tlpipe.utils.multiscale

Functions

MAD(a)	Median absolute deviation divides 0.6745.
convolve(a, phi)	Convolve a along each axis sequentially by phi.
convolve1d(input, weights[, axis, output, ...])	Calculate a one-dimensional convolution along the given axis.
median_filter(input[, size, footprint, ...])	Calculates a multidimensional median filter.
median_wavelet_detrend(a[, level, scale, ...])	Return the detrended component (i.e., smooth component being subtracted) of the median-wavelet transfrom.
median_wavelet_smooth(a[, level, scale, ...])	Return the smooth component of the median-wavelet transform.
median_wavelet_transform(a[, level, scale, ...])	Median-wavelet transfrom.
multiscale_median_detrend(a[, level, scale])	Return the detrended component (i.e., smooth component being subtracted) of the multiscale median transfrom.
multiscale_median_flag(a[, level, scale, ...])
multiscale_median_smooth(a[, level, scale])	Return the smooth component of the multiscale median transform.
multiscale_median_transform(a[, level, ...])	Multiscale median transform.
starlet_detrend(a[, level, phi])	Return the detrended component (i.e., smooth component being subtracted) of the first generation starlet transfrom.
starlet_smooth(a[, level, phi])	Return the smooth component of the first generation starlet transform.
starlet_transform(a[, level, gen2, ...])	Computes the starlet transform (i.e.
up_sampling(a)	Up-sampling an array by interleaving it with zero values.