cddm._core_nb

Low level numba functions

Module Contents

cddm._core_nb.abs2(x)

Absolute square of data

cddm._core_nb.mean(a, b)

Man value

cddm._core_nb.choose(a, b)

Chooses data randomly

cddm._core_nb.convolve(a, out)

Convolves input array with kernel [0.25,0.5,0.25]

cddm._core_nb.interpolate(x_new, x, y, out)

Linear interpolation

cddm._core_nb.log_interpolate(x_new, x, y, out=None)

Linear interpolation in semilogx space.

cddm._core_nb.median(array, out=None)

Performs median filter of complex or float data.

cddm._core_nb.weighted_sum(x, y, weight, out=None)

Performs weighted sum of two data sets, given the weight data. Weight must be normalized between 0 and 1. Performs: x * weight + (1.- weight) * y

cddm._core_nb.decreasing(array, out)

Performs decreasing filter. Each next element must be smaller or equal

cddm._core_nb.increasing(array, out)

Performs increasing filter. Each next element must be greater or equal

cddm._core_nb.weight_from_g(g, delta)

Computes weight for weighted normalization from normalized and scaled correlation function

cddm._core_nb.weight_prime_from_g(g, delta, b1, b2)

Computes weight for weighted normalization from normalized and scaled correlation function

cddm._core_nb.sigma_weighted(w, g, delta)

Computes standard deviation of the weighted normalization.