Python Sparse data Analysis Package

Note

This page is a reference documentation. It only explains the class signature, and not how to use it. Please refer to the gallery for the big picture.

class pysap.base.transform.WaveletTransformBase(nb_scale, verbose=0, dim=2, use_wrapping=False, **kwargs)[source]¶

Data structure representing a signal wavelet decomposition.

Available transforms are define in ‘pysap.transform’.

analysis(**kwargs)[source]¶

Decompose a real or complex signal using ISAP.

Fill the instance ‘analysis_data’ and ‘analysis_header’ parameters.

Parameters: kwargs : dict (optional)

the parameters that will be passed to ‘pysap.extensions.mr_tansform’.

property analysis_data¶

Get the decomposition coefficients array.

property analysis_header¶

Get the decomposition coefficients header.

band_at(scale, band)[source]¶

Get the band at a specific scale.

Parameters

scale : int

index of the scale.

band : int

index of the band.

Returns

band_data : nd-arry

the requested band data array.

classmethod bands_shapes(bands_lengths, ratio=None)[source]¶

Return the different bands associated shapes given there lengths.

Parameters

bands_lengths : ndarray (<nb_scale>, max(<nb_band_per_scale>, 0))

array holding the length between two bands of the data vector per scale.

ratio : ndarray, default None

a array containing ratios for eeach scale and each band.

Returns

bands_shapes : list of list of 2-uplet (<nb_scale>, <nb_band_per_scale>)

structure holding the shape of each bands at each scale.

property data¶

Get the input data array.

property info¶: Return the transformation information. This iformation is only available when using the Python bindings.

show()[source]¶: Display the different bands at the different decomposition scales.

synthesis()[source]¶

Reconstruct a real or complex signal from the wavelet coefficients using ISAP.