/**
 * @file src/tableau/sparse-matrix.ts
 * @description Compressed Sparse Column (CSC) matrix implementation
 *
 * Optimized for column operations which are frequent in the simplex algorithm.
 * Provides O(nnz) pivot operations instead of O(n*m) for dense matrices.
 *
 * CSC Storage Format:
 * - values: non-zero values stored column by column
 * - rowIndices: row index for each value
 * - colPointers: starting index in values/rowIndices for each column
 *
 * Column c's entries are at indices colPointers[c] to colPointers[c+1]-1
 */
export interface SparseVector {
    indices: number[];
    values: number[];
    length: number;
}
export declare class SparseMatrix {
    values: number[];
    rowIndices: number[];
    colPointers: number[];
    nRows: number;
    nCols: number;
    private precision;
    private workVector;
    private workIndices;
    constructor(nRows: number, nCols: number, precision?: number);
    /**
     * Create sparse matrix from dense Float64Array
     */
    static fromDense(dense: Float64Array, width: number, height: number, precision?: number): SparseMatrix;
    /**
     * Convert to dense Float64Array
     */
    toDense(): Float64Array;
    /**
     * Get value at (row, col)
     */
    get(row: number, col: number): number;
    /**
     * Set value at (row, col)
     * Handles insertion and removal of entries
     */
    set(row: number, col: number, value: number): void;
    /**
     * Get column as sparse vector
     */
    getColumn(col: number): SparseVector;
    /**
     * Get row as sparse vector (less efficient - requires full scan)
     */
    getRow(row: number): SparseVector;
    /**
     * Get row into pre-allocated dense array (more efficient for repeated access)
     * Returns array of non-zero column indices
     */
    getRowDense(row: number, output: Float64Array): number[];
    /**
     * Add a new row (expands matrix vertically)
     */
    addRow(): void;
    /**
     * Add a new column (expands matrix horizontally)
     */
    addColumn(): void;
    /**
     * Set entire column from sparse vector
     */
    setColumn(col: number, sparseCol: SparseVector): void;
    /**
     * Number of non-zero entries
     */
    get nnz(): number;
    /**
     * Density (fraction of non-zeros)
     */
    get density(): number;
    /**
     * Scale a row by a factor
     */
    scaleRow(row: number, factor: number): void;
    /**
     * Add scaled row to another row: targetRow += factor * sourceRow
     * This is the core operation in Gaussian elimination / pivot
     */
    addScaledRow(targetRow: number, sourceRow: number, factor: number): void;
    /**
     * Perform pivot operation at (pivotRow, pivotCol)
     * This is optimized for sparse operations
     */
    pivot(pivotRow: number, pivotCol: number): number[];
    /**
     * Clone the matrix
     */
    clone(): SparseMatrix;
}