enyo.util.lineprofiles module¶

Implements a set of line profile parameterizations.

#.. _pypi https://pypi.org/project/sdss-mangadap/

class enyo.util.lineprofiles.FFTGaussianLSF(p=None, dx=None, pixel=True)[source]¶

Bases: enyo.util.lineprofiles.GaussianLSF

Define a Gaussian line profile by first constructing the analytic FFT of the profile and then returning the inverse real FFT. See ppxf_util.emline by M. Cappellari. The sampling must be uniform in \(x\).

Parameters:	p (array-like, optional) – Input parameters ordered as the total integral of the profile, the profile center, and the profile standard deviation. Assumed to be (1.0, 0.0, 1.0) by default. dx (`float`, optional) – Sampling width. Default is 1. pixel (`bool`, optional) – Flag to produce profile integrated over the sampling width.

p¶

Most recently used parameters

Type:	numpy.ndarray

dx¶

Assumed sampling.

Type:	`float`

pixel¶

Flag to produce profile integrated over the sampling width.

Type:	`bool`

sample(x)[source]¶

Sample the profile.

Warning

Does not check if the provided \(x\) values are sampled at dx.

Parameters:	x (array-like) – Independent variable.

class enyo.util.lineprofiles.GaussianLSF(p=None)[source]¶

Bases: object

Define a Gaussian line profile, sampled over the width of the sampling step, parameterized by its integral (\(F\)), center (\(\mu\)), and standard deviation (\(\sigma\)). I.e:

\[\mathcal{N}(x|f,\mu,\sigma) = \frac{f}{\sqrt{2\pi}\sigma} \exp\left(\frac{-\Delta^2}{2\sigma^2}\right)\]

where \(\Delta = x-\mu\). The coordinate vector \(x\) does not need to be uniformly sampled.

Parameters:	p (array-like, optional) – Input parameters ordered as the total integral of the profile, the profile center, and the profile standard deviation. Assumed to be (1.0, 0.0, 1.0) by default.

p¶

Most recently used parameters

Type:	numpy.ndarray

static npar()[source]¶

parameters_from_moments(mom0, mom1, mom2)[source]¶: Provided the 0th, 1st, and 2nd moments, produce a set of parameters for the profile.

sample(x)[source]¶

Sample the profile.

Parameters:	x (array-like) – Independent variable.

set_par(p)[source]¶

Set the internal parameters to the provided set.

Parameters:	p (array-like) – LSF parameters.
Raises:	`ValueError` – Raised if the provided parameter vector is not 3 elements long.

class enyo.util.lineprofiles.IntegratedGaussianLSF(p=None, dx=None)[source]¶

Bases: enyo.util.lineprofiles.GaussianLSF

Define a Gaussian line profile, integrated over the width of the sampling step, parameterized by its integral (\(F\)), center (\(\mu\)), and standard deviation (\(\sigma\)). I.e:

\[\mathcal{N}(x|F,\mu,\sigma) = \frac{F}{2} \left[ {\rm erf}\left(\frac{\Delta+\delta_x/2}{\sqrt{2}\sigma}\right) - {\rm erf}\left(\frac{\Delta-\delta_x/2}{\sqrt{2}\sigma}\right)\right]\]

where \({\rm erf}(x)\) is the error function, \(\Delta = x-\mu\), and \(\delta_x\) is the sampling step. The sampling must be uniform in \(x\).

Parameters:	p (array-like, optional) – Input parameters ordered as the total integral of the profile, the profile center, and the profile standard deviation. Assumed to be (1.0, 0.0, 1.0) by default. dx (`float`, optional) – Sampling width. Default is 1.

p¶

Most recently used parameters

Type:	numpy.ndarray

dx¶

Assumed sampling.

Type:	`float`

sample(x)[source]¶

Sample the profile.

Warning

Does not check if the provided \(x\) values are sampled at dx.

Parameters:	x (array-like) – Independent variable.