Struct rustlearn::array::dense::Array

pub struct Array { /* fields omitted */ }

Basic two-dimensional dense matrix type.

Methods

impl Array

pub fn zeros(rows: usize, cols: usize) -> Array

Create a rows by cols array of zeros.

pub fn ones(rows: usize, cols: usize) -> Array

Create a rows by cols array of ones.

pub fn reshape(&mut self, rows: usize, cols: usize)

Change the shape of the array to rows by cols.

Panics

If the number of elements implied by the new shape is different from the current number of elements.

pub fn order(&self) -> &MatrixOrder

Return the order (row-major or column-major) of the array.

pub fn data(&self) -> &Vec<f32>

Return an immutable reference to the underlying data buffer of the array.

The arrangement of the elements in that vector is dependent on whether this is a row-major or a column-major array.

pub fn as_slice(&self) -> &[f32]

Return an immutable reference to the underlying data buffer of the array.

The arrangement of the elements in that vector is dependent on whether this is a row-major or a column-major array.

pub fn as_mut_slice(&mut self) -> &mut [f32]

Return an mutable reference to the underlying data buffer of the array.

The arrangement of the elements in that vector is dependent on whether this is a row-major or a column-major array.

pub fn T(self) -> Array

Transpose the matrix.

pub fn sum(&self) -> f32

Compute the sum of the entries of the array.

pub fn mean(&self) -> f32

Compute the mean of the array.

Trait Implementations

impl Encodable for Array

fn encode<__S: Encoder>(&self, __arg_0: &mut __S) -> Result<(), __S::Error>

Serialize a value using an Encoder.

impl Decodable for Array

fn decode<__D: Decoder>(__arg_0: &mut __D) -> Result<Array, __D::Error>

Deserialize a value using a Decoder.

impl Clone for Array

fn clone(&self) -> Array

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Array

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.

impl<'a> RowIterable for &'a Array

type Item = ArrayView<'a>

type Output = ArrayIterator<'a>

Important traits for ArrayIterator<'a>

impl<'a> Iterator for ArrayIterator<'a> type Item = ArrayView<'a>;

fn iter_rows(self) -> ArrayIterator<'a>

Iterate over rows of the matrix.

fn view_row(self, idx: usize) -> ArrayView<'a>

View a row of the matrix.

Important traits for ArrayIterator<'a>

impl<'a> Iterator for ArrayIterator<'a> type Item = ArrayView<'a>;

fn iter_rows_range(self, range: Range<usize>) -> ArrayIterator<'a>

Iterate over a subset of rows of the matrix.

impl<'a> ColumnIterable for &'a Array

type Item = ArrayView<'a>

type Output = ArrayIterator<'a>

Important traits for ArrayIterator<'a>

impl<'a> Iterator for ArrayIterator<'a> type Item = ArrayView<'a>;

fn iter_columns(self) -> ArrayIterator<'a>

Iterate over columns of a the matrix.

fn view_column(self, idx: usize) -> ArrayView<'a>

View a column of the matrix.

Important traits for ArrayIterator<'a>

impl<'a> Iterator for ArrayIterator<'a> type Item = ArrayView<'a>;

fn iter_columns_range(self, range: Range<usize>) -> ArrayIterator<'a>

Iterate over a subset of columns of the matrix.

impl IndexableMatrix for Array

fn rows(&self) -> usize

Return the number of rows of the matrix.

fn cols(&self) -> usize

Return the number of columns of the matrix.

unsafe fn get_unchecked(&self, row: usize, col: usize) -> f32

Get the value of the entry at (row, column) without bounds checking.

unsafe fn get_unchecked_mut(&mut self, row: usize, col: usize) -> &mut f32

Get a mutable reference to the value of the entry at (row, column) without bounds checking.

fn get(&self, row: usize, column: usize) -> f32

Get the value of the entry at (row, column).

fn get_mut(&mut self, row: usize, column: usize) -> &mut f32

Get a mutable reference to value of the entry at (row, column).

fn set(&mut self, row: usize, column: usize, value: f32)

Set the value of the entry at (row, column) to value.

unsafe fn set_unchecked(&mut self, row: usize, column: usize, value: f32)

Set the value of the entry at (row, column) to value without bounds checking.

impl From<Vec<f32>> for Array

fn from(data: Vec<f32>) -> Array

Construct an array from a vector.

