class

Crystalla::Matrix

Inherits Crystalla::BlasHelper / Crystalla::LapackHelper / Reference / Object

Constructors

[](*values : Array(Number)) : Matrix
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new(values : Array(Float64), number_of_rows : Int32, number_of_cols : Int32)
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Class methods

columns(columns : Array(Array(Float64))) : Crystalla::Matrix
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columns(columns : Array(Array(Number))) : Crystalla::Matrix
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constant_matrix(value : Number, number_of_rows : Int32, number_of_cols : Int32) : Crystalla::Matrix
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diag(diagonal : Array(Number), number_of_rows : Int32, number_of_cols : Int32) : Crystalla::Matrix
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diag(diagonal : Array(Number)) : Crystalla::Matrix
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empty
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eye(number_of_rows : Int32, number_of_cols : Int32) : Crystalla::Matrix
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eye(number_of_rows_and_cols : Int32) : Crystalla::Matrix
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load(file : String) : Crystalla::Matrix
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ones(number_of_rows : Int32, number_of_cols : Int32) : Crystalla::Matrix
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rand(number_of_rows : Int32, number_of_cols : Int32, range : Range(Int32, Int32)) : Crystalla::Matrix
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rand(number_of_rows : Int32, number_of_cols : Int32) : Crystalla::Matrix
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rand_perm(n : Int32) : Crystalla::Matrix
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repeat_column(column : Array(Number), times : Int32) : Crystalla::Matrix
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repeat_row(row : Array(Number), times : Int32) : Crystalla::Matrix
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row_vector(values : Array(Number)) : Crystalla::Matrix
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rows(rows : Array(Array(Number)))
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validate_dimensions(number_of_rows, number_of_cols)
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zeros(number_of_rows : Int32, number_of_cols : Int32) : Crystalla::Matrix
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Instance methods

*(other : self) : Matrix
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+(other : self) : Matrix
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-(other : self) : Matrix
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-
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==(other : Matrix) : Bool
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[](rows : Range(Int32, Int32), cols : Range(Int32, Int32)) : Matrix
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[](row, col) : Float64
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[]=(row : Int32, col : Int32, value : Number)
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add_rows(index : Int32, rows : Matrix) : Matrix
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all_close(other : Matrix, absolute_tolerance = nil, relative_tolerance = nil) : Bool
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append(row : Matrix) : Matrix
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clone
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compare(other : Matrix, &) : Bool
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dimensions
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each_by_col
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each_by_row
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each_col
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each_row
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inspect(io)
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invert!
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mean
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mean_by_col
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mean_by_row
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number_of_cols
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number_of_rows
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pca_fit(n_components : Int32) : Transformations::PCA

Uses this matrix as a n_samples * n_features model to fit a PCA transformation with the specified number of components

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pca_transform(n_components : Int32) : Crystalla::Matrix

Uses this matrix as a n_samples * n_features model to fit a PCA transformation and reduces it to the specified number of components

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prepend(row : Matrix) : Matrix
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row_vector?
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shuffle_cols
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singular_values(count : Int32) : Array(Float64)
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singular_values
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solve(b : self) : Matrix
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square?
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svd(count : Int32) : Tuple(Matrix, Array(Float64), Matrix)
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svd
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to_s(io)
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to_unsafe
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trace

Returns the sum of the diagonal elements. Only useful for numeric matrices.

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transpose
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values
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zip_with(other : Matrix, &) : Matrix
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