Modules for LAMOST spectra.
Project description
laspec
A toolkit for LAMOST spectra.
citation
If you make use of this package in your research, please cite the paper below:
bibtex:
@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, bozhang@nao.cas.cn
home page
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
...
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