Struct smartcore::linalg::naive::dense_matrix::DenseMatrix

pub struct DenseMatrix<T: RealNumber> { /* fields omitted */ }

Column-major, dense matrix. See Simple Dense Matrix.

Implementations

impl<T: RealNumber> DenseMatrix<T>

pub fn new(nrows: usize, ncols: usize, values: Vec<T>) -> Self

Create new instance of DenseMatrix without copying data. values should be in column-major order.

pub fn from_2d_array(values: &[&[T]]) -> Self

New instance of DenseMatrix from 2d array.

pub fn from_2d_vec(values: &Vec<Vec<T>>) -> Self

New instance of DenseMatrix from 2d vector.

pub fn from_array(nrows: usize, ncols: usize, values: &[T]) -> Self

Creates new matrix from an array.

• nrows - number of rows in new matrix.
• ncols - number of columns in new matrix.
• values - values to initialize the matrix.

pub fn from_vec(nrows: usize, ncols: usize, values: &[T]) -> DenseMatrix<T>

Creates new matrix from a vector.

• nrows - number of rows in new matrix.
• ncols - number of columns in new matrix.
• values - values to initialize the matrix.

pub fn row_vector_from_array(values: &[T]) -> Self

Creates new row vector (1xN matrix) from an array.

• values - values to initialize the matrix.

pub fn row_vector_from_vec(values: Vec<T>) -> Self

Creates new row vector (1xN matrix) from a vector.

• values - values to initialize the matrix.

pub fn column_vector_from_array(values: &[T]) -> Self

Creates new column vector (1xN matrix) from an array.

• values - values to initialize the matrix.

pub fn column_vector_from_vec(values: Vec<T>) -> Self

Creates new column vector (1xN matrix) from a vector.

• values - values to initialize the matrix.

pub fn iter(&self) -> DenseMatrixIterator<'_, T>

Creates new column vector (1xN matrix) from a vector.

• values - values to initialize the matrix.

Trait Implementations

impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T>

type RowVector = Vec<T>

Row vector that is associated with this matrix type, e.g. if we have an implementation of sparce matrix we should have an associated sparce vector type that represents a row in this matrix.

pub fn from_row_vector(vec: Self::RowVector) -> Self

Transforms row vector vec into a 1xM matrix.

pub fn to_row_vector(self) -> Self::RowVector

Transforms 1-d matrix of 1xM into a row vector.

pub fn get(&self, row: usize, col: usize) -> T

Get an element of the matrix.

pub fn get_row(&self, row: usize) -> Self::RowVector

Get the row'th row

pub fn get_row_as_vec(&self, row: usize) -> Vec<T>

Get a vector with elements of the row'th row

pub fn copy_row_as_vec(&self, row: usize, result: &mut Vec<T>)

Copies a vector with elements of the row'th row into result

pub fn get_col_as_vec(&self, col: usize) -> Vec<T>

Get a vector with elements of the col'th column

pub fn copy_col_as_vec(&self, col: usize, result: &mut Vec<T>)

Copies a vector with elements of the col'th column into result

pub fn set(&mut self, row: usize, col: usize, x: T)

Set an element at col, row to x

pub fn zeros(nrows: usize, ncols: usize) -> Self

Create new matrix with zeros of size nrows by ncols.

pub fn ones(nrows: usize, ncols: usize) -> Self

Create new matrix with ones of size nrows by ncols.

pub fn eye(size: usize) -> Self

Create an identity matrix of size size

pub fn shape(&self) -> (usize, usize)

Return the shape of an array.

pub fn v_stack(&self, other: &Self) -> Self

Stack arrays in sequence horizontally (column wise).

pub fn h_stack(&self, other: &Self) -> Self

Stack arrays in sequence vertically (row wise).

pub fn matmul(&self, other: &Self) -> Self

Matrix product.

pub fn dot(&self, other: &Self) -> T

Vector dot product Both matrices should be of size 1xM

pub fn slice(&self, rows: Range<usize>, cols: Range<usize>) -> Self

Return a slice of the matrix.

pub fn approximate_eq(&self, other: &Self, error: T) -> bool

Returns True if matrices are element-wise equal within a tolerance error.

pub fn fill(nrows: usize, ncols: usize, value: T) -> Self

Create new matrix of size nrows by ncols where each element is set to value.

pub fn add_mut(&mut self, other: &Self) -> &Self

Add matrices, element-wise, overriding original matrix with result.

pub fn sub_mut(&mut self, other: &Self) -> &Self

Subtract matrices, element-wise, overriding original matrix with result.

