Data, Iteration, and Logging Utilities

Internal helpers for preprocessing, iteration, storage, and documentation.

Index

init_train!, init_classify!, hypersphere_preprocess, get_dim, get_n_samples, get_data_shape, get_sample, element_min
get_iterator, update_iter, build_art_stats, log_art_stats!
replace_mat_index!, unsafe_replace_mat_index!, accommodate_vector!
_COMMON_DOC, _OPTS_DOCSTRING, _ARG_ART, _ARG_X, _ARG_W, _ARG_INDEX, _ARG_ART_X_W, _ARGS_MATRIX_REPLACE, MATCH_FUNCTIONS_DOCS, ACTIVATION_FUNCTIONS_DOCS

Data Preparation

`init_train!`

AdaptiveResonance.init_train! — Function

init_train!(
    x::AbstractVector{T} where T<:Real,
    art::ARTModule,
    preprocessed::Bool
) -> AbstractVector{T} where T<:Real

Summary

Initializes the module for training in a single iteration.

The purpose of this function is mainly to handle the conditions of complement coding. Fails if the module was incorrectly set up or if the module was not setup and the data was not preprocessed.

Arguments

x::RealVector: the sample used for initialization.
art::ARTModule: the ART/ARTMAP module that will be trained on the sample.
preprocessed::Bool: a required flag for if the sample has already been complement coded and normalized.

Method List / Definition Locations

init_train!(x, art, preprocessed)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/ART/single/modules/HypersphereART.jl:144.

init_train!(x, art, preprocessed)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:470.

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init_train!(
    x::AbstractMatrix{T} where T<:Real,
    art::ARTModule,
    preprocessed::Bool
) -> Any

Summary

Initializes the training loop for batch learning.

Arguments

x::RealMatrix: the data that is used for training.
art::ARTModule: the ART/ARTMAP that will be trained.
preprocessed::Bool: required flag for if the data has already been complement coded and normalized.

Method List / Definition Locations

init_train!(x, art, preprocessed)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/ART/single/modules/HypersphereART.jl:155.

init_train!(x, art, preprocessed)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:501.

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`init_classify!`

AdaptiveResonance.init_classify! — Function

init_classify!(
    x::AbstractArray{T} where T<:Real,
    art::ARTModule,
    preprocessed::Bool
) -> Any

Summary

Initializes the classification loop for batch inference.

Arguments

x::RealArray: the data that is used for inference.
art::ARTModule: the ART/ARTMAP module that will be used for inference.
preprocessed::Bool: required flag for if the data has already been complement coded and normalized.

Method List / Definition Locations

init_classify!(x, art, preprocessed)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/ART/single/modules/HypersphereART.jl:170.

init_classify!(x, art, preprocessed)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:519.

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`hypersphere_preprocess`

AdaptiveResonance.hypersphere_preprocess — Function

hypersphere_preprocess(
    x::AbstractArray{T} where T<:Real,
    art::HypersphereART,
    preprocessed::Bool
) -> Any

Summary

Validate Hypersphere ART input dimensions and normalize original features.

Method List / Definition Locations

hypersphere_preprocess(x, art, preprocessed)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/ART/single/modules/HypersphereART.jl:178.

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`get_dim`

AdaptiveResonance.get_dim — Function

get_dim(data::AbstractMatrix{T} where T<:Real) -> Any

Summary

Returns the dimension of the data, enforcint the (dim, n_samples) convention of the package.

Arguments

data::RealMatrix: the 2-D data to infer the feature dimension of.

Method List / Definition Locations

get_dim(data)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:227.

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`get_n_samples`

AdaptiveResonance.get_n_samples — Function

get_n_samples(data::AbstractMatrix{T} where T<:Real) -> Any

Summary

Returns the number of samples, enforcing the convention of the package.

Arguments

data::RealMatrix: the 2-D data to infer the number of samples from.

Method List / Definition Locations

get_n_samples(data)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:238.

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`get_data_shape`

AdaptiveResonance.get_data_shape — Function

get_data_shape(
    data::AbstractMatrix{T} where T<:Real
) -> Tuple{Any, Any}

Summary

Returns the (dim, n_samples) of the provided 2-D data matrix, enforcing the ART package convention.

Arguments

data::RealMatrix: the 2-D data to infer the feature dimension and number of samples from.

Method List / Definition Locations

get_data_shape(data)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:249.

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`get_sample`

AdaptiveResonance.get_sample — Function

get_sample(
    x::AbstractMatrix{T} where T<:Real,
    i::Integer
) -> Any

Summary

Returns a sample from data array x at sample location i. This function implements the convention that columns are samples while rows are features within samples.

