analysis.fisher module

This module contains functions necessary to produce statistical results of the fisher formalism from a given galaxy.

class analysis.fisher.Fisher(g_parameters, image_renderer, snr, var_noise=None)

Bases: object

Produce fisher object (containing fisher analysis) for a given set of galaxy parameters.

Given a galaxy image and the appropiate parameters that describe it, (in the form of analysis.galfun.GParameters object) will produce a fisher object that contains the analysis of it using the Fisher Formalism.

NOTE: The matrices are in dictionary form, use the function matrixToNumpyArray() to change them to a matrix that is ordered according to param_names.

Args:

g_parameters(GParameters): String point to the directory

specified by the user.

image_renderer(ImageRenderer): Object used to render image of galaxy. snr(float): Value S/N ratio to use in the analysis.

Attributes:

image_renderer_partials(analysis.galfun.ImageRenderer): Object used to render images of partial derivatives. image(Galsim.Image): Dictionary whose keys are the ids of each of the

galaxies specified in galaxies.csv, and that map to another dictionary that can be taken in by analysis.galfun.getGalaxyModel()

var_noise(float): Variance of noise of given S/N . steps(dict): Dictionary containing the step size used when

calculating partial derivatives.

param_names(list): A list containing the keys of fit_params

in a desirable order.

num_params(int): Number of parameters specified for the galaxy. num_galaxies(int): Number of galaxies specified. derivatives_images(dict): Dictionary containing np.array(s) that represent the

derivative of the galaxy(ies) with respect to each parameter.

second_derivatives_images(dict): Dictionary containing np.array(s) that represent the

second derivatives of the galaxy(ies) with respect to its parameters.

fisher_matrix_images(dict): Dictionary containing np.array(s) that represent the

fisher matrix images of the galaxy(ies) with respect to its parameters.

fisher_matrix(dict): Dictionary containing fisher matrix elements. covariance_matrix(dict): Dictionary containing covariance matrix elements. correlation_matrix(dict): Dictionary containing correlation matrix elements. bias_matrix_images(dict): Dictionary containing bias matrix image elements. bias_matrix(dict): Dictionary containing bias matrix elements. bias_images(dict): Dictionary containing bias images elements. biases(dict): Dictionary containing biases

biasImages()

Construct the bias of each parameter per pixel.

biasMatrix()

Return bias matrix from the images of the bias matrix

biasMatrixImages()

Produce images of each element of the bias matrix.

correlationMatrix()

Calculate correlation matrix from the covariance matrix.

covarianceMatrix()

Calculate the covariance matrix by inverting fisher matrix.

derivativesImages()

Return images of the partial derivatives of the galaxy.

The partial differentiation includes each of the different parameters that describe the galaxy.

fisherConditionNumber()

The condition number will give a sense of how singular the matrix tends to be.

fisherMatrix()

Calculate the actual values of the fisher matrix.

fisherMatrixImages()

Produce images of fisher matrix).

getBiases()

Return the value of the bias of each parameter in vector form.

matrixToNumpyArray(matrix)

Convert matrix dictionary to a numpy array.

numpyArrayToMatrix(array)

Convert numpy array to matrix dictionary.

secondDerivativesImages()

Return the images for the second derivatives of the given galaxy.

analysis.fisher.getSNR(img, var_noise)