Simulation and Neural network Analysis Productivity layer
Project description
Blue Brain SNAP
Blue Brain Simulation and Neural network Analysis Productivity layer (Blue Brain SNAP).
Blue Brain SNAP is a Python library for accessing BlueBrain circuit models represented in SONATA format.
Installation
Blue Brain SNAP can be installed using pip:
pip install bluepysnap
Usage
There are two main interface classes provided by Blue Brain SNAP:
Circuit corresponds to the static structure of a neural network, that is:
node positions and properties,
edge positions and properties, and,
detailed morphologies.
Simulation corresponds to the dynamic data for a neural network simulation, including:
spike reports,
soma reports, and,
compartment reports.
Most of Blue Brain SNAP methods return pandas Series or DataFrames, indexed in a way to facilitate combining data from different sources (that is, by node or edge IDs).
Among other dependencies, Blue Brain SNAP relies on Blue Brain Project provided libraries:
Tools
Circuit Validation
Blue Brain SNAP provides a SONATA circuit validator for verifying circuits.
The validation includes:
integrity of the circuit config file.
existence of the different node/edges files and components directories.
presence of the “sonata required” field for node/edges files.
the correctness of the edge to node population/ids bindings.
existence of the morphology files for the nodes.
This functionality is provided by either the cli function:
bluepysnap validate-circuit my/circuit/path/circuit_config.jsonOr a python free function:
from bluepysnap.circuit_validation import validate
errors = validate("my/circuit/path/circuit_config.json")Simulation Validation
Similarly to circuit validation, Blue Brain SNAP also provides a SONATA simulation validator for verifying simulation configs.
Currently, the validator verifies that:
all the mandatory fields are present in the config file
all the properties in the simulation config specification have correct data types and accepted values
paths specified in the config exist
node sets specified in the config exist
input spike file’s node IDs are found in the source node set
electrodes file’s node IDs are found in the simulation’s node_set (if set) or in non-virtual populations
neurodamus helpers and variables exist (requires neurodamus to be available in the environment)
This functionality is provided by either the cli function:
bluepysnap validate-simulation my/circuit/path/simulation_config.jsonOr a python free function:
from bluepysnap.simulation_validation import validate
errors = validate("my/circuit/path/simulation_config.json")Acknowledgements
The development of this software was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
This project/research has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2).
The Blue Brain Project would like to thank Dr Eilif Muller, the author of the precursor to Blue Brain SNAP, for his invaluable insights and contributions
License
Blue Brain SNAP is licensed under the terms of the GNU Lesser General Public License version 3, unless noted otherwise, for example, external dependencies. Refer to COPYING.LESSER and COPYING for details.
Copyright (c) 2019-2024 Blue Brain Project/EPFL
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License version 3 as published by the Free Software Foundation.
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 Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License along with this program. If not, see <https://www.gnu.org/licenses/>.
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