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//! Safe interface for NumPy ndarray use crate::npyffi::{self, npy_intp, NPY_ORDER, PY_ARRAY_API}; use ndarray::*; use num_traits::AsPrimitive; use pyo3::{ ffi, prelude::*, type_object, types::PyAny, AsPyPointer, PyDowncastError, PyNativeType, PyResult, }; use std::{cell::Cell, mem, os::raw::c_int, ptr, slice}; use std::{iter::ExactSizeIterator, marker::PhantomData}; use crate::convert::{IntoPyArray, NpyIndex, ToNpyDims, ToPyArray}; use crate::dtype::Element; use crate::error::{FromVecError, NotContiguousError, ShapeError}; use crate::slice_box::SliceBox; /// A safe, static-typed interface for /// [NumPy ndarray](https://numpy.org/doc/stable/reference/arrays.ndarray.html). /// /// # Memory location /// /// - Case1: Constructed via [`IntoPyArray`](../convert/trait.IntoPyArray.html) or /// [`from_vec`](#method.from_vec) or [`from_owned_array`](#method.from_owned_vec). /// /// These methods don't allocate memory and use `Box<[T]>` as a internal buffer. /// /// Please take care that **you cannot use some destructive methods like `resize`, /// for this kind of array**. /// /// - Case2: Constructed via other methods, like [`ToPyArray`](../convert/trait.ToPyArray.html) or /// [`from_slice`](#method.from_slice) or [`from_array`](#from_array). /// /// These methods allocate memory in Python's private heap. /// /// In both cases, **PyArray is managed by Python GC.** /// So you can neither retrieve it nor deallocate it manually. /// /// # Reference /// Like [`new`](#method.new), all constractor methods of `PyArray` returns `&PyArray`. /// /// This design follows /// [pyo3's ownership concept](https://pyo3.rs/master/doc/pyo3/index.html#ownership-and-lifetimes). /// /// /// # Data type and Dimension /// `PyArray` has 2 type parametes `T` and `D`. `T` represents its data type like /// [`f32`](https://doc.rust-lang.org/std/primitive.f32.html), and `D` represents its dimension. /// /// All data types you can use implements [Element](../types/trait.Element.html). /// /// Dimensions are represented by ndarray's /// [Dimension](https://docs.rs/ndarray/latest/ndarray/trait.Dimension.html) trait. /// /// Typically, you can use `Ix1, Ix2, ..` for fixed size arrays, and use `IxDyn` for dynamic /// dimensioned arrays. They're re-exported from `ndarray` crate. /// /// You can also use various type aliases we provide, like [`PyArray1`](./type.PyArray1.html) /// or [`PyArrayDyn`](./type.PyArrayDyn.html). /// /// To specify concrete dimension like `3×4×5`, you can use types which implements ndarray's /// [`IntoDimension`](https://docs.rs/ndarray/latest/ndarray/dimension/conversion/trait.IntoDimension.html) /// trait. Typically, you can use array(e.g. `[3, 4, 5]`) or tuple(e.g. `(3, 4, 5)`) as a dimension. /// /// # Example /// ``` /// # #[macro_use] extern crate ndarray; /// use pyo3::{GILGuard, Python}; /// use numpy::PyArray; /// use ndarray::Array; /// Python::with_gil(|py| { /// let pyarray = PyArray::arange(py, 0., 4., 1.).reshape([2, 2]).unwrap(); /// let array = array![[3., 4.], [5., 6.]]; /// assert_eq!