pub fn mul_mut(&mut self, other: &Self) -> &Self

Multiply matrices, element-wise, overriding original matrix with result.

pub fn div_mut(&mut self, other: &Self) -> &Self

Divide matrices, element-wise, overriding original matrix with result.

pub fn div_element_mut(&mut self, row: usize, col: usize, x: T)

Divide single element of the matrix by x, write result to original matrix.

pub fn mul_element_mut(&mut self, row: usize, col: usize, x: T)

Multiply single element of the matrix by x, write result to original matrix.

pub fn add_element_mut(&mut self, row: usize, col: usize, x: T)

Add single element of the matrix to x, write result to original matrix.

pub fn sub_element_mut(&mut self, row: usize, col: usize, x: T)

Subtract x from single element of the matrix, write result to original matrix.

pub fn transpose(&self) -> Self

Reverse or permute the axes of the matrix, return new matrix.

pub fn rand(nrows: usize, ncols: usize) -> Self

Create new nrows by ncols matrix and populate it with random samples from a uniform distribution over [0, 1).

pub fn norm2(&self) -> T

Returns L2 norm.

pub fn norm(&self, p: T) -> T

Returns matrix norm of order p.

pub fn column_mean(&self) -> Vec<T>

Returns the average of the matrix columns.

pub fn add_scalar_mut(&mut self, scalar: T) -> &Self

Add scalar to the matrix, override original matrix with result.

pub fn sub_scalar_mut(&mut self, scalar: T) -> &Self

Subtract scalar from the elements of matrix, override original matrix with result.

pub fn mul_scalar_mut(&mut self, scalar: T) -> &Self

Multiply scalar by the elements of matrix, override original matrix with result.

pub fn div_scalar_mut(&mut self, scalar: T) -> &Self

Divide elements of the matrix by scalar, override original matrix with result.

pub fn negative_mut(&mut self)

Numerical negative, element-wise. Overrides original matrix.

pub fn reshape(&self, nrows: usize, ncols: usize) -> Self

Returns new matrix of shape nrows by ncols with data copied from original matrix.

pub fn copy_from(&mut self, other: &Self)

Copies content of other matrix.

pub fn abs_mut(&mut self) -> &Self

Calculate the absolute value element-wise. Overrides original matrix.

pub fn max_diff(&self, other: &Self) -> T

Calculates max(|a - b|) of two matrices

pub fn sum(&self) -> T

Calculates sum of all elements of the matrix.

pub fn max(&self) -> T

Calculates max of all elements of the matrix.

pub fn min(&self) -> T

Calculates min of all elements of the matrix.

pub fn softmax_mut(&mut self)

Calculates Softmax function. Overrides the matrix with result.

pub fn pow_mut(&mut self, p: T) -> &Self

Raises elements of the matrix to the power of p

pub fn argmax(&self) -> Vec<usize>

Returns the indices of the maximum values in each row.

pub fn unique(&self) -> Vec<T>

Returns vector with unique values from the matrix.

pub fn cov(&self) -> Self

Calculates the covariance matrix

pub fn add(&self, other: &Self) -> Self

Add matrices, element-wise

pub fn sub(&self, other: &Self) -> Self

Subtract matrices, element-wise

pub fn mul(&self, other: &Self) -> Self

Multiply matrices, element-wise

pub fn div(&self, other: &Self) -> Self

Divide matrices, element-wise

pub fn add_scalar(&self, scalar: T) -> Self

Add scalar to the matrix.

pub fn sub_scalar(&self, scalar: T) -> Self

Subtract scalar from the elements of matrix.

pub fn mul_scalar(&self, scalar: T) -> Self

Multiply scalar by the elements of matrix.

pub fn div_scalar(&self, scalar: T) -> Self

Divide elements of the matrix by scalar.

pub fn negative(&self) -> Self

Numerical negative, element-wise.

pub fn abs(&self) -> Self

Calculate the absolute value element-wise.

pub fn pow(&mut self, p: T) -> Self

Returns new matrix with elements raised to the power of p

pub fn take(&self, index: &[usize], axis: u8) -> Self

Take elements from an array along an axis.

impl<T: RealNumber> CholeskyDecomposableMatrix<T> for DenseMatrix<T>

pub fn cholesky(&self) -> Result<Cholesky<T, Self>, Failed>

Compute the Cholesky decomposition of a matrix.

