Struct NDArray

pub struct NDArray<T> {
    pub shape: Shape,
    pub size: usize,
    pub rank: usize,
    pub values: Vec<T>,
}

Fields

shape: Shape

size: usize

rank: usize

values: Vec<T>

Implementations

impl<T: Default + Clone + Debug + PartialEq> NDArray<T>

pub fn rank(&self) -> usize

Gets the rank of the current array

pub fn shape(&self) -> &Shape

Returns the shape dimensions of the array

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

Get the generic values stored in the array

pub fn size(&self) -> usize

Get the current calculated size of the contigous array

pub fn get(&self, indices: Vec<usize>) -> &T

Get generic value from provided indices

pub fn idx(&self, index: usize) -> &T

Get generic value from provided indices

pub fn set_rank(&mut self, new_rank: usize)

Lets you change the rank of the current ndarray

pub fn new(shape: Vec<usize>) -> Result<NDArray<T>, String>

Create instance of NDArray, provide shape dimensions as parameter

pub fn array(shape: Vec<usize>, values: Vec<T>) -> Result<NDArray<T>, String>

Create instance of NDArray, provide shape dimensions and array values as parameter

pub fn fill(shape: Vec<usize>, value: T) -> Result<NDArray<T>, String>

Fill ndarray with values

pub fn reshape(&mut self, shape_vals: Vec<usize>) -> Result<(), String>

Reshape dimensions of array to new shape. Shape must match current size

pub fn index(&self, indices: Vec<usize>) -> Result<usize, String>

Get contigous index of array using provided indices as parameter

pub fn indices(&self, index: usize) -> Result<Vec<usize>, String>

Get indices from provided contigous index as parameter

pub fn set_idx(&mut self, idx: usize, value: T) -> Result<(), String>

Set index and generic value, index must be within size of array

pub fn set(&mut self, indices: Vec<usize>, value: T) -> Result<(), String>

Set generic value using provided indices. Indices must match rank of array

pub fn rows(&self, index: usize) -> Result<Vec<T>, String>

Get rows dimension associated with multi dimensional array

pub fn cols(&self, index: usize) -> Result<Vec<T>, String>

Get column dimension associated with multi dimensional array

pub fn axis(&self, axis: usize, index: usize) -> Result<NDArray<T>, String>

Get values from a specific axis/slice

pub fn axis_indices( &self, axis: usize, indices: Vec<usize>, ) -> Result<NDArray<T>, String>

Get mutiple axis values with provided indices

pub fn drop_axis(&self, axis: usize, index: usize) -> Result<NDArray<T>, String>

Drop specified axis of ndarray

pub fn batch(&self, batch_size: usize) -> Result<Vec<NDArray<T>>, String>

Batch ndarray in specified amount of chunks of rows, cols etc.

pub fn value_indices(&self, value: T) -> Vec<usize>

pub fn indice_query(&self, indices: Vec<usize>) -> Result<NDArray<T>, String>

pub fn split( &self, axis: usize, percentage: f64, ) -> Result<(NDArray<T>, NDArray<T>), String>

Trait Implementations

impl AggregateOps for NDArray<f64>

fn avg(&self) -> f64

Take the average of all elements in ndarray structure

fn length(&self) -> f64

Computes the length or magnitude of vector

fn square(&self) -> Result<NDArray<f64>, String>

Raise all elements to the second power

fn sum(&self) -> Result<NDArray<f64>, String>

sum all elements in ndarray structure

fn abs(&self) -> Result<NDArray<f64>, String>

Get the absolute value of each element in ndarray

fn sort(&self) -> Vec<f64>

Sort values in ndarray on specific axis

fn unique(&self) -> Vec<f64>

Get unique values in ndarray

fn mean(&self, axis: usize) -> Result<Vec<f64>, String>

Calculate the mean of values along a specific axis

fn stdev(&self, axis: usize) -> Result<Vec<f64>, String>

Calculate the mean of values along a specific axis

fn stdev_sample(&self, axis: usize) -> Result<Vec<f64>, String>

Calculate the mean of values along a specific axis

impl BinaryOps for NDArray<f64>

fn mult(&self, other: NDArray<f64>) -> Result<NDArray<f64>, String>

Multiply an ndarray by another

fn add(&self, value: NDArray<f64>) -> Result<NDArray<f64>, String>

Add two NDArray’s and get resulting NDArray instance

fn subtract(&self, value: NDArray<f64>) -> Result<NDArray<f64>, String>

Subtract values in NDArray instances

fn dot(&self, input: NDArray<f64>) -> Result<NDArray<f64>, String>

Perform dot product of current NDArray on another NDArray instance

fn scale_add(&self, value: NDArray<f64>) -> Result<NDArray<f64>, String>

Add values by scalar for current NDArray instance

fn scale_mult(&self, value: NDArray<f64>) -> Result<NDArray<f64>, String>

Elementwise multiplication of ndarray

fn save(&self, filepath: &str) -> Result<()>

Save instance of NDArray to json file with serialized values

fn load(filepath: &str) -> Result<NDArray<f64>>

Load Instance of saved NDarray, serialize to NDArray structure

impl<T: Clone> Clone for NDArray<T>

fn clone(&self) -> NDArray<T>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T: Debug> Debug for NDArray<T>

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

Formats the value using the given formatter.

impl<'de, T> Deserialize<'de> for NDArray<T>

where T: Deserialize<'de>,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<T: PartialEq> PartialEq for NDArray<T>

fn eq(&self, other: &NDArray<T>) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl ScalarOps for NDArray<f64>

fn scalar_subtract(&self, scalar: f64) -> Result<NDArray<f64>, String>

Subtract all values in ndarray by scalar

fn scalar_add(&self, scalar: f64) -> Result<NDArray<f64>, String>

Add all values in ndarray by scalar

fn scalar_mult(&self, scalar: f64) -> Result<NDArray<f64>, String>

Multiply all values in ndarray by scalar

fn scalar_div(&self, scalar: f64) -> Result<NDArray<f64>, String>

Divide all values in ndarray by scalar

impl<T> Serialize for NDArray<T>

where T: Serialize,

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl UnaryOps for NDArray<f64>

fn transpose(self) -> Result<NDArray<f64>, String>

Tranpose current NDArray instance, works only on rank 2 values

fn permute(self, indice_order: Vec<usize>) -> Result<NDArray<f64>, String>

Permute indices of NDArray. Can be used to peform transposes/contraction on rank 3 or higher values.

fn norm(&self, p: usize) -> Result<NDArray<f64>, String>

L2 norm can also be x^t x

fn signum(&self) -> Result<NDArray<f64>, String>

Adds values based on x < 0 < 1

fn sum_axis(&self, axis: usize) -> Result<NDArray<f64>, String>

Sum values along a specified axis

fn select_axis( &self, axis: usize, indices: Vec<usize>, ) -> Result<NDArray<f64>, String>

Select specific indices from an axis

fn apply( &self, loss_func: fn(value: f64) -> f64, ) -> Result<NDArray<f64>, String>

Apply loss function on values in ndarray

fn argmax(&self, axis: usize) -> NDArray<f64>

Get’s the maximum values index along a specified axis

fn argmin(&self, axis: usize) -> Result<NDArray<f64>, String>

Get’s the minimum values index along a specified axis

fn nonzero(&self) -> NDArray<f64>

Retrieve all non zero elements in an ndarray

impl<T> StructuralPartialEq for NDArray<T>