Table of Contents

SelectionFunctions

Functions that selects a subset of elements to maintain or transform, while nulling the others.

class psyneulink.core.components.functions.selectionfunctions.SelectionFunction(default_variable, params, owner=None, name=None, prefs=None, context=None, **kwargs)

Functions that selects a particular value to maintain or transform, while nulling the others.

class psyneulink.core.components.functions.selectionfunctions.OneHot(default_variable=None, mode=None, direction=None, abs_val=None, indicator=None, tie=None, seed=None, params=None, owner=None, prefs=None)

Return an array with one non-zero value.

function returns an array the same length as the first item in variable, with all of its values zeroed except one (unless there is a tie, which is handled as specified by tie); the following options can be used in any combination:

  • mode: determines how the non-zero value(s) in the array is (are) selected

    • STANDARD: value (or 1) for the element(s) with the maximum or minimum value(s) in the array, as specified by the options below; all other elements are zeroed; this is the default.

    • PROB: value of probabilistically chosen element based on probabilities passed in second item of variable; if there is a tie, a single element is chosen probabilistically.

    • PROB_INDICATOR: same as PROB but chosen item is assigned a value of 1; if there is a tie, a single element is chosen probabilistically.

  • direction: MAX (default) or MIN determines whether the maximum or minimum value(s) in the array are selected.

  • abs_val: False (default) or True determines whether the absolute values of the elements in the array are used to select the maximum or minimum value(s).

  • indicator: False (default) or True determines whether the selected values(s) is (are) replace with a value of 1.

  • tie: ALL (default), FIRST, LAST or RANDOM determines how a tie is handled when there is more than one element with the maximum or minimum value;

    ALL: selects all elements in the tie;

    FIRST: selects the value of the element with the lowest index;

    LAST: selects the value of the element with the lowest index;

    RANDOM: randomly selects one of the tied elements;

The following convenience keywords can be used to specify particular combinations of options for the mode argument together with the tie argument (these are included mainly for backward compatibility):

  • ARG_MAX: signed value of a single element with the maximum signed value, or the one with lowest index if there is a tie.

  • ARG_MAX_ABS: absolute value of a single element with the maximum absolute value, or the one with lowest index if there is a tie.

  • ARG_MAX_INDICATOR: 1 in place of single element with maximum signed value, or the one with lowest index if there is a tie.

  • ARG_MAX_ABS_INDICATOR: 1 in place of single element with maximum absolute value, or the one with lowest index if there is a tie.

  • MAX_VAL: signed value of the element with the maximum signed value; if there is a tie, which elements are returned is determined by tie_index.

  • MAX_ABS_VAL: absolute value of the element with the maximum absolute value; if there is a tie, which elements are returned is determined by tie_index.

  • MAX_INDICATOR: 1 in place of the element with the maximum signed value; if there is a tie, which elements are returned is determined by tie_index.

  • MAX_ABS_INDICATOR: 1 in place of the element(s) with the maximum absolute value; if there is a tie, which elements are returned is determined by tie_index.

  • ARG_MIN: signed value of a single element with the minium signed value, or the one with lowest index if there is a tie.

  • ARG_MIN_ABS: absolute value of a single element with the minium absolute value, or the one with lowest index if there is a tie.

  • ARG_MIN_INDICATOR: 1 in place of single element with minimum signed value, or the one with lowest index if there is a tie.

  • MIN_VAL: signed value of the element with the minimum signed value, or all elements with the minimum value if there is a tie.

  • MIN_ABS_VAL: absolute value of element with the minimum absolute value; if there is a tie, which elements are returned is determined by tie_index.

  • MIN_INDICATOR: 1 in place of the element with the minimum signed value; if there is a tie, which elements are returned is determined by tie_index.

  • MIN_ABS_INDICATOR: 1 in place of the element with the minimum absolute value; if there is a tie, which elements are returned is determined by tie_index.

Parameters:

  • variable (2d np.array : default class_defaults.variable) – First (possibly only) item specifies a template for the array to be transformed; if mode is PROB then a 2nd item must be included that is a probability distribution with same length as 1st item.

