csvbinmatrix 0.8.0

Binary matrix Compressed Sparse Vector
Documentation 
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#![doc = include_str!("../../docs/matrix/views.md")]

use super::CSVBinaryMatrix;

impl CSVBinaryMatrix {
    /// Returns the number of cells.
    #[must_use]
    pub fn number_of_cells(&self) -> usize {
        self.number_of_rows * self.number_of_columns
    }

    /// Returns the number of ones.
    #[must_use]
    pub fn number_of_ones(&self) -> usize {
        self.distances.len() - 1
    }

    /// Returns the number of zeros.
    #[must_use]
    pub fn number_of_zeros(&self) -> usize {
        self.number_of_rows * self.number_of_columns - self.number_of_ones()
    }

    /// Returns the sparsity of the matrix.
    ///
    /// The sparsity is the ratio of the number of zeros to the number of cells.
    #[must_use]
    pub fn sparsity(&self) -> f64 {
        let number_of_cells = self.number_of_rows * self.number_of_columns;
        #[allow(clippy::cast_precision_loss)]
        {
            1.0 - ((self.distances.len() - 1) as f64 / number_of_cells as f64)
        }
    }

    /// Returns the density of the matrix.
    ///
    /// The density is the ratio of the number of ones to the number of cells.
    #[must_use]
    pub fn density(&self) -> f64 {
        let number_of_cells = self.number_of_rows * self.number_of_columns;
        #[allow(clippy::cast_precision_loss)]
        {
            (self.distances.len() - 1) as f64 / number_of_cells as f64
        }
    }

    /// Returns `true` if the matrix is complete or all-ones.
    #[must_use]
    pub fn is_complete(&self) -> bool {
        self.number_of_ones() == self.number_of_rows * self.number_of_columns
    }

    /// Returns `true` if the matrix is empty or all-zeros.
    #[must_use]
    pub fn is_empty(&self) -> bool {
        self.number_of_ones() == 0
    }
}

#[cfg(test)]
mod tests {

    use pretty_assertions::assert_eq;
    use rstest::rstest;

    use super::super::tests::{matrix_a, ones_matrix, zeros_matrix};
    use super::super::CSVBinaryMatrix;

    #[rstest]
    fn number_of_cells(matrix_a: CSVBinaryMatrix) {
        assert_eq!(matrix_a.number_of_cells(), 9);
    }

    #[rstest]
    fn number_of_ones(zeros_matrix: CSVBinaryMatrix, matrix_a: CSVBinaryMatrix) {
        assert_eq!(zeros_matrix.number_of_ones(), 0);
        assert_eq!(matrix_a.number_of_ones(), 5);
    }

    #[rstest]
    fn number_of_zeros(zeros_matrix: CSVBinaryMatrix, matrix_a: CSVBinaryMatrix) {
        assert_eq!(zeros_matrix.number_of_zeros(), 9);
        assert_eq!(matrix_a.number_of_zeros(), 4);
    }

    #[rstest]
    fn sparsity(
        zeros_matrix: CSVBinaryMatrix,
        ones_matrix: CSVBinaryMatrix,
        matrix_a: CSVBinaryMatrix,
    ) {
        let error_margin = f64::EPSILON;
        assert!((1.0 - zeros_matrix.sparsity()).abs() < error_margin);
        assert!(ones_matrix.sparsity() < error_margin);
        assert!((0.444_444_444_444_444_4 - matrix_a.sparsity()).abs() < error_margin);
    }

    #[rstest]
    fn density(
        zeros_matrix: CSVBinaryMatrix,
        ones_matrix: CSVBinaryMatrix,
        matrix_a: CSVBinaryMatrix,
    ) {
        let error_margin = f64::EPSILON;
        assert!(zeros_matrix.density() < error_margin);
        assert!((1.0 - ones_matrix.density()).abs() < error_margin);
        assert!((0.555_555_555_555_555_6 - matrix_a.density()).abs() < error_margin);
    }

    #[rstest]
    fn is_complete(zeros_matrix: CSVBinaryMatrix, ones_matrix: CSVBinaryMatrix) {
        assert!(!zeros_matrix.is_complete());
        assert!(ones_matrix.is_complete());
    }

    #[rstest]
    fn is_empty(zeros_matrix: CSVBinaryMatrix, ones_matrix: CSVBinaryMatrix) {
        assert!(zeros_matrix.is_empty());
        assert!(!ones_matrix.is_empty());
    }
}