Corrspecengine

Corrspecengine

Purpose

This function is the primary calculational engine for the function corrspec. It calculates the correlation maps and related matrices corrected for previously determined pure variables.

Synopsis

matrix = corrspecengine(data_x,data_y,purvar_index,offset, matrix_options);

Description

Calculates the matrices (weigh matrix, dispersion matrix and max matrix) needed for corrspec corrected for previously determined pure variables.

Inputs

• data_x : (2-way array class "double" or "dataset") x-matrix for dispersion matrix.

• data_y : (2-way array class "double" or "dataset") y-matrix for dispersion matrix.

• purvar_index : indices of maximum value in purity_values, i.e. the index of the pure variables. First column for x data, second column for y data. Empty when no pure variables have been chosen yet. When base_x is a single number n, the program calculates the first n pure purity_indices.

• offset : noise correction factor. One element defines offset for both x and y, two elements separately for x and y.

• max : if not given, only weight matrix will be calculated, otherwise it contains 2 elements: the options the dispersion_matrix and the max_matrix:

• 1: standardized, offset corrected

• 2: length sqrt(nrows), offset corrected

• 3: purity about mean, offset corrected

• 4: purity about origin, offset corrected

• 5: asynchronous, offset corrected

Outputs

• matrix : cell array with either one or three matrices, with size [ncols_y ncols_x] (ncols_y represents number of spectra in y, etc.).

• matrix{1}: weight_matrix, matrix used to correct for previously selected pure variables.

• matrix{2}: dispersion_matrix, matrix of interest, generally correlation matrix, corrected for previously selected pure variables.

• matrix{3}: max_matrix, matrix from which pure variables are chosen, generally a co-purity matrix corrected for previously selected pure variables.

See Also

corrspec, dispmat