pub fn cholesky_mut(self) -> Result<Cholesky<T, Self>, Failed>

Compute the Cholesky decomposition of a matrix. The input matrix will be used for factorization.

pub fn cholesky_solve_mut(self, b: Self) -> Result<Self, Failed>

Solves Ax = b

impl<T: Clone + RealNumber> Clone for DenseMatrix<T>

pub fn clone(&self) -> DenseMatrix<T>

Returns a copy of the value.

pub fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<T: Debug + RealNumber> Debug for DenseMatrix<T>

pub fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de, T: RealNumber + Debug + Deserialize<'de>> Deserialize<'de> for DenseMatrix<T>

pub fn deserialize<D>(deserializer: D) -> Result<Self, D::Error> where
    D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl<T: RealNumber> Display for DenseMatrix<T>

pub fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<T: RealNumber> EVDDecomposableMatrix<T> for DenseMatrix<T>

pub fn evd(&self, symmetric: bool) -> Result<EVD<T, Self>, Failed>

Compute the eigen decomposition of a square matrix.

pub fn evd_mut(self, symmetric: bool) -> Result<EVD<T, Self>, Failed>

Compute the eigen decomposition of a square matrix. The input matrix will be used for factorization.

impl<T: RealNumber> HighOrderOperations<T> for DenseMatrix<T>

pub fn ab(&self, a_transpose: bool, b: &Self, b_transpose: bool) -> Self

Y = AB

impl<T: RealNumber> Into<Vec<T, Global>> for DenseMatrix<T>

pub fn into(self) -> Vec<T>

Performs the conversion.

impl<T: RealNumber> LUDecomposableMatrix<T> for DenseMatrix<T>

pub fn lu(&self) -> Result<LU<T, Self>, Failed>

Compute the LU decomposition of a square matrix.

pub fn lu_mut(self) -> Result<LU<T, Self>, Failed>

Compute the LU decomposition of a square matrix. The input matrix will be used for factorization.

pub fn lu_solve_mut(self, b: Self) -> Result<Self, Failed>

Solves Ax = b

impl<T: RealNumber> Matrix<T> for DenseMatrix<T>

impl<T: RealNumber> MatrixPreprocessing<T> for DenseMatrix<T>

pub fn binarize_mut(&mut self, threshold: T)

Each element of the matrix greater than the threshold becomes 1, while values less than or equal to the threshold become 0

pub fn binarize(&self, threshold: T) -> Self

Returns new matrix where elements are binarized according to a given threshold.

impl<T: RealNumber> MatrixStats<T> for DenseMatrix<T>

pub fn mean(&self, axis: u8) -> Vec<T>

Computes the arithmetic mean along the specified axis.

pub fn var(&self, axis: u8) -> Vec<T>

Computes variance along the specified axis.

pub fn std(&self, axis: u8) -> Vec<T>

Computes the standard deviation along the specified axis.

pub fn scale_mut(&mut self, mean: &[T], std: &[T], axis: u8)

standardize values by removing the mean and scaling to unit variance

impl<T: RealNumber> PartialEq<DenseMatrix<T>> for DenseMatrix<T>

pub fn eq(&self, other: &Self) -> bool

This method tests for self and other values to be equal, and is used by ==.

#[must_use]pub fn ne(&self, other: &Rhs) -> bool

This method tests for !=.

impl<T: RealNumber> QRDecomposableMatrix<T> for DenseMatrix<T>

pub fn qr(&self) -> Result<QR<T, Self>, Failed>

Compute the QR decomposition of a matrix.

pub fn qr_mut(self) -> Result<QR<T, Self>, Failed>

Compute the QR decomposition of a matrix. The input matrix will be used for factorization.

pub fn qr_solve_mut(self, b: Self) -> Result<Self, Failed>

Solves Ax = b

impl<T: RealNumber> SVDDecomposableMatrix<T> for DenseMatrix<T>

pub fn svd_solve_mut(self, b: Self) -> Result<Self, Failed>

Solves Ax = b. Overrides original matrix in the process.

pub fn svd_solve(&self, b: Self) -> Result<Self, Failed>

Solves Ax = b

pub fn svd(&self) -> Result<SVD<T, Self>, Failed>

Compute the SVD decomposition of a matrix.

pub fn svd_mut(self) -> Result<SVD<T, Self>, Failed>

Compute the SVD decomposition of a matrix. The input matrix will be used for factorization.

impl<T: RealNumber + Debug + Serialize> Serialize for DenseMatrix<T>

pub fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error> where
    S: Serializer, 

Serialize this value into the given Serde serializer.