PyKinematicalBroadening 0.0.5

Kinematical broadening in velocity space (km/s)

PyKinematicalBroadening

email: [e-mail], [e-mail]

© Copyright ®

J.G. - Jean Gomes

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Description

RESUME: PyKinematicalBroadening is an Extragalactic Kinematics repository for applying a kernel in velocity space to models in order to obtain the respective broadened model. This is a python code that performs kinematical broadening of a spectrum by applying a kernel in velocity space to a model, and obtaining the respective broadened model. The code defines the function broadening, which performs the convolution with a Gaussian kernel. The kernel is generated using a certain number of points, which can be set with the Ni_Gauss parameter. The code then reads in a test spectrum from a file, interpolates it onto a set of equally spaced wavelength values, and then plots the original and broadened spectra for different velocity dispersions.

In detail, the GaussianConvolution function convolves a given input spectrum fluxes_o defined at wavelengths lambda_o with a Gaussian kernel of width vd_sigma and mean velocity vc0_gals. The kernel is defined with Ni_Gauss points, which should be at least as large as vd_sigma. The output spectrum is defined at wavelengths lambda_s, and is returned as fluxes_s. The fill_val parameter defines the value to use for regions outside of the original wavelength range, and verbosity controls the level of detail of console output.

The main code reads in a test spectrum from a file and interpolates it onto a set of equally spaced wavelength values. It then loops over different velocity dispersions and calls 'broadening' for each one, broadening the spectrum and plotting the results.

You can easily install PyKinematicalBroadening by using pip - PyPI - The Python Package Index:

pip install PyKinematicalBroadening

or by using a generated conda repository https://anaconda.org/neutrinomuon/PyKinematicalBroadening:

conda install -c neutrinomuon PyKinematicalBroadening

OBS.: Linux, OS-X ad Windows pre-compilations available in conda.

You can also clone the repository and install by yourself in your machine:

git clone https://github.com/neutrinomuon/PyKinematicalBroadening
python setup.py install

Example

Example of the test_spectrum test_spectrum.spec successively broadened by different velocity dispersions in [km/s]. The code is not optimized for cpu speed, but it shows the principle of how it works.

Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND 4.0)

Creative Commons Attribution-NonCommercial-NoDerivs (CC-BY-NC-ND)