Source code for tvb.adapters.datatypes.db.mapped_value

# -*- coding: utf-8 -*-
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# TheVirtualBrain-Framework Package. This package holds all Data Management, and
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"""
.. moduleauthor:: Bogdan Neacsa <bogdan.neacsa@codemart.ro>
.. moduleauthor:: Lia Domide <lia.domide@codemart.ro>
"""

import json

from sqlalchemy import Column, String, Integer, ForeignKey
from sqlalchemy.orm import relationship
from tvb.adapters.datatypes.db.time_series import TimeSeriesIndex
from tvb.adapters.datatypes.h5.mapped_value_h5 import ValueWrapper
from tvb.core.entities.file.simulator.datatype_measure_h5 import DatatypeMeasure
from tvb.core.entities.model.model_datatype import DataType


[docs] class ValueWrapperIndex(DataType): """ Class to wrap a singular value storage in DB. """ id = Column(Integer, ForeignKey(DataType.id), primary_key=True) data_value = Column(String) data_type = Column(String, default='unknown') data_name = Column(String) @property def display_name(self): """ Simple String to be used for display in UI.""" return "Value Wrapper - " + self.data_name + " : " + str(self.data_value) + " (" + str(self.data_type) + ")"
[docs] def fill_from_has_traits(self, datatype): # type: (ValueWrapper) -> None super(ValueWrapperIndex, self).fill_from_has_traits(datatype) self.data_value = datatype.data_value self.data_type = datatype.data_type self.data_name = datatype.data_name
[docs] class DatatypeMeasureIndex(DataType): """ Class to hold the metric for a previous stored DataType. E.g. Measure (single value) for any TimeSeries resulted in a group of Simulations """ id = Column(Integer, ForeignKey(DataType.id), primary_key=True) # Actual measure (dictionary Algorithm: single Value) serialized metrics = Column(String) # DataType for which the measure was computed. fk_source_gid = Column(String(32), ForeignKey(TimeSeriesIndex.gid), nullable=False) source = relationship(TimeSeriesIndex, foreign_keys=fk_source_gid, primaryjoin=TimeSeriesIndex.gid == fk_source_gid) @property def display_name(self): result = super(DatatypeMeasureIndex, self).display_name if self.metrics is not None: metrics = json.loads(self.metrics) for entry, metric_value in metrics.items(): result = result + " -- " + entry + ' : ' + str(metric_value) return result
[docs] def fill_from_has_traits(self, datatype): # type: (DatatypeMeasure) -> None super(DatatypeMeasureIndex, self).fill_from_has_traits(datatype) self.metrics = json.dumps(datatype.metrics) self.fk_source_gid = datatype.analyzed_datatype.gid.hex