cubes.piws.importer.scans.Scans

class cubes.piws.importer.scans.Scans(session, project_name, center_name, scans, can_read=True, can_update=False, data_filepath=None, use_store=True, piws_security_model=True)

This class enables us to load the scan data to CW.

__init__(session, project_name, center_name, scans, can_read=True, can_update=False, data_filepath=None, use_store=True, piws_security_model=True)

Initialize the Scans class.

Parameters:

session: Session (mandatory) :

a cubicweb session.

project_name: str (mandatory) :

the name of the project.

center_name: str (mandatory) :

the center name.

scans: dict of list of dict (mandatory) :

the scan description: the first dictionary contains the subject name as keys and then a list of dictionaries with four keys (Scans - (Scan - TypeData - FileSet - ExternalResource - ScoreValues) - Assessment) that contains the entities parameter decriptions.

can_read: bool (optional, default True) :

set the read permission to the imported data.

can_update: bool (optional, default False) :

set the update permission to the imported data.

data_filepath: str (optional, default None) :

the path to folder containing the current study dataset.

use_store: bool (optional, default True) :

if True use an SQLGenObjectStore, otherwise the session.

piws_security_model: bool (optional, default True) :

if True apply the PIWS security model.

Notes

Here is an axemple of the definiton of the ‘scans’ parameter:

scans = {
    "subjects1": [{
        "Assessment": {
            "age_of_subject": 27, "identifier": u"toy_V1_subject1",
            "timepoint": u"V1"},
        "Scans": [{
            "TypeData": {
                "fov_y": 0, "fov_x": 0, "voxel_res_y": 2.0,
                "voxel_res_x": 2.0, "voxel_res_z": 2.0,
                "field": "3T", "tr": 2.5, "shape_y": 2,
                "shape_x": 2, "shape_z": 2, "te": 0,
                "type": u"MRIData"},
            "ExternalResources": [ {
                "absolute_path": True, "name": u"t1",
                "identifier": u"toy_V1_subject1_t1_1",
                "filepath": u"/tmp/demo/V1/subject1/images/t1/t1.nii.gz"}],
            "FileSet": {
                "identifier": u"toy_V1_subject1_t1", "name": u"T1"},
            "Scan": {
                "format": u"Nifti", "label": u"T1",
                "identifier": u"toy_V1_subject1_t1",
                "type": u"MRIData"}
        }]
    }]
}

Note that an optional filed can be set in order to specify the scan acquisition device.

scans = {
    "subjects1": [ {
        "Assessment": {
        ..
        },
        "Device": {
            "ExternalResources": [{
                "absolute_path": true, 
                "filepath": "/my/path/examcard.pdf", 
                "identifier": "EXAM_CARD_TIEMPOINT_CENTER", 
                "name": "EXAM_CARD_TIEMPOINT_CENTER"
            }], 
            "identifier": "31be53546754dc5f04ab2d9db6bed7cf", 
            "manufacturer": "SIEMENS", 
            "model": "Verio", 
            "serialnum": "xxxxx", 
            "software_version": "xxxxxx"
        }
        ...
    }]
}

Methods

__init__(session, project_name, center_name, ...)	Initialize the Scans class.
cleanup()	Method to cleanup temporary items and to commit changes.
import_data()	Method that import the scan data in the db.
schema(outfname[, text_font, node_text_size])	Create a view of the schema described in a python structure.

Attributes

assessment_relations
device_relations
dtype
fileset_relations
has_data
relations

__module__ = 'cubes.piws.importer.scans'

_create_scan(scan_struct, scantype_struct, fset_struct, extfiles, scores, subject_eid, study_eid, assessment_eid)

Create a scans and its associated relations.

dtype = 'PETData'

has_data = [('Scan', 'has_data', 'MRIData'), ('MRIData', 'scan', 'PETData'), ('MRIData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'DMRIData'), ('DMRIData', 'scan', 'PETData'), ('DMRIData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'FMRIData'), ('FMRIData', 'scan', 'PETData'), ('FMRIData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'EEGData'), ('EEGData', 'scan', 'PETData'), ('EEGData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'ETData'), ('ETData', 'scan', 'PETData'), ('ETData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'PETData'), ('PETData', 'scan', 'PETData'), ('PETData', 'in_assessment', 'Assessment')]

import_data()

Method that import the scan data in the db.

Note

Below the schema used to insert the scans:

Warning

In the ‘scans’ input structure, the ‘TypeData’ item contains a special key ‘type’ corresponding to the data type. The associated value is a string representing the entity name that must be in [‘PETData’, ‘FMRIData’, ‘DMRIData’, ‘MRIData’].

Warning

This method assumes that all the subjects and groups have already been inserted in the database.

relations = [['Scan', 'filesets', 'FileSet'], ('FileSet', 'in_assessment', 'Assessment'), ('FileSet', 'external_files', 'ExternalFile'), ('ExternalFile', 'fileset', 'FileSet'), ('ExternalFile', 'in_assessment', 'Assessment'), ('Assessment', 'study', 'Study'), ('Study', 'assessments', 'Assessment'), ('Subject', 'assessments', 'Assessment'), ('Assessment', 'subjects', 'Subject'), ('Center', 'assessments', 'Assessment'), ('Assessment', 'center', 'Center'), ('CWGroup', 'can_read', 'Assessment'), ('CWGroup', 'can_update', 'Assessment'), ('Assessment', 'device', 'Device'), ('Device', 'device_assessments', 'Assessment'), ['Scan', 'filesets', 'FileSet'], ('FileSet', 'in_assessment', 'Assessment'), ('FileSet', 'external_files', 'ExternalFile'), ('ExternalFile', 'fileset', 'FileSet'), ('ExternalFile', 'in_assessment', 'Assessment'), ('Device', 'center', 'Center'), ('Scan', 'study', 'Study'), ('Study', 'study_scans', 'Scan'), ('Scan', 'subject', 'Subject'), ('Subject', 'subject_scans', 'Scan'), ('Assessment', 'scans', 'Scan'), ('Scan', 'in_assessment', 'Assessment'), ('Scan', 'score_values', 'ScoreValue'), ('Assessment', 'device', 'Device'), ('Device', 'device_assessments', 'Assessment'), ('ScoreValue', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'MRIData'), ('MRIData', 'scan', 'PETData'), ('MRIData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'DMRIData'), ('DMRIData', 'scan', 'PETData'), ('DMRIData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'FMRIData'), ('FMRIData', 'scan', 'PETData'), ('FMRIData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'EEGData'), ('EEGData', 'scan', 'PETData'), ('EEGData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'ETData'), ('ETData', 'scan', 'PETData'), ('ETData', 'in_assessment', 'Assessment'), ('Scan', 'has_data', 'PETData'), ('PETData', 'scan', 'PETData'), ('PETData', 'in_assessment', 'Assessment')]