ANNarchy 4.8.2
  • ANNarchy
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  • Reference
  • Core components
    • Population
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  • Configuration
    • setup
    • compile
    • clear
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    • set_seed
    • get_population
    • get_projection
    • populations
    • projections
    • monitors
  • Simulation
    • simulate
    • simulate_until
    • step
    • parallel_run
    • enable_learning
    • disable_learning
    • get_time
    • set_time
    • get_current_step
    • set_current_step
    • dt
  • 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
    • STP
    • STDP
    • Hebb
    • Oja
    • IBCM
  • Inputs
    • InputArray
    • TimedArray
    • PoissonPopulation
    • TimedPoissonPopulation
    • SpikeSourceArray
    • HomogeneousCorrelatedSpikeTrains
    • CurrentInjection
    • DecodingProjection
    • ImagePopulation
    • VideoPopulation
  • IO
    • save
    • load
    • save_parameters
    • load_parameters
  • Utilities
    • report
  • Random Distributions
    • Uniform
    • DiscreteUniform
    • Normal
    • LogNormal
    • Exponential
    • Gamma
    • Binomial
  • Functions and Constants
    • add_function
    • functions
    • Constant
    • get_constant
  • Plotting
    • raster_plot
    • histogram
    • inter_spike_interval
    • coefficient_of_variation
    • population_rate
    • smoothed_rate
  • Callbacks
    • every
    • callbacks_enabled
    • disable_callbacks
    • enable_callbacks
    • clear_all_callbacks
  • 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

On this page

  • DiscreteUniform
    • Parameters
    • Methods
      • get_values

DiscreteUniform

core.Random.DiscreteUniform(self, min, max, seed=None)

Discrete uniform distribution between min and max.

The returned values are integers in the range [min, max].

Parameters

Name Type Description Default
min int minimum value. required
max int maximum value. required
seed int (optional) seed for the random generator. If left None, the value set in ann.setup() is used. None

Methods

Name Description
get_values Returns a Numpy array with the given shape.

get_values

core.Random.DiscreteUniform.get_values(shape)

Returns a Numpy array with the given shape.

Parameters

Name Type Description Default
shape tuple Shape of the array. required

Returns

Name Type Description
np.ndarray Array.
Uniform
Normal
 

Copyright Julien Vitay, Helge Ülo Dinkelbach, Fred Hamker