Metadata-Version: 2.1
Name: eniric
Version: 1.0rc3
Summary: Eniric: Extended NIR Information Content
Home-page: https://github.com/jason-neal/eniric.git
Author: Jason Neal
Author-email: jason.neal@astro.up.pt
License: MIT Licence
Download-URL: https://github.com/jason-neal/eniric.git
Description: # [ENIRIC](https://github.com/jason-neal/eniric) - Extended Near InfraRed Information Content
        
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        `Eniric` is a Python 3 software to compute the theoretical Radial Velocity (RV) precision of stellar spectra.
        `Eniric` is an overhaul and extension to the code used in [Figueria et al. 2016](http://dx.doi.org/10.1051/0004-6361/201526900) to analysis the precision of M-dwarf stars.
        Extending the performance and usability, it is able to be used on any synthetic spectra from the [PHOENIX-ACES](http://phoenix.astro.physik.uni-goettingen.de) and [BT-Settl](https://phoenix.ens-lyon.fr/Grids/BT-Settl/CIFIST2011_2015/FITS/) (CIFIST2001-2015) libraries.
        
        Checkout the documentation on [Read the Docs](https://eniric.readthedocs.io/en/latest/)!
        
        ## Features:
        `Eniric` contains a number of features to transform and prepare the spectra (observed and synthetic).
        
        - [Spectral broadening](https://eniric.readthedocs.io/en/latest/broadening.html)
        
             Allows for Rotational and Instrumental broadening of synthetic spectra given a rotation speed ``vsini`` and resolution ``R``.
        
        - [Atmospheric transmission masking](https://eniric.readthedocs.io/en/latest/telluric_corection.html)
        
           Analyzing the RV precision attainable under the different masking conditions presented in `Figueira et al. 2016`_.
        
           The three conditions specifically treated are:
           * No contamination or treatment of atmospheric transmission
           * Masking all regions affected by atmospheric absorption of a given depth % over the course of the year.
           * Assuming perfect telluric correction in which the variance of the measured flux is impacted.
        
        - Relative RV precision
        
          The RV precision can be calculated relative to a specified SNR per pixel in the center of a spectroscopic band.
            The default as used in the Figueira et al. 2016 is a SNR of 100 at the center of the J-band.
        
        - Spectral Resampling
        
           Allows for resampling of synthetic spectra to ``N`` pixels per FWHM.
        
        - SNR normalization.
        
           Normalize spectral flux to a defined SNR level.
        
        - Band selection
        
          Analysis splitable into individual photometric bands ``Z``\ , ``Y``\ , ``J``\ , ``H``\ , ``K``.
          User definable.
        
        - Theoretical RV precision
        
           Compute spectral RV precision and spectral quality.
        
        - Incremental quality & precision
        
            Determine the RV precision and spectral quality on narrow wavelength slices across the entire spectrum, similar to that present in Figure 1 of `Artigau et al. 2018 <http://adsabs.harvard.edu/abs/2018AJ....155..198A>`_.
        
        * Analyse relative precision of synthetic libraries
        
            The RV precision of are present relative to a specified SNR per pixel in the center of a photometric band.
            The default as used in `Figueira et al. 2016`_ is a SNR of 100 at the center of the J-band.
            - Available through [Starfish]'s() grid_tools.
               - [PHOENIX-ACES](http://phoenix.astro.physik.uni-goettingen.de)
               - [BT-Settl](https://phoenix.ens-lyon.fr/Grids/BT-Settl/CIFIST2011_2015/FITS/)
        
        
        ## Contents
        
        - [Installation](https://eniric.readthedocs.io/en/latest/installation.html)
        - [Configuration](https://eniric.readthedocs.io/en/latest/configuration.html)
        - [Basic Usage](https://eniric.readthedocs.io/en/latest/basic_usage.html)
        - [Broadening](https://eniric.readthedocs.io/en/latest/broadening.html)
        - [Atmospheric Transmission](https://eniric.readthedocs.io/en/latest/telluric_corection.html)
        - [Normalization](https://eniric.readthedocs.io/en/latest/normalization.html)
        - [Resampling](https://eniric.readthedocs.io/en/latest/resampling.html)
        - [Theoretical Precision of Synthetic Spectra](https://eniric.readthedocs.io/en/latest/theoretical_precision.html)
        - [Scripts](https://eniric.readthedocs.io/en/latest/scripts.html)
        - [Example Notebooks](https://eniric.readthedocs.io/en/latest/examples.html)
        - [Utilities](https://eniric.readthedocs.io/en/latest/utilities.html)
        
        
        ## Background
        The origin of this code was used in [Figueira et al. 2016](http://dx.doi.org/10.1051/0004-6361/201526900).
        
            P. Figueira, V. Zh. Adibekyan, M. Oshagh, J. J. Neal, B. Rojas-Ayala, C. Lovis, C. Melo, F. Pepe, N. C. Santos, M. Tsantaki, 2016,
            Radial velocity information content of M dwarf spectra in the near-infrared,
            Astronomy and Astrophysics, 586, A101
        
        It had a number of efficiency issues with convolution which were improved upon
        
        To reproduce the updated results for [Figueira et al. 2016](http://dx.doi.org/10.1051/0004-6361/201526900) run
        
            phoenix_precision.py -t 3900 3500 2800 2600 -l 4.5 -m 0.5 -r 60000 80000 100000 -v 1.0 5.0 10.0 -b Z Y J H K
        
        after installation and configuration.
        
Keywords: Astronomy,Radial velocity,Near-infrared spectroscopy,M-dwarfs
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Natural Language :: English
Classifier: Operating System :: Unix
Classifier: Operating System :: Microsoft :: Windows
Description-Content-Type: text/markdown
Provides-Extra: ci
Provides-Extra: dev
Provides-Extra: test
Provides-Extra: docs