( /// array.dot(&pyarray.readonly().as_array()), /// array![[8., 15.], [12., 23.]] /// ); /// }); /// ``` pub struct PyArray<T, D>(PyAny, PhantomData<T>, PhantomData<D>); /// One-dimensional array. pub type PyArray1<T> = PyArray<T, Ix1>; /// Two-dimensional array. pub type PyArray2<T> = PyArray<T, Ix2>; /// Three-dimensional array. pub type PyArray3<T> = PyArray<T, Ix3>; /// Four-dimensional array. pub type PyArray4<T> = PyArray<T, Ix4>; /// Five-dimensional array. pub type PyArray5<T> = PyArray<T, Ix5>; /// Six-dimensional array. pub type PyArray6<T> = PyArray<T, Ix6>; /// Dynamic-dimensional array. pub type PyArrayDyn<T> = PyArray<T, IxDyn>; /// Returns a array module. pub fn get_array_module(py: Python<'_>) -> PyResult<&PyModule> { PyModule::import(py, npyffi::array::MOD_NAME) } unsafe impl<T, D> type_object::PyLayout<PyArray<T, D>> for npyffi::PyArrayObject {} impl<T, D> type_object::PySizedLayout<PyArray<T, D>> for npyffi::PyArrayObject {} pyobject_native_type_convert!( PyArray<T, D>, npyffi::PyArrayObject, *npyffi::PY_ARRAY_API.get_type_object(npyffi::NpyTypes::PyArray_Type), Some("numpy"), npyffi::PyArray_Check, T, D ); pyobject_native_type_named!(PyArray<T, D>, T, D); pyobject_native_type_fmt!(PyArray<T, D>, T, D); impl<'a, T, D> std::convert::From<&'a PyArray<T, D>> for &'a PyAny { fn from(ob: &'a PyArray<T, D>) -> Self { unsafe { &*(ob as *const PyArray<T, D> as *const PyAny) } } } impl<T, D> IntoPy<PyObject> for PyArray<T, D> { fn into_py(self, py: Python<'_>) -> PyObject { unsafe { PyObject::from_borrowed_ptr(py, self.as_ptr()) } } } impl<'a, T: Element, D: Dimension> FromPyObject<'a> for &'a PyArray<T, D> { // here we do type-check three times // 1. Checks if the object is PyArray // 2. Checks if the data type of the array is T // 3. Checks if the dimension is same as D fn extract(ob: &'a PyAny) -> PyResult<Self> { let array = unsafe { if npyffi::PyArray_Check(ob.as_ptr()) == 0 { return Err(PyDowncastError::new(ob, "PyArray<T, D>").into()); } &*(ob as *const PyAny as *const PyArray<T, D>) }; let dtype = array.dtype(); let dim = array.shape().len(); if T::is_same_type(dtype) && D::NDIM.map(|n| n == dim).unwrap_or(true) { Ok(array) } else { Err(ShapeError::new(dtype, dim, T::DATA_TYPE, D::NDIM).into()) } } } impl<T, D> PyArray<T, D> { /// Gets a raw [`PyArrayObject`](../npyffi/objects/struct.PyArrayObject.html) pointer. pub fn as_array_ptr(&self) -> *mut npyffi::PyArrayObject { self.as_ptr() as _ } /// Returns `dtype` of the array. /// Counterpart of `array.dtype` in Python. /// /// # Example /// ``` /// pyo3::Python::with_gil(|py| { /// let array = numpy::PyArray::from_vec(py, vec![1, 2, 3i32]); /// let dtype = array.dtype(); /// assert_eq!(dtype.get_datatype().unwrap(), numpy::DataType::Int32); /// }); /// ``` pub fn dtype(&self) -> &crate::PyArrayDescr { let descr_ptr = unsafe { (*self.as_array_ptr()).descr }; unsafe { pyo3::FromPyPointer::from_borrowed_ptr(self.py(), descr_ptr as _) } } #[inline(always)] fn check_flag(&self, flag: c_int) -> bool { unsafe { *self.as_array_ptr() }.flags & flag == flag } #[inline(always)] pub(crate) fn get_flag(&self) -> c_int { unsafe { *self.as_array_ptr() }.flags } /// Returns a temporally unwriteable reference of the array. pub fn readonly(&self) -> crate::PyReadonlyArray<T, D> { self.into() } /// Returns `true` if the internal data of the array is C-style contiguous /// (default of numpy and ndarray) or Fortran-style contiguous. /// /// # Example /// ``` /// use pyo3::types::IntoPyDict; /// pyo3::Python::with_gil(|py| { /// let array = numpy::PyArray::arange(py, 0, 10, 1); /// assert!