Crate ndarray

Expand description

The ndarray crate provides an n-dimensional container for general elements and for numerics.

In n-dimensional we include for example 1-dimensional rows or columns, 2-dimensional matrices, and higher dimensional arrays. If the array has n dimensions, then an element in the array is accessed by using that many indices. Each dimension is also called an axis.

ArrayBase: The n-dimensional array type itself.
It is used to implement both the owned arrays and the views; see its docs for an overview of all array features.
The main specific array type is Array, which owns its elements.

Highlights

Generic n-dimensional array
Slicing, also with arbitrary step size, and negative indices to mean elements from the end of the axis.
Views and subviews of arrays; iterators that yield subviews.
Higher order operations and arithmetic are performant
Array views can be used to slice and mutate any [T] data using ArrayView::from and ArrayViewMut::from.
Zip for lock step function application across two or more arrays or other item producers (NdProducer trait).

Crate Status

Still iterating on and evolving the crate
- The crate is continuously developing, and breaking changes are expected during evolution from version to version. We adopt the newest stable rust features if we need them.
- Note that functions/methods/traits/etc. hidden from the docs are not considered part of the public API, so changes to them are not considered breaking changes.
Performance:
- Prefer higher order methods and arithmetic operations on arrays first, then iteration, and as a last priority using indexed algorithms.
- The higher order functions like .map(), .map_inplace(), .zip_mut_with(), Zip and azip!() are the most efficient ways to perform single traversal and lock step traversal respectively.
- Performance of an operation depends on the memory layout of the array or array view. Especially if it’s a binary operation, which needs matching memory layout to be efficient (with some exceptions).
- Efficient floating point matrix multiplication even for very large matrices; can optionally use BLAS to improve it further.
- See also the ndarray-parallel crate for integration with rayon.
Requires Rust 1.27

Crate Feature Flags

The following crate feature flags are available. They are configured in your Cargo.toml.

rustc-serialize
- Optional, compatible with Rust stable
- Enables serialization support for rustc-serialize 0.3
serde-1
- Optional, compatible with Rust stable
- Enables serialization support for serde 1.0
blas
- Optional and experimental, compatible with Rust stable
- Enable transparent BLAS support for matrix multiplication. Uses blas-src for pluggable backend, which needs to be configured separately.

Documentation

The docs for ArrayBase provide an overview of the n-dimensional array type. Other good pages to look at are the documentation for the s![] and azip!() macros.
If you have experience with NumPy, you may also be interested in ndarray_for_numpy_users.

Re-exports

pub use self::OwnedArcRepr as OwnedRcRepr;

Modules

Standalone documentation pages.

Producers, iterables and iterators.

Linear algebra.

ndarray prelude.

Macros

Create an Array with one, two or three dimensions.

Array zip macro: lock step function application across several arrays and producers.

Slice argument constructor.

Stack arrays along the given axis.

Structs

An n-dimensional array.

An axis index.

AxisDescription

Description of the axis, its length and its stride.

Dimension description.

Dynamic dimension or index type.

ArcArray’s representation.

Array’s representation.

A contiguous array shape of n dimensions.

An error related to array shape or layout.

A slice (range with step size).

Represents all of the necessary information to perform a slice.

An array shape of n dimensions in c-order, f-order or custom strides.

Array view’s representation.

Lock step function application across several arrays or other producers.

Enums

Error code for an error related to array shape or layout.

Value controlling the execution of .fold_while on Zip.

A slice (range with step) or an index.

Traits

Argument conversion into an array view

Array representation trait.

Array representation trait.

Array representation trait.

Array representation trait.

Array representation trait.

Array shape and index trait.

FixedInitializer

Fixed-size array used for array initialization

Extra indexing methods for array views

Argument conversion a dimension.

Argument conversion into a producer.

Elements that support linear algebra operations.

Floating-point element types f32 and f64.

Tuple or fixed size arrays that can be used to index an array.

A producer of an n-dimensional set of elements; for example an array view, mutable array view or an iterator that yields chunks.

Array shape with a next smaller dimension.

Elements that can be used as direct operands in arithmetic with arrays.

A trait for Shape and D where D: Dimension that allows customizing the memory layout (strides) of an array shape.

Functions

Create a new dimension value.

Create a zero-dimensional index

Create a one-dimensional index

Create a two-dimensional index

Create a three-dimensional index

Create a four-dimensional index

Create a five-dimensional index

Create a six-dimensional index

Create a dynamic-dimensional index

Create a zero-dimensional array with the element x.

Create a one-dimensional array with elements from xs.

Create a two-dimensional array with elements from xs.

Create a three-dimensional array with elements from xs.

Create a zero-dimensional array view borrowing x.

Create a one-dimensional array view with elements borrowing xs.

Create a two-dimensional array view with elements borrowing xs.

Create a one-dimensional read-write array view with elements borrowing xs.

Create a two-dimensional read-write array view with elements borrowing xs.

Create an iterable of the array shape shape.

Return an iterable of the indices of the passed-in array.

Create a one-dimensional array with elements from xs.

Create a two-dimensional array with elements from xs.

Create a three-dimensional array with elements from xs.

Stack arrays along the given axis.

Type Definitions

An array where the data has shared ownership and is copy on write.

An array that owns its data uniquely.

zero-dimensional array

one-dimensional array

two-dimensional array

three-dimensional array

four-dimensional array

five-dimensional array

six-dimensional array

dynamic-dimensional array

A read-only array view.

zero-dimensional array view

one-dimensional array view

two-dimensional array view

three-dimensional array view

four-dimensional array view

five-dimensional array view

six-dimensional array view

dynamic-dimensional array view

A read-write array view.

zero-dimensional read-write array view

one-dimensional read-write array view

two-dimensional read-write array view

three-dimensional read-write array view

four-dimensional read-write array view

five-dimensional read-write array view

six-dimensional read-write array view

dynamic-dimensional read-write array view

Array index type

zero-dimensionial

one-dimensional

two-dimensional

three-dimensional

four-dimensional

five-dimensional

six-dimensional

dynamic-dimensional

Array index type (signed)

An array where the data has shared ownership and is copy on write.

one-dimensional shared ownership array

two-dimensional shared ownership array