Crate numpy[−][src]

Expand description

rust-numpy provides Rust interfaces for NumPy C APIs, especially for ndarray class.

It uses pyo3 for rust bindings to cpython, and uses ndarray for rust side matrix library.

For numpy dependency, it calls import numpy.core internally. So you just need numpy installed by pip install numpy or other ways in your python environment. You can use both system environment and virtualenv.

This library loads numpy module automatically. So if numpy is not installed, it simply panics, instead of returing a result.

Example

#[macro_use]
extern crate ndarray;
use numpy::{ToPyArray, PyArray};
fn main() {
    pyo3::Python::with_gil(|py| {
        let py_array = array![[1i64, 2], [3, 4]].to_pyarray(py);
        assert_eq!(
            py_array.readonly().as_array(),
            array![[1i64, 2], [3, 4]]
        );
    })
}

Re-exports

pub use crate::array::get_array_module;

pub use crate::array::PyArray;

pub use crate::array::PyArray0;

pub use crate::array::PyArray1;

pub use crate::array::PyArray2;

pub use crate::array::PyArray3;

pub use crate::array::PyArray4;

pub use crate::array::PyArray5;

pub use crate::array::PyArray6;

pub use crate::array::PyArrayDyn;

pub use crate::convert::IntoPyArray;

pub use crate::convert::NpyIndex;

pub use crate::convert::ToNpyDims;

pub use crate::convert::ToPyArray;

pub use crate::npyffi::PY_ARRAY_API;

pub use crate::npyffi::PY_UFUNC_API;

pub use crate::npyiter::NpyIterFlag;

pub use crate::npyiter::NpyMultiIter;

pub use crate::npyiter::NpyMultiIterBuilder;

pub use crate::npyiter::NpySingleIter;

pub use crate::npyiter::NpySingleIterBuilder;

Modules

Safe interface for NumPy ndarray

Defines conversion traits between rust types and numpy data types.

Low-Level bindings for NumPy C API.

Wrapper of Array Iterator API.

Macros

Create an Array with one, two or three dimensions.

Return the Einstein summation convention of given tensors.

Create a PyArray with one, two or three dimensions. This macro is backed by ndarray::array.

Structs

Represents that given vec cannot be treated as array.

NotContiguousError

Represents that the array is not contiguous.

Binding of numpy.dtype.

PyReadonlyArray

Readonly reference of PyArray.

Represents that shapes of the given arrays don’t match.

Enums

Represents numpy data type.

Traits

Represents that a type can be an element of PyArray.

Iterator mode for single iterator

Functions

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

Return the dot product of two arrays.

Return the Einstein summation convention of given tensors.

Return the inner product of two arrays.

Type Definitions

one-dimensional

two-dimensional

three-dimensional

four-dimensional

five-dimensional

six-dimensional

dynamic-dimensional

PyReadonlyArray1

One-dimensional readonly array.

PyReadonlyArray2

Two-dimensional readonly array.

PyReadonlyArray3

Three-dimensional readonly array.

PyReadonlyArray4

Four-dimensional readonly array.

PyReadonlyArray5

Five-dimensional readonly array.

PyReadonlyArray6

Six-dimensional readonly array.

PyReadonlyArrayDyn

Dynamic-dimensional readonly array.