Deborah.DeborahCore.XYMLVectorizer

gen_XY_ML(
    X_mat::AbstractArray{T,3},
    read_column::Int,
    conf_arr::AbstractVector{Int},
    X_label::String,
    overall_name::String,
    analysis_dir::String;
    use_avg::Bool = true,
    dump::Bool = true
) -> Vector{T}

Flatten a slice of a 3D input array into a 1D vector and optionally write it to a .dat file.

Arguments

• X_mat::AbstractArray{T,3}: Input data of shape $(\texttt{column\_idx}, N_\text{set}, N_\text{src})$
• read_column::Int: Index to select along the 1st dimension
• conf_arr::AbstractVector{Int}: Configuration number array, $\text{length} = N_\text{set}$
• X_label::String: Prefix for output filename
• overall_name::String: Suffix for output filename
• use_avg::Bool: If true, treat as averaged source data (jsrc = -1)
• dump::Bool: If true, write a .dat file

Returns

• Vector{T}: Flattened vector of selected component from X_mat

gen_XY_ML(
    X_mat::AbstractArray{T,2}, 
    conf_arr::AbstractVector{Int}, 
    X_label::String, 
    overall_name::String,
    analysis_dir::String; 
    use_avg::Bool=true, 
    dump::Bool=true
) -> Vector{T}

Convert a 2D input matrix into a flattened vector and optionally dump it to a .dat file for ML processing.

Arguments

• X_mat::AbstractArray{T,2}: Input matrix of shape $(N_\text{set}, N_\text{src})$.
• conf_arr::AbstractVector{Int}: Array of configuration indices, length $N_\text{set}$.
• X_label::String: Label prefix for the output file.
• overall_name::String: Suffix for the output file name.
• use_avg::Bool=true: If true, assumes averaged source and marks jsrc as -1.
• dump::Bool=true: Whether to write the output to a .dat file.

Returns

• Vector{T}: Flattened 1D array of input values.

mat_XY_ML(
    X_vec::AbstractVector{T}, 
    N_src::Int, 
    N_set::Int
) -> Matrix{T}

Reshape a flattened ML input vector into a 2D matrix of shape $(N_\text{set}, N_\text{src})$.

Arguments

• X_vec::AbstractVector{T}: Flattened 1D array ($\text{length} = N_\text{set} \times N_\text{src}$)
• N_src::Int: Number of sources (columns in output matrix)
• N_set::Int: Number of configurations (rows in output matrix)

Returns

• Matrix{T}: Reconstructed matrix of shape $(N_\text{set}, N_\text{src})$