  • mode (DETERMINISTiC, PROB, PROB_INDICATOR,)

  • ARG_MAX

  • ARG_MAX_ABS

  • ARG_MAX_INDICATOR

  • ARG_MAX_ABS_INDICATOR

:param : :param ARG_MIN: :param ARG_MIN_ABS: :param ARG_MIN_INDICATOR: :param ARG_MIN_ABS_INDICATOR: :param : :param MAX_VAL: :param MAX_ABS_VAL: :param MAX_INDICATOR: :param MAX_ABS_INDICATOR: :param : :param MIN_VAL: :param MIN_ABS_VAL: :param MIN_INDICATOR: :param MIN_ABS_INDICATOR: :param : :param : specifies how non-zero value(s) in the array returned by function are determined

(see above for details).

:type : default ARG_MAX :type direction: Optional[Literal[‘max’, ‘min’]] :param direction: specifies whether the maximum or minimum value(s) in the array are selected.

(see above for details).

Parameters:

  • abs_val (bool : default False) – specifies whether the absolute values of the elements in the array are used to select the maximum or minimum value(s). (see above for details).

  • indicator (bool : default False) – specifies whether the selected values(s) is (are) replace with a value of 1. (see above for details).

  • tie (ALL, FIRST, LAST, RANDOM : default ALL) – specifies how a tie is handled when there is more than one element with the maximum or minimum value; (see above for details).

  • params (Dict[param keyword: param value] : default None) – a parameter dictionary that specifies the parameters for the function. Values specified for parameters in the dictionary override any assigned to those parameters in arguments of the constructor.

  • owner (Component) – component to which to assign the Function.

  • name (str : default see name) – specifies the name of the Function.

  • prefs (PreferenceSet or specification dict : default Function.classPreferences) – specifies the PreferenceSet for the Function (see prefs for details).

variable

1st item contains value to be transformed; if mode is PROB, 2nd item is a probability distribution, each element of which specifies the probability for selecting the corresponding element of the 1st item.

Type:

number or np.array

mode
Type:

DETERMINISTIC, PROB, PROB_INDICATOR,

ARG_MAX, ARG_MAX_ABS, ARG_MAX_INDICATOR, ARG_MAX_ABS_INDICATOR,
ARG_MIN, ARG_MIN_ABS, ARG_MIN_INDICATOR, ARG_MIN_ABS_INDICATOR,
MAX_VAL, MAX_ABS_VAL, MAX_INDICATOR, MAX_ABS_INDICATOR,
MIN_VAL, MIN_ABS_VAL, MIN_INDICATOR,  MIN_ABS_INDICATOR,
direction

determines whether the maximum or minimum value(s) in the array are selected. (see above for details).

Type:

MAX or MIN

abs_val

determines whether the absolute values of the elements in the array are used to select the maximum or minimum value(s). (see above for details).

Type:

bool

indicator

determines whether the selected values(s) is (are) replace with a value of 1. (see above for details).

Type:

bool

tie

determines how a tie is handled when there is more than one element with the maximum or minimum value; (see above for details).

Type:

ALL, FIRST, LAST, RANDOM

random_state

private pseudorandom number generator

Type:

numpy.RandomState

owner

component to which the Function has been assigned.

Type:

Component

name

the name of the Function; if it is not specified in the name argument of the constructor, a default is assigned by FunctionRegistry (see Naming for conventions used for default and duplicate names).

Type:

str

prefs

the PreferenceSet for function; if it is not specified in the prefs argument of the Function’s constructor, a default is assigned using classPreferences defined in __init__.py (see Preferences for details).

Type:

PreferenceSet or specification dict : Function.classPreferences

_function(variable=None, context=None, params=None)
Parameters:

  • variable (2d np.array : default class_defaults.variable) – 1st item is an array to be transformed; if mode is PROB, 2nd item must be an array of probabilities (i.e., elements between 0 and 1) of equal length as the 1st item.

  • params (Dict[param keyword: param value] : default None) – a parameter dictionary that specifies the parameters for the function. Values specified for parameters in the dictionary override any assigned to those parameters in arguments of the constructor.

Returns:

array with selected elements having non-zero values and all others having zeroes – specified by mode, direction, abs_val, indicator, and tie.

Return type:

np.array

_parse_mode(mode)

Convert mode spec to corresponding options. Here for convenience, but mostly for backward compatibility with old mode spec.

_validate_params(request_set, target_set=None, context=None)

Validate params and assign validated values to targets,

This performs top-level type validation of params

This can be overridden by a subclass to perform more detailed checking (e.g., range, recursive, etc.) It is called only if the parameter_validation attribute is True (which it is by default)

IMPLEMENTATION NOTES:

  • future versions should add recursive and content (e.g., range) checking

  • should method return validated param set?

Parameters:

  • validated (dict (target_set) - repository of params that have been)

  • validated

Return none: