Analysis#

class vampires_dpp.analysis.Moffat(x0, y0, gammax, gammay, theta, alpha, amplitude, background, **kwargs)#

static evaluate(x, y, x0, y0, gammax, gammay, theta, alpha, amplitude, background)#: Evaluate the model on some input variables.

static fit_deriv(x, y, x0, y0, gammax, gammay, theta, alpha, amplitude, background)#

param_names = ('x0', 'y0', 'gammax', 'gammay', 'theta', 'alpha', 'amplitude', 'background')#

Names of the parameters that describe models of this type.

The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.

When defining a custom model class the value of this attribute is automatically set by the ~astropy.modeling.Parameter attributes defined in the class body.

vampires_dpp.analysis.find_norm_peak(image, center, window_size=20, phot_rad=8, oversamp=4)#

usage: peak = find_peak(image, xc, yc, boxsize) finds the subpixel peak of an image

image: an image of a point source for which we would like to find the peak xc, yc: approximate coordinate of the point source boxsize: region in which most of the flux is contained (typically 20) oversamp: how many times to oversample the image in the FFT interpolation in order to find the peak

Return type:: float
Returns:: peak of the oversampled image

Marcos van Dam, October 2022, translated from IDL code of the same name

Analysis

Contents

Analysis#