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.
MSRV: Requires Rust 1.64 or later

§Crate Feature Flags

The following crate feature flags are available. They are configured in your Cargo.toml. See doc::crate_feature_flags for more information.

std: Rust standard library-using functionality (enabled by default)
serde: serialization support for serde 1.x
rayon: Parallel iterators, parallelized methods, the parallel module and par_azip!.
approx Implementations of traits from the approx crate.
blas: transparent BLAS support for matrix multiplication, needs configuration.
matrixmultiply-threading: Use threading from matrixmultiply.

§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.

§The ndarray ecosystem

ndarray provides a lot of functionality, but it’s not a one-stop solution.

ndarray includes matrix multiplication and other binary/unary operations out of the box. More advanced linear algebra routines (e.g. SVD decomposition or eigenvalue computation) can be found in ndarray-linalg.

The same holds for statistics: ndarray provides some basic functionalities (e.g. mean) but more advanced routines can be found in ndarray-stats.

If you are looking to generate random arrays instead, check out ndarray-rand.

For conversion between ndarray, nalgebra and image check out nshare.

Modules§

doc: Standalone documentation pages.
iter: Producers, iterables and iterators.
linalg: Linear algebra.
parallel: Parallelization features for ndarray.
prelude: ndarray prelude.

Macros§

array: Create an Array with one, two, three, four, five, or six dimensions.
azip: Array zip macro: lock step function application across several arrays and producers.
concatenate: Concatenate arrays along the given axis.
par_azip: Parallelized array zip macro: lock step function application across several arrays and producers.
s: Slice argument constructor.
stack: Stack arrays along the new axis.

Structs§

ArrayBase: An n-dimensional array.
Axis: An axis index.
AxisDescription: Description of the axis, its length and its stride.
Dim: Dimension description.
IxDynImpl: Dynamic dimension or index type.
Linspace: An iterator of a sequence of evenly spaced floats.
Logspace: An iterator of a sequence of logarithmically spaced number.
MathCell: A transparent wrapper of Cell<T> which is identical in every way, except it will implement arithmetic operators as well.
NewAxis: Token to represent a new axis in a slice description.
OwnedArcRepr: ArcArray’s representation.
OwnedRepr: Array’s representation.
RawViewRepr: Array pointer’s representation.
Shape: A contiguous array shape of n dimensions.
ShapeError: An error related to array shape or layout.
Slice: A slice (range with step size).
SliceInfo: Represents all of the necessary information to perform a slice.
StrideShape: An array shape of n dimensions in c-order, f-order or custom strides.
ViewRepr: Array view’s representation.
Zip: Lock step function application across several arrays or other producers.

Enums§

CowRepr: CowArray’s representation.
ErrorKind: Error code for an error related to array shape or layout.
FoldWhile: Value controlling the execution of .fold_while on Zip.
Order: Array order
SliceInfoElem: A slice (range with step), an index, or a new axis token.

Traits§

AsArray: Argument conversion into an array view
AssignElem: A producer element that can be assigned to once
Data: Array representation trait.
DataMut: Array representation trait.
DataOwned: Array representation trait.
DataShared: Array representation trait.
DimAdd: Adds the two dimensions at compile time.
DimMax
Dimension: Array shape and index trait.
IndexLonger: Extra indexing methods for array views
IntoDimension: Argument conversion a dimension.
IntoNdProducer: Argument conversion into a producer.
LinalgScalar: Elements that support linear algebra operations.
MultiSliceArg: Slicing information describing multiple mutable, disjoint slices.
NdFloat: Floating-point element types f32 and f64.
NdIndex: Tuple or fixed size arrays that can be used to index an array.
NdProducer: A producer of an n-dimensional set of elements; for example an array view, mutable array view or an iterator that yields chunks.
RawData: Array representation trait.
RawDataClone: Array representation trait.
RawDataMut: Array representation trait.
RawDataSubst: Array representation trait.
RemoveAxis: Array shape with a next smaller dimension.
ScalarOperand: Elements that can be used as direct operands in arithmetic with arrays.
ShapeArg: Array shape argument with optional order parameter
ShapeBuilder: A trait for Shape and D where D: Dimension that allows customizing the memory layout (strides) of an array shape.
SliceArg: A type that can slice an array of dimension D.

Functions§

Dim: Create a new dimension value.
Ix0: Create a zero-dimensional index
Ix1: Create a one-dimensional index
Ix2: Create a two-dimensional index
Ix3: Create a three-dimensional index
Ix4: Create a four-dimensional index
Ix5: Create a five-dimensional index
Ix6: Create a six-dimensional index
IxDyn: Create a dynamic-dimensional index
arr0: Create a zero-dimensional array with the element x.
arr1: Create a one-dimensional array with elements from xs.
arr2: Create a two-dimensional array with elements from xs.
arr3: Create a three-dimensional array with elements from xs.
aview0: Create a zero-dimensional array view borrowing x.
aview1: Create a one-dimensional array view with elements borrowing xs.
aview2: Create a two-dimensional array view with elements borrowing xs.
aview_mut1: Create a one-dimensional read-write array view with elements borrowing xs.
aview_mut2: Create a two-dimensional read-write array view with elements borrowing xs.
concatenate: Concatenate arrays along the given axis.
indices: Create an iterable of the array shape shape.
indices_of: Return an iterable of the indices of the passed-in array.
linspace: Return an iterator of evenly spaced floats.
logspace: An iterator of a sequence of logarithmically spaced numbers.
range: Return an iterator of floats from a to b (exclusive), incrementing by step.
rcarr1: Create a one-dimensional array with elements from xs.
rcarr2: Create a two-dimensional array with elements from xs.
rcarr3: Create a three-dimensional array with elements from xs.
stack: Stack arrays along the new axis.

Type Aliases§

ArcArray: An array where the data has shared ownership and is copy on write.
ArcArray1: one-dimensional shared ownership array
ArcArray2: two-dimensional shared ownership array
Array: An array that owns its data uniquely.
Array0: zero-dimensional array
Array1: one-dimensional array
Array2: two-dimensional array
Array3: three-dimensional array
Array4: four-dimensional array
Array5: five-dimensional array
Array6: six-dimensional array
ArrayD: dynamic-dimensional array
ArrayView: A read-only array view.
ArrayView0: zero-dimensional array view
ArrayView1: one-dimensional array view
ArrayView2: two-dimensional array view
ArrayView3: three-dimensional array view
ArrayView4: four-dimensional array view
ArrayView5: five-dimensional array view
ArrayView6: six-dimensional array view
ArrayViewD: dynamic-dimensional array view
ArrayViewMut: A read-write array view.
ArrayViewMut0: zero-dimensional read-write array view
ArrayViewMut1: one-dimensional read-write array view
ArrayViewMut2: two-dimensional read-write array view
ArrayViewMut3: three-dimensional read-write array view
ArrayViewMut4: four-dimensional read-write array view
ArrayViewMut5: five-dimensional read-write array view
ArrayViewMut6: six-dimensional read-write array view
ArrayViewMutD: dynamic-dimensional read-write array view
CowArray: An array with copy-on-write behavior.
Ix: Array index type
Ix0: zero-dimensionial
Ix1: one-dimensional
Ix2: two-dimensional
Ix3: three-dimensional
Ix4: four-dimensional
Ix5: five-dimensional
Ix6: six-dimensional
IxDyn: dynamic-dimensional
Ixs: Array index type (signed)
RawArrayView: A read-only array view without a lifetime.
RawArrayViewMut: A mutable array view without a lifetime.

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