Database module#

NNGT provides a database to store NEST simulations. This database requires peewee>3 to work and can be switched on using:

nngt.set_config("use_database", True)

The commands are then used by calling nngt.database to access the database tools.

Functions
Recording a simulation
Checking results in the database

Functions #

nngt.database.get_results(table, column=None, value=None)#

Return the entries where the attribute column satisfies the required equality.

Parameters:

Parameters:	table (str) – Name of the table where the search should be performed (among `'simulation'`, `'computer'`, `'neuralnetwork'`, `'activity'`, `'synapse'`, `'neuron'`, or `'connection'`). column (str, optional (default: None)) – Name of the variable of interest (a column on the table). If None, the whole table is returned. value (column corresponding type, optional (default: None)) – Specific value for the variable of interest. If None, the whole column is returned.
Returns:	`peewee.SelectQuery` with entries matching the request.

table (str) – Name of the table where the search should be performed (among 'simulation', 'computer', 'neuralnetwork', 'activity', 'synapse', 'neuron', or 'connection').
column (str, optional (default: None)) – Name of the variable of interest (a column on the table). If None, the whole table is returned.
value (column corresponding type, optional (default: None)) – Specific value for the variable of interest. If None, the whole column is returned.

Returns:

peewee.SelectQuery with entries matching the request.

nngt.database.is_clear()#: Check that the logs are clear.

nngt.database.log_simulation_end(network=None, log_activity=True)#: Record the simulation completion and simulated times, save the data, then reset.

nngt.database.log_simulation_start(network, simulator, save_network=True)#

Record the simulation start time, all nodes, connections, network, and computer properties, as well as some of simulation’s.

Parameters:	network (`Network` or subclass) – Network used for the current simulation. simulator (str) – Name of the simulator. save_network (bool, optional (default: True)) – Whether to save the network or not.

nngt.database.reset()#: Reset log status.

Recording a simulation #

nngt.database.log_simulation_start(net, "nest-2.14")
nest.Simulate(1000.)
nngt.database.log_simulation_end()

Checking results in the database #

The database contains the following tables, associated to their respective fields:

‘activity’: Activity,
‘computer’: Computer,
‘connection’: Connection,
‘neuralnetwork’: NeuralNetwork,
‘neuron’: Neuron,
‘simulation’: Simulation,
‘synapse’: Synapse.

These tables are the first keyword passed to get_results(), you can find the existing columns for each of the tables in the following classes descriptions:

Store results into a database

class nngt.database.db_generation.Activity(*args, **kwargs)[source]#

Class detailing the network’s simulated activity.

DoesNotExist#: alias of ActivityDoesNotExist

id = <IntegerField: Activity.id>#

raster = <PickledField: Activity.raster>#: Raster of the simulated activity.

simulations#

class nngt.database.db_generation.Computer(*args, **kwargs)[source]#

Class containing informations about the conputer.

DoesNotExist#: alias of ComputerDoesNotExist

cores = <IntegerField: Computer.cores>#: Number of cores returned by psutil.cpu_count() or -1

id = <IntegerField: Computer.id>#

name = <TextField: Computer.name>#: Name from platform.node() or "unknown"

platform = <TextField: Computer.platform>#: System information from platform.platform()

python = <TextField: Computer.python>#: Python version given by platform.python_version()

ram = <IntegerField: Computer.ram>#: Total memory given by psutil.virtual_memory().total (long) or -1

simulations#

class nngt.database.db_generation.Connection(*args, **kwargs)[source]#

Class detailing the existing connections in the network: a couple of pre- and post-synaptic neurons and a synapse.

DoesNotExist#: alias of ConnectionDoesNotExist

id = <IntegerField: Connection.id>#

post = <ForeignKeyField: Connection.post>#

post_id = <ForeignKeyField: Connection.post>#

pre = <ForeignKeyField: Connection.pre>#

pre_id = <ForeignKeyField: Connection.pre>#

simulations#

synapse = <ForeignKeyField: Connection.synapse>#

synapse_id = <ForeignKeyField: Connection.synapse>#

nngt.database.db_generation.migrate(*operations, **kwargs)[source]#

class nngt.database.db_generation.NeuralNetwork(*args, **kwargs)[source]#

Class containing informations about the neural network.

DoesNotExist#: alias of NeuralNetworkDoesNotExist

compressed_file = <LongCompressedField: NeuralNetwork.compressed_file>#: Compressed (bz2) string of the graph from str(graph); once uncompressed, can be loaded using Graph.from_file(name, from_string=True).

directed = <IntegerField: NeuralNetwork.directed>#: Whether the graph is directed or not

edges = <IntegerField: NeuralNetwork.edges>#: Number of edges.

id = <IntegerField: NeuralNetwork.id>#

network_type = <TextField: NeuralNetwork.network_type>#: Type of the network from Graph.type

nodes = <IntegerField: NeuralNetwork.nodes>#: Number of nodes.

simulations#

weight_distribution = <TextField: NeuralNetwork.weight_distribution>#: Name of the weight_distribution used.

weighted = <IntegerField: NeuralNetwork.weighted>#: Whether the graph is weighted or not.

class nngt.database.db_generation.Neuron(*args, **kwargs)[source]#

Base class that will be modified to contain all the properties of the neurons used during a simulation.

DoesNotExist#: alias of NeuronDoesNotExist

id = <IntegerField: Neuron.id>#

int_connections#

out_connections#

class nngt.database.db_generation.Simulation(*args, **kwargs)[source]#

Class containing all informations about the simulation properties.

DoesNotExist#: alias of SimulationDoesNotExist

activity = <ForeignKeyField: Simulation.activity>#: Activity table entry where the simulated activity is described.

activity_id = <ForeignKeyField: Simulation.activity>#

completion_time = <DateTimeField: Simulation.completion_time>#: Date and time at which the simulation ended.

computer = <ForeignKeyField: Simulation.computer>#: Computer table entry where the computer used is defined.

computer_id = <ForeignKeyField: Simulation.computer>#

connections = <ForeignKeyField: Simulation.connections>#: Connection table entry where the connections are described.

connections_id = <ForeignKeyField: Simulation.connections>#

grnd_seed = <IntegerField: Simulation.grnd_seed>#: Master seed of the simulation.

id = <IntegerField: Simulation.id>#

local_seeds = <PickledField: Simulation.local_seeds>#: List of the local threads seeds.

network = <ForeignKeyField: Simulation.network>#: Network table entry where the simulated network is described.

network_id = <ForeignKeyField: Simulation.network>#

pop_sizes = <PickledField: Simulation.pop_sizes>#: Pickled list containing the group sizes.

population = <PickledField: Simulation.population>#: Pickled list containing the neural group names.

resolution = <FloatField: Simulation.resolution>#: Timestep used to simulate the components of the neural network

simulated_time = <FloatField: Simulation.simulated_time>#: Virtual time that was simulated for the neural network.

simulator = <TextField: Simulation.simulator>#: Name of the neural simulator used (NEST, Brian…)

start_time = <DateTimeField: Simulation.start_time>#: Date and time at which the simulation started.

class nngt.database.db_generation.Synapse(*args, **kwargs)[source]#

Base class that will be modified to contain all the properties of the synapses used during a simulation.

DoesNotExist#: alias of SynapseDoesNotExist

connections#

id = <IntegerField: Synapse.id>#

Database module#

Functions#

Recording a simulation#

Checking results in the database#

Functions #

Recording a simulation #

Checking results in the database #