protoclass.data_management.DWIModality

class protoclass.data_management.DWIModality(path_data=None)

Class to handle DWI modality.

Parameters:

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

The folder in which the data are stored.

Attributes

path_data_	(str or list of str) Location of the data.
data_	(ndarray, shape (B_seq, Y, X, Z)) The different volume from different B sequuences. The data are saved in B_seq, Y, X, Z ordered.
pdf_series_	(list of ndarray, length (n_serie)) List of the PDF for each serie.
bin_series_	(list of ndarray, length (n_serie)) List of the bins used to plot the pdfs.
max_series_	(float) Maximum intensity of all the DCE series.
min_series_	(float) Minimum intensity of all the DCE series.
n_serie_	(int) Number of serie in this DCE sequence.
max_series_list_	(list of float) List of the maximum intensity for each DCE serie.
min_series_list_	(list of float) List of the minimum intensity for each DCE serie.

Methods

is_read()	Function to know if the data have been read.
read_data_from_path([path_data])	Function to read DWI images which represent a 3D volume over time.
update_histogram([nb_bins])	Update the histogram of each serie and first-order statistics.

__init__(path_data=None)

Methods

__init__([path_data])
is_read()	Function to know if the data have been read.
read_data_from_path([path_data])	Function to read DWI images which represent a 3D volume over time.
update_histogram([nb_bins])	Update the histogram of each serie and first-order statistics.

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)

Function to read DWI images which represent a 3D volume over time.

Parameters:

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

Path to the DWI data. It will overrides the path given in the constructor.

Returns:

self : object

Returns self.

update_histogram(nb_bins=None)

Update the histogram of each serie and first-order statistics.

Parameters:

nb_bins : list of int, str, 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, a list of integer needs to be given.

Returns:

self : object

Returns self.