Class NeuroMLBridge
java.lang.Object
org.episteme.natural.biology.loaders.neuroml.NeuroMLBridge
Bridge for converting NeuroML DTOs to core Episteme domain objects.
This bridge provides systematic conversion from NeuroML-parsed data transfer objects to the core Episteme architecture, enabling deep integration with the library's domain models for cells, neurons, synapses, and neural networks.
Architecture
NeuroML XML → NeuroMLReader → Cell/Morphology DTOs → NeuroMLBridge → Core Episteme Objects
├── Neuron
├── NeuronMorphology
├── Synapse
└── NeuralNetwork
Usage Example
NeuroMLReader reader = new NeuroMLReader();
NeuroMLModel model = reader.read(new File("neuron.nml"));
// Convert to core Episteme structures
NeuroMLBridge bridge = new NeuroMLBridge();
List<Neuron> neurons = bridge.toNeurons(model);
NeuralNetwork network = bridge.toNeuralNetwork(model);
- Since:
- 1.0
- Author:
- Silvere Martin-Michiellot, Gemini AI (Google DeepMind)
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionconvertMorphology(Morphology morphology) Converts NeuroML Morphology to Episteme NeuronMorphology.convertToNeuron(Cell neuromlCell) Converts a single NeuroML Cell DTO to a Episteme Neuron.toBiologyCell(Cell neuromlCell) Converts a NeuroML Cell to a generic Episteme biology Cell.toNeuralNetwork(NeuroMLDocument model) Converts NeuroML network to Episteme NeuralNetwork.toNeurons(NeuroMLDocument model) Converts NeuroML Cell DTOs to Episteme Neuron objects.
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Constructor Details
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NeuroMLBridge
public NeuroMLBridge()
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Method Details
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toNeurons
Converts NeuroML Cell DTOs to Episteme Neuron objects.NeuroML cells contain morphological and biophysical data that maps to the neuroscience domain model.
- Parameters:
model- the parsed NeuroML model- Returns:
- list of Neuron objects
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convertToNeuron
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convertMorphology
Converts NeuroML Morphology to Episteme NeuronMorphology.- Parameters:
morphology- the NeuroML morphology DTO- Returns:
- a NeuronMorphology object
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toNeuralNetwork
Converts NeuroML network to Episteme NeuralNetwork.- Parameters:
model- the parsed NeuroML model- Returns:
- a NeuralNetwork containing populations and projections
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toBiologyCell
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