The Virtual Brain Project

Source code for tvb.core.entities.transient.context_overlay

# -*- coding: utf-8 -*-
#
#
# TheVirtualBrain-Framework Package. This package holds all Data Management, and 
# Web-UI helpful to run brain-simulations. To use it, you also need do download
# TheVirtualBrain-Scientific Package (for simulators). See content of the
# documentation-folder for more details. See also http://www.thevirtualbrain.org
#
# (c) 2012-2017, Baycrest Centre for Geriatric Care ("Baycrest") and others
#
# This program is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software Foundation,
# either version 3 of the License, or (at your option) any later version.
# This program is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE.  See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with this
# program.  If not, see <http://www.gnu.org/licenses/>.
#
#
#   CITATION:
# When using The Virtual Brain for scientific publications, please cite it as follows:
#
#   Paula Sanz Leon, Stuart A. Knock, M. Marmaduke Woodman, Lia Domide,
#   Jochen Mersmann, Anthony R. McIntosh, Viktor Jirsa (2013)
#       The Virtual Brain: a simulator of primate brain network dynamics.
#   Frontiers in Neuroinformatics (7:10. doi: 10.3389/fninf.2013.00010)
#
#
"""
Entities to be used with an overlay on Operation or DataType, are defined here.

.. moduleauthor:: Lia Domide <lia.domide@codemart.ro>
"""

import numpy
import six
from tvb.basic.config.utils import EnhancedDictionary
from tvb.core.entities import model
from tvb.core.utils import date2string


