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A toolkit for LAMOST spectra.

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{2021ApJS..256...14Z,
       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}, Weikai and {Yang}, Cheng-Qun and {Liu}, Nian and {Hou}, Yong-Hui},
        title = "{Self-consistent Stellar Radial Velocities from LAMOST Medium-resolution Survey DR7}",
      journal = {\apjs},
     keywords = {Radial velocity, Surveys, Astronomy data analysis, Astronomy data reduction, Spectroscopic binary stars, Radio spectroscopy, Spectroscopy, Catalogs, Sky surveys, Astrostatistics, Robust regression, 1332, 1671, 1858, 1861, 1557, 1359, 1558, 205, 1464, 1882, 1949, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics},
         year = 2021,
        month = sep,
       volume = {256},
       number = {1},
          eid = {14},
        pages = {14},
          doi = {10.3847/1538-4365/ac0834},
archivePrefix = {arXiv},
       eprint = {2105.11624},
 primaryClass = {astro-ph.SR},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021ApJS..256...14Z},
      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}
}

Bo Zhang, [email protected]

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

git clone https://github.com/hypergravity/laspec.git
cd laspec
sh install.sh

A documentation on ReadTheDoc will be updated soon ...

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

• 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

...