The ndarray
crate provides an n-dimensional container for general elements
and for numerics.
Please read the API documentation on docs.rs or take a look at the quickstart tutorial.
- Generic 1, 2, ..., n-dimensional arrays
- Owned arrays and array views
- 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.
- 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.
- Efficient floating point matrix multiplication even for very large matrices; can optionally use BLAS to improve it further.
The following crate feature flags are available. They are configured in your Cargo.toml.
std
Rust standard library (enabled by default)
This crate can be used without the standard library by disabling the default std feature. To do so, use this in your Cargo.toml:
[dependencies] ndarray = { version = "0.x.y", default-features = false }
The geomspace linspace logspace range std var var_axis and std_axis methods are only available when std is enabled.
serde
- Enables serialization support for serde 1.x
rayon
- Enables parallel iterators, parallelized methods and
par_azip!
. - Implies std
- Enables parallel iterators, parallelized methods and
approx
- Implementations of traits from version 0.4 of the [approx] crate.
approx-0_5
- Implementations of traits from version 0.5 of the [approx] crate.
blas
- Enable transparent BLAS support for matrix multiplication.
Uses
blas-src
for pluggable backend, which needs to be configured separately (see below).
- Enable transparent BLAS support for matrix multiplication.
Uses
matrixmultiply-threading
- Enable the
threading
feature in the matrixmultiply package
- Enable the
[dependencies] ndarray = "0.15.0"
Blas integration is an optional add-on. Without BLAS, ndarray uses the
matrixmultiply
crate for matrix multiplication for f64
and f32
arrays (and it's always enabled as a fallback since it supports matrices of
arbitrary strides in both dimensions).
Depend and link to blas-src
directly to pick a blas provider. Ndarray
presently requires a blas provider that provides the cblas-sys
interface. If
further feature selection is wanted or needed then you might need to depend directly on
the backend crate's source too. The backend version must be the one that
blas-src
also depends on.
An example configuration using system openblas is shown below. Note that only end-user projects (not libraries) should select provider:
[dependencies] ndarray = { version = "0.15.0", features = ["blas"] } blas-src = { version = "0.8", features = ["openblas"] } openblas-src = { version = "0.10", features = ["cblas", "system"] }
Using system-installed dependencies can save a long time building dependencies. An example configuration using (compiled) netlib is shown below anyway:
[dependencies] ndarray = { version = "0.15.0", features = ["blas"] } blas-src = { version = "0.8.0", default-features = false, features = ["netlib"] }
When this is done, your program must also link to blas_src
by using it or
explicitly including it in your code:
extern crate blas_src;
The following versions have been verified to work together. For ndarray 0.15 or later,
there is no tight coupling to the blas-src
version, so version selection is more flexible.
ndarray |
blas-src |
openblas-src |
netlib-src |
---|---|---|---|
0.15 | 0.8 | 0.10 | 0.8 |
0.15 | 0.7 | 0.9 | 0.8 |
0.14 | 0.6.1 | 0.9.0 | |
0.13 | 0.2.0 | 0.6.0 |
See RELEASES.md.
Dual-licensed to be compatible with the Rust project.
Licensed under the Apache License, Version 2.0 http://www.apache.org/licenses/LICENSE-2.0 or the MIT license http://opensource.org/licenses/MIT, at your option. This file may not be copied, modified, or distributed except according to those terms.