Crate ndarray

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.
• 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 1.22

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

doc	Standalone documentation pages.
iter	Producers, iterables and iterators.
linalg	Linear algebra.
prelude	ndarray prelude.

Macros

array	Create an Array with one, two or three dimensions.
azip	Array zip macro: lock step function application across several arrays and producers.
s	Slice argument constructor.
stack	Stack arrays along the given 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.
OwnedArcRepr	ArcArray's representation.
OwnedRepr	Array'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

ErrorKind	Error code for an error related to array shape or layout.
FoldWhile	Value controlling the execution of .fold_while on Zip.
SliceOrIndex	A slice (range with step) or an index.

Traits

AsArray	Argument conversion into an array view
Data	Array representation trait.
DataClone	Array representation trait.
DataMut	Array representation trait.
DataOwned	Array representation trait.
DataShared	Array representation trait.
Dimension	Array shape and index trait.
FixedInitializer	Fixed-size array used for array initialization
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.
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.
RemoveAxis	Array shape with a next smaller dimension.
ScalarOperand	Elements that can be used as direct operands in arithmetic with arrays.
ShapeBuilder	A trait for Shape and D where D: Dimension that allows customizing the memory layout (strides) of an array shape.

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.
indices	Create an iterable of the array shape shape.
indices_of	Return an iterable of the indices of the passed-in array.
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 given axis.

Type Definitions

ArcArray	An array where the data has shared ownership and is copy on write.
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
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)
RcArray	An array where the data has shared ownership and is copy on write.
RcArray1	one-dimensional shared ownership array
RcArray2	two-dimensional shared ownership array