[docs]class CommonDetails(EnhancedDictionary): """ Enhanced dictionary holding details about an entity. It also contains metadata on how this details will be displayed in UI (disabled/readonly/hidden input field). """ CODE_GID = "gid" CODE_OPERATION_TAG = "operation_label" CODE_OPERATION_GROUP_ID = 'operation_group_id' CODE_OPERATION_GROUP_NAME = 'operation_group_name' def __init__(self): super(CommonDetails, self).__init__() self.metadata = dict() self.scientific_details = dict() self.gid = None self.metadata[self.CODE_GID] = {"name": "Unique Global Identifier", "readonly": "True"} self.author = None self.metadata['author'] = {"name": "Author", "disabled": "True"} self.operation_type = None self.metadata['operation_type'] = {"name": "Operation Algorithm", "disabled": "True"} self.operation_label = None self.metadata[self.CODE_OPERATION_TAG] = {"name": "Operation Label"} self.count = 1 self.metadata['count'] = {"name": "No. of entities in group", "disabled": "True"} self.operation_group_id = None self.metadata[self.CODE_OPERATION_GROUP_ID] = {"name": "groupId", "hidden": "True"} self.operation_group_name = None self.metadata[self.CODE_OPERATION_GROUP_NAME] = {"name": "operationGroupName", "hidden": "True"} self.burst_name = None self.metadata['burst_name'] = {"name": "Simulation", "disabled": "True"}
[docs] def add_scientific_fields(self, extra_fields_dict): """ :param extra_fields_dict a dictionary of fields to be added in a distinct category. """ for key, value in six.iteritems(extra_fields_dict): if value is not None and isinstance(value, numpy.ndarray): # Make sure arrays are displayed in a compatible form: [1, 2, 3] value = str(value.tolist()) elif value is not None and isinstance(value, list) and len(value) > 0 and isinstance(value[0], str): value = [str(v) for v in value] self.scientific_details[key] = {"name": key, "value": str(value), "disabled": "True"}
@property
[docs] def meta_attributes_list(self): """ A list with all attributes for a DataType which are expected to be submitted from UI. """ result = self.keys() result.remove('metadata') result.remove('scientific_details') return result
@staticmethod
[docs] def compute_operation_name(category_name, algorithm_name): """ Compute Operation display name, based on Operation Category and Algorithm. """ display_name = '' if category_name: display_name = category_name if algorithm_name: display_name = display_name + "->" + algorithm_name return display_name
[docs] def get_ui_fields(self): """ :returns: list of dictionaries to be used for UI display. \ Each entry in the list will be displayed as a UI group of fields. """ framework_metadata = self.metadata for key in self.meta_attributes_list: framework_metadata[key]['value'] = getattr(self, key) if len(self.scientific_details) > 0: return [self.scientific_details, framework_metadata] return [framework_metadata]
[docs]class OperationOverlayDetails(CommonDetails): """ Entity used for displaying in an overlay details about an operation. """ def __init__(self, operation, username, count_inputs, count_results, burst, no_of_op_in_group, op_pid): super(OperationOverlayDetails, self).__init__() self.operation_id = operation.id self.metadata['operation_id'] = {"name": "Entity id", "disabled": "True"} self.operation_status = operation.status self.metadata['operation_status'] = {"name": "Status", "disabled": "True"} self.start_date = date2string(operation.start_date) self.metadata['start_date'] = {"name": "Start date", "disabled": "True"} self.end_date = "None" if operation.completion_date is None else date2string(operation.completion_date) self.metadata['end_date'] = {"name": "End date", "disabled": "True"} self.result_datatypes = count_results self.metadata['result_datatypes'] = {"name": "No. of resulted DataTypes", "disabled": "True"} self.input_datatypes = count_inputs self.metadata['input_datatypes'] = {"name": "No. of input DataTypes", "disabled": "True"} # If the operation was executed in another process or as a cluster then show the pid/job_id if op_pid is not None: if op_pid.pid is not None: self.pid = op_pid.pid self.metadata['pid'] = {"name": "Process pid", "disabled": "True"} elif op_pid.job_id is not None: self.job_id = op_pid.job_id self.metadata['job_id'] = {"name": "Cluster job Id", "disabled": "True"} ### Now set/update generic fields self.gid = operation.gid self.author = username self.count = no_of_op_in_group self.burst_name = burst.name if burst is not None else "" self.operation_type = self.compute_operation_name(operation.algorithm.algorithm_category.displayname, operation.algorithm.displayname) group_id = operation.operation_group.id if operation.operation_group is not None else None self.operation_group_id = group_id self.operation_label = (operation.operation_group.name if operation.operation_group is not None else operation.user_group) self.metadata[self.CODE_OPERATION_TAG]["disabled"] = 'True' group_value = operation.operation_group.name if operation.operation_group is not None else None self.operation_group_name = group_value self.metadata[self.CODE_OPERATION_GROUP_NAME]["disabled"] = 'True'
[docs]class DataTypeOverlayDetails(CommonDetails): """ Entity used for displaying in an overlay details about a DataType. """ DATA_SUBJECT = "subject" DATA_STATE = "data_state" DATA_TITLE = "datatype_title" DATA_TAG_1 = "datatype_tag_1" DATA_TAG_2 = "datatype_tag_2" DATA_TAG_3 = "datatype_tag_3" DATA_TAG_4 = "datatype_tag_4" DATA_TAG_5 = "datatype_tag_5" def __init__(self): super(DataTypeOverlayDetails, self).__init__() self.data_state = None self.metadata[self.DATA_STATE] = {"name": "State"} self.datatype_title = None self.metadata[self.DATA_TITLE] = {"name": "Title", "disabled": "True"} self.subject = None self.metadata[self.DATA_SUBJECT] = {"name": "Subject"} self.data_type = None self.metadata['data_type'] = {"name": "Data Type", "disabled": "True"} self.data_type_id = None self.metadata['data_type_id'] = {"name": "Entity id", "disabled": "True"} self.create_date = None self.metadata['create_date'] = {"name": "Creation Date", "disabled": "True"} self.datatype_tag_1 = None self.metadata[self.DATA_TAG_1] = {"name": "DataType Tag 1"} self.datatype_tag_2 = None self.metadata[self.DATA_TAG_2] = {"name": "DataType Tag 2"} self.datatype_tag_3 = None self.metadata[self.DATA_TAG_3] = {"name": "DataType Tag 3"} self.datatype_tag_4 = None self.metadata[self.DATA_TAG_4] = {"name": "DataType Tag 4"} self.datatype_tag_5 = None self.metadata[self.DATA_TAG_5] = {"name": "DataType Tag 5"} self.datatype_size = None self.metadata['datatype_size'] = {"name": "Size on Disk (KB)", "disabled": "True"}
[docs] def fill_from_datatype(self, datatype_result, parent_burst): """ Fill current dictionary with information from a loaded DB DataType. :param datatype_result DB loaded DataType :param parent_burst Burst entity in which current dataType was generated """ self.gid = datatype_result.gid self.data_type_id = datatype_result.id self.data_state = datatype_result.state self.datatype_title = datatype_result.display_name self.subject = datatype_result.subject self.data_type = datatype_result.type self.datatype_tag_1 = datatype_result.user_tag_1 self.datatype_tag_2 = datatype_result.user_tag_2 self.datatype_tag_3 = datatype_result.user_tag_3 self.datatype_tag_4 = datatype_result.user_tag_4 self.datatype_tag_5 = datatype_result.user_tag_5 self.datatype_size = datatype_result.disk_size self.author = datatype_result.parent_operation.user.username parent_algorithm = datatype_result.parent_operation.algorithm operation_name = self.compute_operation_name(parent_algorithm.algorithm_category.displayname, parent_algorithm.displayname) self.operation_type = operation_name create_date_str = '' if datatype_result.parent_operation.completion_date is not None: create_date_str = date2string(datatype_result.parent_operation.completion_date) self.create_date = create_date_str if parent_burst is not None: self.burst_name = parent_burst.name else: self.burst_name = '' ### Populate Group attributes if isinstance(datatype_result, model.DataTypeGroup): self.count = datatype_result.count_results self.operation_group_name = datatype_result.parent_operation.operation_group.name self.operation_label = datatype_result.parent_operation.operation_group.name self.operation_group_id = datatype_result.parent_operation.operation_group.id else: self.operation_label = datatype_result.parent_operation.user_group ### Populate Scientific attributes if hasattr(datatype_result, 'summary_info') and datatype_result.summary_info is not None: self.add_scientific_fields(datatype_result.summary_info)