Panics

This will panic if the input vector is emtpy.

impl<'a> From<&'a Vec<Vec<f32>>> for Array

fn from(input: &Vec<Vec<f32>>) -> Array

Construct an array from a vector of vectors.

Panics

This will panic if the input vector is emtpy or if its rows are of unequal length.

impl ElementwiseArrayOps<f32> for Array

type Output = Array

fn add(&self, rhs: f32) -> Array

fn add_inplace(&mut self, rhs: f32)

fn sub(&self, rhs: f32) -> Array

fn sub_inplace(&mut self, rhs: f32)

fn times(&self, rhs: f32) -> Array

fn times_inplace(&mut self, rhs: f32)

fn div(&self, rhs: f32) -> Array

fn div_inplace(&mut self, rhs: f32)

impl<'a> ElementwiseArrayOps<&'a Array> for Array

Perform elementwise operations between two arrays.

Panics

Will panic if the two operands are not of the same shape.

type Output = Array

fn add(&self, rhs: &'a Array) -> Array

fn add_inplace(&mut self, rhs: &'a Array)

fn sub(&self, rhs: &'a Array) -> Array

fn sub_inplace(&mut self, rhs: &'a Array)

fn times(&self, rhs: &'a Array) -> Array

fn times_inplace(&mut self, rhs: &'a Array)

fn div(&self, rhs: &'a Array) -> Array

fn div_inplace(&mut self, rhs: &'a Array)

impl<'a> Dot<&'a Array> for Array

type Output = Array

fn dot(&self, rhs: &'a Array) -> Array

impl RowIndex<Vec<usize>> for Array

type Output = Array

fn get_rows(&self, index: &Vec<usize>) -> Array

impl<'a> From<&'a Array> for SparseRowArray

fn from(array: &Array) -> SparseRowArray

Performs the conversion.

impl<'a> From<&'a Array> for SparseColumnArray

fn from(array: &Array) -> SparseColumnArray

Performs the conversion.

impl<'a> SupervisedModel<&'a Array> for RandomForest

fn fit(&mut self, X: &Array, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &Array) -> Result<Array, &'static str>

fn predict(&self, x: T) -> Result<Array, &'static str>

impl<'a> SupervisedModel<&'a Array> for SGDClassifier

fn fit(&mut self, X: &Array, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &Array) -> Result<Array, &'static str>

fn predict(&self, x: T) -> Result<Array, &'static str>

impl<'a> ParallelPredict<&'a Array> for SGDClassifier

fn decision_function_parallel(
    &self,
    X: &Array,
    num_threads: usize
) -> Result<Array, &'static str>

fn predict_parallel(
    &self,
    X: T,
    num_threads: usize
) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a Array> + Clone> SupervisedModel<&'a Array> for OneVsRestWrapper<T>

fn fit(&mut self, X: &'a Array, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &'a Array) -> Result<Array, &'static str>

fn predict(&self, X: &'a Array) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a Array> + Clone + Sync> ParallelPredict<&'a Array> for OneVsRestWrapper<T>

fn decision_function_parallel(
    &self,
    X: &'a Array,
    num_threads: usize
) -> Result<Array, &'static str>

fn predict_parallel(
    &self,
    X: &'a Array,
    num_threads: usize
) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a Array> + Clone + Sync + Send> ParallelSupervisedModel<&'a Array> for OneVsRestWrapper<T>

fn fit_parallel(
    &mut self,
    X: &'a Array,
    y: &Array,
    num_threads: usize
) -> Result<(), &'static str>

impl<'a> SupervisedModel<&'a Array> for DecisionTree

fn fit(&mut self, X: &Array, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &Array) -> Result<Array, &'static str>

fn predict(&self, x: T) -> Result<Array, &'static str>

impl<'a> SupervisedModel<&'a Array> for SVC

fn fit(&mut self, X: &Array, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &Array) -> Result<Array, &'static str>

fn predict(&self, X: &Array) -> Result<Array, &'static str>