(array.is_contiguous()); /// let locals = [("np", numpy::get_array_module(py).unwrap())].into_py_dict(py); /// let not_contiguous: &numpy::PyArray1<f32> = py /// .eval("np.zeros((3, 5))[::2, 4]", Some(locals), None) /// .unwrap() /// .downcast() /// .unwrap(); /// assert!(!not_contiguous.is_contiguous()); /// }); /// ``` pub fn is_contiguous(&self) -> bool { self.check_flag(npyffi::NPY_ARRAY_C_CONTIGUOUS) | self.check_flag(npyffi::NPY_ARRAY_F_CONTIGUOUS) } /// Returns `true` if the internal data of the array is Fortran-style contiguous. pub fn is_fortran_contiguous(&self) -> bool { self.check_flag(npyffi::NPY_ARRAY_F_CONTIGUOUS) } /// Returns `true` if the internal data of the array is C-style contiguous. pub fn is_c_contiguous(&self) -> bool { self.check_flag(npyffi::NPY_ARRAY_C_CONTIGUOUS) } /// Get `Py<PyArray>` from `&PyArray`, which is the owned wrapper of PyObject. /// /// You can use this method when you have to avoid lifetime annotation to your function args /// or return types, like used with pyo3's `pymethod`. /// /// # Example /// ``` /// use pyo3::{GILGuard, Python, Py}; /// use numpy::PyArray1; /// fn return_py_array() -> Py<PyArray1<i32>> { /// Python::with_gil(|py| PyArray1::zeros(py, [5], false).to_owned()) /// } /// let array = return_py_array(); /// pyo3::Python::with_gil(|py| { /// assert_eq!(array.as_ref(py).readonly().as_slice().unwrap(), &[0, 0, 0, 0, 0]); /// }); /// ``` pub fn to_owned(&self) -> Py<Self> { unsafe { Py::from_borrowed_ptr(self.py(), self.as_ptr()) } } /// Constructs `PyArray` from raw python object without incrementing reference counts. pub unsafe fn from_owned_ptr(py: Python<'_>, ptr: *mut ffi::PyObject) -> &Self { py.from_owned_ptr(ptr) } /// Constructs PyArray from raw python object and increments reference counts. pub unsafe fn from_borrowed_ptr(py: Python<'_>, ptr: *mut ffi::PyObject) -> &Self { py.from_borrowed_ptr(ptr) } /// Returns the number of dimensions in the array. /// /// Same as [numpy.ndarray.ndim](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.ndim.html) /// /// # Example /// ``` /// use numpy::PyArray3; /// pyo3::Python::with_gil(|py| { /// let arr = PyArray3::<f64>::new(py, [4, 5, 6], false); /// assert_eq!(arr.ndim(), 3); /// }); /// ``` // C API: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_NDIM pub fn ndim(&self) -> usize { let ptr = self.as_array_ptr(); unsafe { (*ptr).nd as usize } } /// Returns a slice which contains how many bytes you need to jump to the next row. /// /// Same as [numpy.ndarray.strides](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.strides.html) /// # Example /// ``` /// use numpy::PyArray3; /// pyo3::Python::with_gil(|py| { /// let arr = PyArray3::<f64>::new(py, [4, 5, 6], false); /// assert_eq!(arr.strides(), &[240, 48, 8]); /// }); /// ``` // C API: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_STRIDES pub fn strides(&self) -> &[isize] { let n = self.ndim(); let ptr = self.as_array_ptr(); unsafe { let p = (*ptr).strides; slice::from_raw_parts(p, n) } } /// Returns a slice which contains dimmensions of the array. /// /// Same as [numpy.ndarray.shape](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.shape.html) /// # Example /// ``` /// use numpy::PyArray3; /// pyo3::Python::with_gil(|py| { /// let arr = PyArray3::<f64>::new(py, [4, 5, 6], false); /// assert_eq!