Labels of LAMOST Spectra with the Stellar LAbel Machine (SLAM)}",
      journal = {\apjs},
     keywords = {Astronomical methods, Astronomy data analysis, Bayesian statistics, Stellar abundances, Chemical abundances, Fundamental parameters of stars, Catalogs, Surveys, 1043, 1858, 1900, 1577, 224, 555, 205, 1671, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics},
         year = 2020,
        month = jan,
       volume = {246},
       number = {1},
          eid = {9},
        pages = {9},
          doi = {10.3847/1538-4365/ab55ef},
archivePrefix = {arXiv},
       eprint = {1908.08677},
 primaryClass = {astro-ph.SR},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020ApJS..246....9Z},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

author

Bo Zhang, [e-mail]

home page

• https://github.com/hypergravity/laspec
• https://pypi.org/project/laspec/

install

• for the latest stable version: pip install -U laspec
• for the latest github version: pip install -U git+git://github.com/hypergravity/laspec

doumentation

A documentation on ReadTheDoc will be updated soon ...

Link to the doc: https://laspec.readthedocs.io/en/latest/

module structure

• binning
  module for rebinning spectra
  • rebin(wave, flux, flux_err, mask): rebin spectra
• ccf
  module for cross correlation function
  • sine_bell: a sine bell function
  • wxcorr: weigted cross-correlation
  • wxcorr_cost: negative CCF function
  • wxcorr_spec: weigted cross-correlation of two spectra
  • wxcorr_rvgrid: weighted cross correlation given an RV grid
  • wxcorr_cost_binary: negative CCF function
  • wxcorr_spec_binary: weigted cross-correlation of two spectra
  • wxcorr_rvgrid_binary: weighted cross correlation given an RV grid
  • RVM Radial Velocity Machine
    • measure: measure the RV of single stars
    • measure_binary: measure the RV of binary systems
• convolution
  module for spectral Gaussian convolution
  • conv_spec: capable to tackle arbitrary R_hi and R_lo but relatively slow
• interpolation
  interpolation, but slow, please do not use.
  • Interp1q: use numpy.interp instead
• lamost
  module for LAMOST spectra and files
  • lamost_filepath(planid, mjd, spid, fiberid)
  • lamost_filepath_med(planid, mjd, spid, fiberid)
  • sdss_filepath(plate, mjd, fiberid)
• mrs
  MRS module
  • MrsSpec: MRS spectrum (B / R)
  • MrsEpoch: MRS epoch spectrum (B + R)
  • MrsFits(astropy.io.fits.HDUList): MRS fits reader
  • MrsSource(numpy.ndarray): MRS source constructor
• line_indices
  module to measure spectral line index (EW)
  • measure_line_index: measure line index (EW)
• normalization
  module to normalize spectra
  • normalize_spectrum_spline: a Python version of Chao's method (recommended)
  • normalize_spectrum_poly: polynomial normalization
  • normalize_spectrum_general： a unified wrapper of spline and poly
  • NOTE: bad pixels (e.g., cosmic rays) should be properly removed before normallization
• qconv
  quick convolution, designed for two cases:
  • conv_spec_Gaussian(wave, flux, R_hi=3e5, R_lo=2000): scalar resolution to scalar resolution instrumental broadening
  • conv_spec_Rotation(wave, flux, vsini=100., epsilon=0.6): stellar rotation broadening
• read_spectrum
  module to read LAMOST/SDSS spectra
  • read_spectrum(fp): read LAMOST low-res spectra
  • read_lamostms(fp): read LAMOST medium-res spcetra
• spec
  modules for operations on general spectra (deprecated)
  • Spec: spec class
• wavelength
  module to convert wavelength between air and vacuum
  • wave_log10: log10 wavelength grid
  • vac2air: convert wavelength from vacuum to air
  • air2vac: convert wavelength from air to vacuum

acknowledgements

...