protoclass.extraction.LBPExtraction

class protoclass.extraction.LBPExtraction(base_modality, p=8, r=1.0, kind='uniform')

LBP extraction from standalone modality.

Parameters:

base_modality : object

The base modality on which the normalization will be applied. The base modality should inherate from StandaloneModality class.

p : int, optional (default=8)

Number of circularly symmetric neighbour set points (quantization of the angular space).

r : float, optional (default=1.)

Radius of circle (spatial resolution of the operator).

kind : str, optional (default=’uniform’)

Type of LBP to choose: ‘default’, ‘ror’, ‘uniform’, ‘nri_uniform’, and ‘var’

Attributes

base_modality_	(object) The base modality on which the normalization will be applied. The base modality should inherate from StandaloneModality class.
roi_data_	(ndarray, shape flexible) Corresponds to the index to consider in order to fit the data.

Methods

fit(modality[, ground_truth, cat])	Compute the LBP images in the three-ortogonal planes.
load_from_pickles(filename)	Function to load a normalization object.
save_to_pickles(filename)	Function to save a normalizatio object using pickles.
transform(modality[, ground_truth, cat])	Extract the data from the given modality.

__init__(base_modality, p=8, r=1.0, kind='uniform')

Methods

__init__(base_modality[, p, r, kind])
fit(modality[, ground_truth, cat])	Compute the LBP images in the three-ortogonal planes.
load_from_pickles(filename)	Function to load a normalization object.
save_to_pickles(filename)	Function to save a normalizatio object using pickles.
transform(modality[, ground_truth, cat])	Extract the data from the given modality.

fit(modality, ground_truth=None, cat=None)

Compute the LBP images in the three-ortogonal planes.

Parameters:

modality : object of type TemporalModality

The modality object of interest.

ground-truth : object of type GTModality or None

The ground-truth of GTModality. If None, the whole data will be considered.

cat : str or None

String corresponding at the ground-truth of interest. Cannot be None if ground-truth is not None.

load_from_pickles(filename)

Function to load a normalization object.

Parameters:

filename : str

Filename to the pickle file. The extension should be .p.

Returns:

bpp : object

Returns the loaded object.

save_to_pickles(filename)

Function to save a normalizatio object using pickles.

Parameters:

filename : str

Filename to the pickle file. The extension should be .p.

Returns:

None

transform(modality, ground_truth=None, cat=None)

Extract the data from the given modality.

Parameters:

modality : object of type StandaloneModality

The modality object of interest.

ground-truth : object of type GTModality or None

The ground-truth of GTModality. If None, the whole data will be considered.

cat : str or None

String corresponding at the ground-truth of interest. Cannot be None if ground-truth is not None.

Returns

——

data : ndarray, shape (n_sample, n_feature)

A matrix containing the features extracted. The number of samples is equal to the number of positive label in the ground-truth.