(arr.shape(), &[4, 5, 6]); /// }); /// ``` // C API: https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_DIMS pub fn shape(&self) -> &[usize] { let n = self.ndim(); let ptr = self.as_array_ptr(); unsafe { let p = (*ptr).dimensions as *mut usize; slice::from_raw_parts(p, n) } } /// Calcurates the total number of elements in the array. pub fn len(&self) -> usize { self.shape().iter().product() } pub fn is_empty(&self) -> bool { self.len() == 0 } /// Returns the pointer to the first element of the inner array. pub(crate) unsafe fn data(&self) -> *mut T { let ptr = self.as_array_ptr(); (*ptr).data as *mut _ } pub(crate) unsafe fn copy_ptr(&self, other: *const T, len: usize) { ptr::copy_nonoverlapping(other, self.data(), len) } } struct InvertedAxises(Vec<Axis>); impl InvertedAxises { fn invert<S: RawData, D: Dimension>(self, array: &mut ArrayBase<S, D>) { for axis in self.0 { array.invert_axis(axis); } } } impl<T: Element, D: Dimension> PyArray<T, D> { /// Same as [shape](#method.shape), but returns `D` #[inline(always)] pub fn dims(&self) -> D { D::from_dimension(&Dim(self.shape())).expect("PyArray::dims different dimension") } fn ndarray_shape_ptr(&self) -> (StrideShape<D>, *mut T, InvertedAxises) { const ERR_MSG: &str = "PyArray::ndarray_shape: dimension mismatching"; let shape_slice = self.shape(); let shape: Shape<_> = Dim(self.dims()).into(); let sizeof_t = mem::size_of::<T>(); let strides = self.strides(); let mut new_strides = D::zeros(strides.len()); let mut data_ptr = unsafe { self.data() }; let mut inverted_axises = vec![]; for i in 0..strides.len() { // TODO(kngwyu): Replace this hacky negative strides support with // a proper constructor, when it's implemented. // See https://github.com/rust-ndarray/ndarray/issues/842 for more. if strides[i] < 0 { // Move the pointer to the start position let offset = strides[i] * (shape_slice[i] as isize - 1) / sizeof_t as isize; unsafe { data_ptr = data_ptr.offset(offset); } new_strides[i] = (-strides[i]) as usize / sizeof_t; inverted_axises.push(Axis(i)); } else { new_strides[i] = strides[i] as usize / sizeof_t; } } let st = D::from_dimension(&Dim(new_strides)).expect(ERR_MSG); (shape.strides(st), data_ptr, InvertedAxises(inverted_axises)) } /// Creates a new uninitialized PyArray in python heap. /// /// If `is_fortran == true`, returns Fortran-order array. Else, returns C-order array. /// /// # Example /// ``` /// use numpy::PyArray3; /// pyo3::Python::with_gil(|py| { /// let arr = PyArray3::<i32>::new(py, [4, 5, 6], false); /// assert_eq!(arr.shape(), &[4, 5, 6]); /// }); /// ``` pub fn new<ID>(py: Python, dims: ID, is_fortran: bool) -> &Self where ID: IntoDimension<Dim = D>, { let flags = if is_fortran { 1 } else { 0 }; unsafe { PyArray::new_(py, dims, ptr::null_mut(), flags) } } pub(crate) unsafe fn new_<ID>( py: Python, dims: ID, strides: *const npy_intp, flag: c_int, ) -> &Self where ID: IntoDimension<Dim = D>, { let dims = dims.into_dimension(); let ptr = PY_ARRAY_API.PyArray_New( PY_ARRAY_API.get_type_object(npyffi::NpyTypes::PyArray_Type), dims.ndim_cint(), dims.as_dims_ptr(), T::npy_type() as i32, strides