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IntegratorMechanism¶

Contents¶

  • Overview

  • Creating an IntegratorMechanism

  • Structure

  • Execution

  • Class Reference

Overview¶

An IntegratorMechanism integrates its input, possibly based on its prior values. The input can be a single scalar value or an array of scalars (list or 1d np.array). If it is a list or array, then each value is independently integrated. The default function (IntegratorFunction) can be parametrized to implement either a simple increment rate, additive accumulator, or an (exponentially weighted) time-averaging of its input. It can also be assigned a custom function.

Creating an IntegratorMechanism¶

An IntegratorMechanism can be created directly by calling its constructor, or using the mechanism command and specifying INTEGRATOR_MECHANISM as its mech_spec argument. Its function is specified in the function argument, which can be parametrized by calling its constructor with parameter values:

>>> import psyneulink as pnl
>>> my_time_averaging_mechanism = pnl.IntegratorMechanism(function=pnl.AdaptiveIntegrator(rate=0.5))

The default_variable argument specifies the format of its input (i.e., whether it is a single scalar or an array), as well as the value to use if none is provided when Mechanism is executed. Alternatively, the size argument can be used to specify the length of the array, in which case it will be initialized with all zeros.

Structure¶

An IntegratorMechanism has a single InputPort, the value of which is used as the variable for its function. The default for function is AdaptiveIntegrator(rate=0.5). However, a custom function can also be specified, so long as it takes a numeric value, or a list or np.ndarray of numeric values as its input, and returns a value of the same type and format. The Mechanism has a single OutputPort, the value of which is assigned the result of the call to the Mechanism’s function.

Execution¶

When an IntegratorMechanism is executed, it carries out the specified integration, and assigns the result to the value of its primary OutputPort. For the default function (IntegratorFunction), if the value specified for default_variable is a list or array, or size is greater than 1, each element of the array is independently integrated. If its rate parameter is a single value, that rate will be used for integrating each element. If the rate parameter is a list or array, then each element will be used as the rate for the corresponding element of the input (in this case, rate must be the same length as the value specified for default_variable or size).

Class Reference¶

class psyneulink.core.components.mechanisms.processing.integratormechanism.IntegratorMechanism(function=AdaptiveIntegrator(rate=0.5))¶

Subclass of ProcessingMechanism that integrates its input. See Mechanism for additional arguments and attributes.

Parameters

function (IntegratorFunction : default IntegratorFunction) – specifies the function used to integrate the input. Must take a single numeric value, or a list or np.array of values, and return one of the same form.

_handle_default_variable(default_variable=None, size=None, input_ports=None, function=None, params=None)¶

If any parameters with len>1 have been specified for the Mechanism’s function, and Mechanism’s default_variable has not been specified, reshape Mechanism’s variable to match function’s, but make sure function’s has the same outer dimensionality as the Mechanism’s

exception psyneulink.core.components.mechanisms.processing.integratormechanism.IntegratorMechanismError(error_value)¶

© Copyright 2016, Jonathan D. Cohen.

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  • IntegratorMechanism
    • Contents
    • Overview
    • Creating an IntegratorMechanism
    • Structure
    • Execution
    • Class Reference
  • Github