Crate numpy

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 pyo3::prelude::Python;
use numpy::{ToPyArray, PyArray};
fn main() {
    let gil = Python::acquire_gil();
    let py = gil.python();
    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::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;

Modules

array	Safe interface for NumPy ndarray
convert	Defines conversion traits between rust types and numpy data types.
npyffi	Low-Level bindings for NumPy C API.

Structs

FromVecError	Represents that given vec cannot be treated as array.
NotContiguousError	Represents that the array is not contiguous.
PyReadonlyArray	Readonly reference of PyArray.
ShapeError	Represents that shapes of the given arrays don't match.

Enums

DataType

An enum type represents numpy data type.

Traits

Element

Represents that a type can be an element of PyArray.

Functions

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

Type Definitions

Ix1	one-dimensional
Ix2	two-dimensional
Ix3	three-dimensional
Ix4	four-dimensional
Ix5	five-dimensional
Ix6	six-dimensional
IxDyn	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
c32
c64