Arguments

x::RealMatrix: the batch of data to grab a sample from.
i::Integer: the index to get the sample from.

Method List / Definition Locations

get_sample(x, i)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:453.

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`element_min`

AdaptiveResonance.element_min — Function

element_min(
    x::AbstractVector{T} where T<:Real,
    W::AbstractVector{T} where T<:Real
) -> Any

Summary

Returns the element-wise minimum between sample x and weight W.

Arguments

x::RealVector: the input sample.
W::RealVector: the weight vector to compare the sample against.

Method List / Definition Locations

element_min(x, W)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:178.

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Iteration and Logging

`get_iterator`

AdaptiveResonance.get_iterator — Function

get_iterator(opts::ARTOpts, n_samples::Integer) -> Any

Summary

Creates an iterator object according to the ART/ARTMAP modules display settings for batch iteration.

Arguments

opts::ARTOpts: the ART/ARTMAP module's options containing display settings.
n_samples::Integer: the number of iterations to create the iterator for.

Method List / Definition Locations

get_iterator(opts, n_samples)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:417.

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`update_iter`

AdaptiveResonance.update_iter — Function

update_iter(
    art::ARTModule,
    iter::Union{ProgressBars.ProgressBar, UnitRange},
    i::Integer
) -> Union{Nothing, String}

Summary

Updates the iteration of the ART/ARTMAP module, training or inference, according to its display settings.

Arguments

art::ARTModule: the ART/ARTMAP module being iterated upon.
iter::ARTIterator: the iterator object used in the training/inference loop.
i::Integer: the iteration during training/inference that the iterator should be updated to.

Method List / Definition Locations

update_iter(art, iter, i)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:436.

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`build_art_stats`

AdaptiveResonance.build_art_stats — Function

build_art_stats() -> Dict{String, Any}

Summary

Initializes an ARTStats dictionary with zero entries.

Method List / Definition Locations

build_art_stats()

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:138.

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`log_art_stats!`

AdaptiveResonance.log_art_stats! — Function

log_art_stats!(art::ARTModule, bmu::Integer, mismatch::Bool)

Summary

Logs common statistics of an ART module after a training/classification iteration.

Arguments

art::ARTModule: the ART module that just underwent training/classification.
bmu::Integer: the best-matching unit integer index.
mismatch::Bool: flag of whether there was a mismatch in this iteration.

Method List / Definition Locations

log_art_stats!(art, bmu, mismatch)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/common.jl:160.

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Storage Operations

`replace_mat_index!`

AdaptiveResonance.replace_mat_index! — Function

replace_mat_index!(
    mat::AbstractMatrix{T} where T<:Real,
    vec::AbstractVector{T} where T<:Real,
    index::Integer
) -> AbstractVector{T} where T<:Real

Summary

Replaces a matrix element with a vector at the column index.

This function dispatches to the low-level replacement strategy.

Arguments

mat::RealMatrix: the matrix to update with a replaced column vector.
vec::RealVector: the vector to put in the matrix at the column index.
index::Integer: the column index to put the vector.

Method List / Definition Locations

replace_mat_index!(mat, vec, index)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/subroutines.jl:19.

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`unsafe_replace_mat_index!`

AdaptiveResonance.unsafe_replace_mat_index! — Function

unsafe_replace_mat_index!(
    mat::AbstractMatrix{T} where T<:Real,
    vec::AbstractVector{T} where T<:Real,
    index::Integer
) -> AbstractVector{T} where T<:Real

Summary

Low-level function for unsafely replacing a matrix column with a given vector.

Arguments

mat::RealMatrix: the matrix to update with a replaced column vector.
vec::RealVector: the vector to put in the matrix at the column index.
index::Integer: the column index to put the vector.

Method List / Definition Locations

unsafe_replace_mat_index!(mat, vec, index)

defined at /home/runner/work/AdaptiveResonance.jl/AdaptiveResonance.jl/src/lib/subroutines.jl:28.

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`accommodate_vector!`

AdaptiveResonance.accommodate_vector! — Function

accommodate_vector!(vec::Array{T, 1}, goal_len::Integer)

Summary

Extends a vector to a goal length with zeros of its element type to accommodate in-place updates.

Arguments

vec::Vector{T}: a vector of arbitrary element type.
goal_len::Integer: the length that the vector should be.

Method List / Definition Locations

accommodate_vector!(vec, goal_len)

Description

Common docstring for listing available activation functions.

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