protoclass.data_management.ADCModality

class protoclass.data_management.ADCModality(path_data=None)

Class to handle ADC modality.

Parameters:

path_data : str, optional (default=None)

The folder in which the data are stored.

Attributes

path_data_	(string) Location of the data.
data_	(ndarray, shape (Y, X, Z)) The different volume of the T2W volume. The data are saved in Y, X, Z ordered.
metadata_	(dict) Dictionnary which contain the MRI sequence information. Note that the information are given in the original ordering (X, Y, Z), which is different from the organisation of data_ which is (Y, X, Z).
pdf_	(list, length (n_serie)) List of the PDF for each serie.
bin_	(list of ndarray, length (n_serie)) List of the bins used to plot the pdfs.
max_	(float) Maximum intensity of the T2W-MRI volume.
min_	(float) Minimum intensity of the T2W-MRI volume.

Methods

get_pdf([roi_data, nb_bins])	Extract the a list of pdf related with the data.
is_read()	Function to know if the data have been read.
read_data_from_path([path_data])	Read T2W images which represent a single 3D volume.
update_histogram([nb_bins])	Update the PDF and the first-order statistics.

__init__(path_data=None)

Methods

__init__([path_data])
get_pdf([roi_data, nb_bins])	Extract the a list of pdf related with the data.
is_read()	Function to know if the data have been read.
read_data_from_path([path_data])	Read T2W images which represent a single 3D volume.
update_histogram([nb_bins])	Update the PDF and the first-order statistics.

get_pdf(roi_data=None, nb_bins='auto')

Extract the a list of pdf related with the data.

Parameters:

roi_data : tuple

Indices of elements to consider while computing the histogram. The ROI is a 3D volume which will be used for each time serie.

nb_bins : list of int or str, optional (default=’auto’)

The numbers of bins to use to compute the histogram. The possibilities are: - If ‘auto’, the number of bins is found at fitting time. - If None, the number of bins used is the one at the last call of update histogram. - Otherwise, a list of integer needs to be given.

Returns:

pdf_data : ndarray, length (n_serie)

List of the pdf with the associated series.

bin_data : list of ndarray, length (n_series + 1)

List of the bins associated with the list of pdf.

is_read()

Function to know if the data have been read.

Returns:

is_read : bool

If True, the data have been read at least once.

read_data_from_path(path_data=None)

Read T2W images which represent a single 3D volume.

Parameters:

path_data : str or None, optional (default=None)

Path to the standalone modality data.

Returns:

self : object

Returns self.

update_histogram(nb_bins=None)

Update the PDF and the first-order statistics.

Parameters:

nb_bins : int or None, optional (default=None)

The numbers of bins to use to compute the histogram. The possibilities are: - If None, the number of bins found at reading will be used. - If ‘auto’, the number of bins is found at fitting time. - Otherwise, an integer needs to be given.

Returns:

self : object

Returns self.

Notes

There is the possibility to redifine the number of bins to use for the histogram since it can be tricky to play with normalized data.