golconda.decomposer module

class golconda.decomposer.WaveletDecomposer(num_scales: int = 3)[source]

Bases: object

Methods

`decompose`(input_map[, num_scales, ...])	Perform wavelet decomposition based on the chosen filter type for the given image.
`decompose_with_starlet`()	Perform wavelet decomposition using the starlet transform.
`decompose_with_tophat`()	Perform wavelet decomposition using the top-hat filter.
`get_th_smooth_map`(map, window_radius)	Retrieve or compute the top-hat filter in Fourier space for a given radius.
`get_top_hat_filter`(window_radius)	Retrieve or compute the top-hat filter in Fourier space for a given radius.
`reconstruct`(coefficients)	Reconstruct image from wavelet coefficients by summing all scales.
`set_image`(input_map)	Set the input image and compute its Fourier transform.
`set_size_dependent_params`(image_shape[, L])	Initialize size-dependent parameters (frequency grids, pixel size, etc.) based on the image shape.
`top_hat_window_fourier`(k)	Compute the top-hat window function in Fourier space.

decompose(input_map: ndarray, num_scales=1, filter_type: str = 'tophat', recalculate_params: bool = True)[source]: Perform wavelet decomposition based on the chosen filter type for the given image.

decompose_with_starlet() → ndarray[source]: Perform wavelet decomposition using the starlet transform.

decompose_with_tophat() → ndarray[source]: Perform wavelet decomposition using the top-hat filter.

get_th_smooth_map(map, window_radius: float)[source]: Retrieve or compute the top-hat filter in Fourier space for a given radius.

get_top_hat_filter(window_radius: float) → ndarray[source]: Retrieve or compute the top-hat filter in Fourier space for a given radius.

reconstruct(coefficients: List[ndarray]) → ndarray[source]

Reconstruct image from wavelet coefficients by summing all scales.

set_image(input_map: ndarray) → None[source]: Set the input image and compute its Fourier transform.

set_size_dependent_params(image_shape, L=None)[source]: Initialize size-dependent parameters (frequency grids, pixel size, etc.) based on the image shape.

static top_hat_window_fourier(k)[source]: Compute the top-hat window function in Fourier space.