ANNarchy 5.0.0
  • ANNarchy
  • Installation
  • Tutorial
  • Manual
  • Notebooks
  • Reference

  • ANNarchy
  • Core components
    • Network
    • Population
    • Projection
    • Monitor
    • PopulationView
    • Dendrite
  • Neuron and Synapse models
    • Neuron
    • Synapse
    • Parameter
    • Variable
    • Creating
    • Pruning
    • Constant
  • Neuron models
    • LeakyIntegrator
    • Izhikevich
    • IF_curr_exp
    • IF_cond_exp
    • IF_curr_alpha
    • IF_cond_alpha
    • HH_cond_exp
    • EIF_cond_alpha_isfa_ista
    • EIF_cond_exp_isfa_ista
  • Synapse models
    • Hebb
    • Oja
    • IBCM
    • STP
    • STDP
  • Inputs
    • InputArray
    • TimedArray
    • PoissonPopulation
    • TimedPoissonPopulation
    • SpikeSourceArray
    • HomogeneousCorrelatedSpikeTrains
    • CurrentInjection
    • DecodingProjection
    • ImagePopulation
    • VideoPopulation
  • Random Distributions
    • Uniform
    • DiscreteUniform
    • Normal
    • LogNormal
    • Exponential
    • Gamma
    • Binomial
  • Functions
    • add_function
    • functions
  • Callbacks
    • every
  • Utilities
    • report
    • timeit
    • sparse_random_matrix
    • sparse_delays_from_weights
    • magic_network
  • Convolution
    • Convolution
    • Pooling
    • Transpose
    • Copy
  • BOLD monitoring
    • BoldMonitor
    • BoldModel
    • balloon_RN
    • balloon_RL
    • balloon_CN
    • balloon_CL
    • balloon_maith2021
    • balloon_two_inputs
  • Tensorboard logging
    • Logger
  • ANN-to-SNN conversion
    • ANNtoSNNConverter
  • DEPRECATED Top-level API
    • setup
    • compile
    • clear
    • reset
    • set_seed
    • get_population
    • get_projection
    • populations
    • projections
    • monitors
    • simulate
    • simulate_until
    • step
    • enable_learning
    • disable_learning
    • get_time
    • set_time
    • get_current_step
    • set_current_step
    • dt
    • save
    • load
    • save_parameters
    • load_parameters
    • callbacks_enabled
    • disable_callbacks
    • enable_callbacks
    • clear_all_callbacks

On this page

  • Parameter
    • Parameters

Parameter

Parameter(self, value, locality='local', type='float')

Dataclass to represent a parameter in a Neuron or Synapse definition.

neuron = ann.Neuron(
    parameters = dict(

        # Global parameter
        tau = 10.0 # or ann.Parameter(value=10.0, locality='global')

        # Local parameter
        baseline = ann.Parameter(value=ann.Uniform(-1., 1.)),

        # Boolean global parameter
        activated = ann.Parameter(value=True, locality='global', type=bool),
    )
)

In a neuron or synapse model, parameters are global and use the float type if the Parameter class is not used.

If you need a local parameter (one value per neuron or synapse), the Parameter class allows to specify it. Note that you can also define global parameters by passing locality='global'.

Semi-global synaptic parameters (one value per post-synaptic neuron) can be defined using locality='semiglobalglobal'.

If the parameter is an int or a bool, pass it to the type attribute.

Parameters

Name Type Description Default
value float | int | bool | RandomDistribution Initial value of the parameter. It can be defined as a RandomDistribution, which will be sampled with the correct shape when the population/projection is created, or a float/int/bool, depending on type. required
locality str Locality of the parameter. Must be in [‘global’, ‘semiglobal’, ‘local’]. 'local'
type str Data type of the parameter. Must be in [float, int, bool] (or [‘float’, ‘int’, ‘bool’]). 'float'
Synapse
Variable
 

Copyright Julien Vitay, Helge Ülo Dinkelbach, Fred Hamker