Gauss2DPDF

class gammapy.image.models.Gauss2DPDF(sigma=1)[source]

Bases: object

2D symmetric Gaussian PDF.

Reference: http://en.wikipedia.org/wiki/Multivariate_normal_distribution#Bivariate_case

Parameters:

sigma : float

Gaussian width.

Attributes Summary

amplitude PDF amplitude at the center (float)

Methods Summary

__call__(x[, y]) dp / (dx dy) at position (x, y)
containment_fraction(theta) Containment fraction.
containment_radius(containment_fraction) Containment angle for a given containment fraction.
dpdtheta2(theta2) dp / dtheta2 at position theta2 = theta ^ 2
gauss_convolve(sigma) Convolve with another Gaussian 2D PDF.

Attributes Documentation

amplitude

PDF amplitude at the center (float)

Methods Documentation

__call__(x, y=0)[source]

dp / (dx dy) at position (x, y)

Parameters:

x : ndarray

x coordinate

y : ndarray, optional

y coordinate
Returns:

dpdxdy : ndarray

dp / (dx dy)
containment_fraction(theta)[source]

Containment fraction.

Parameters:

theta : ndarray

Offset
Returns:

containment_fraction : ndarray

Containment fraction
containment_radius(containment_fraction)[source]

Containment angle for a given containment fraction.

Parameters:

containment_fraction : ndarray

Containment fraction
Returns:

containment_radius : ndarray

Containment radius
dpdtheta2(theta2)[source]

dp / dtheta2 at position theta2 = theta ^ 2

Parameters:

theta2 : ndarray

Offset squared
Returns:

dpdtheta2 : ndarray

dp / dtheta2
gauss_convolve(sigma)[source]

Convolve with another Gaussian 2D PDF.

Parameters:

sigma : ndarray or float

Gaussian width of the new Gaussian 2D PDF to covolve with.
Returns:

gauss_convolve : Gauss2DPDF

Convolution of both Gaussians.