as *mut _, // strides ptr::null_mut(), // data 0, // itemsize flag, // flag ptr::null_mut(), //obj ); Self::from_owned_ptr(py, ptr) } pub(crate) unsafe fn from_boxed_slice<'py, ID>( py: Python<'py>, dims: ID, strides: *const npy_intp, slice: Box<[T]>, ) -> &'py Self where ID: IntoDimension<Dim = D>, { let dims = dims.into_dimension(); let container = SliceBox::new(slice); let data_ptr = container.data; let cell = pyo3::PyClassInitializer::from(container) .create_cell(py) .expect("Object creation failed."); let ptr = PY_ARRAY_API.PyArray_New( PY_ARRAY_API.get_type_object(npyffi::NpyTypes::PyArray_Type), dims.ndim_cint(), dims.as_dims_ptr(), T::npy_type() as i32, strides as *mut _, // strides data_ptr as _, // data mem::size_of::<T>() as i32, // itemsize 0, // flag ptr::null_mut(), //obj ); PY_ARRAY_API.PyArray_SetBaseObject(ptr as *mut npyffi::PyArrayObject, cell as _); Self::from_owned_ptr(py, ptr) } /// Construct a new nd-dimensional array filled with 0. /// /// If `is_fortran` is true, then /// a fortran order array is created, otherwise a C-order array is created. /// /// See also [PyArray_Zeros](https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_Zeros) /// /// # Example /// ``` /// # #[macro_use] extern crate ndarray; /// use numpy::PyArray2; /// pyo3::Python::with_gil(|py| { /// let pyarray: &PyArray2<usize> = PyArray2::zeros(py, [2, 2], false); /// assert_eq!(pyarray.readonly().as_array(), array![[0, 0], [0, 0]]); /// }); /// ``` pub fn zeros<ID>(py: Python, dims: ID, is_fortran: bool) -> &Self where ID: IntoDimension<Dim = D>, { let dims = dims.into_dimension(); unsafe { let dtype = T::get_dtype(py); let ptr = PY_ARRAY_API.PyArray_Zeros( dims.ndim_cint(), dims.as_dims_ptr(), dtype.into_ptr() as _, if is_fortran { -1 } else { 0 }, ); Self::from_owned_ptr(py, ptr) } } /// Returns the immutable view of the internal data of `PyArray` as slice. /// /// Please consider the use of safe alternatives /// ([`PyReadonlyArray::as_slice`](../struct.PyReadonlyArray.html#method.as_slice) /// , [`as_cell_slice`](#method.as_cell_slice) or [`to_vec`](#method.to_vec)) instead of this. /// /// # Safety /// If the internal array is not readonly and can be mutated from Python code, /// holding the slice might cause undefined behavior. pub unsafe fn as_slice(&self) -> Result<&[T], NotContiguousError> { if !self.is_contiguous() { Err(NotContiguousError) } else { Ok(slice::from_raw_parts(self.data(), self.len())) } } /// Returns the view of the internal data of `PyArray` as `&[Cell<T>]`. pub fn as_cell_slice(&self) -> Result<&[Cell<T>], NotContiguousError> { if !self.is_contiguous() { Err(NotContiguousError) } else { Ok(unsafe { slice::from_raw_parts(self.data() as _, self.len()) }) } } /// Returns the view of the internal data of `PyArray` as mutable slice. /// /// # Safety /// If another reference to the internal data exists(e.g., `&[T]` or `ArrayView`), /// it might cause undefined behavior. /// /// In such case, please consider the use of [`as_cell_slice`](#method.as_cell_slice), pub unsafe fn as_slice_mut(&self) -> Result<&mut [T], NotContiguousError> { if !self.is_contiguous() { Err(NotContiguousError) } else { Ok(slice::from_raw_parts_mut(self.data(), self.len())) } } /// Construct PyArray from /// [`ndarray::Array`](https://docs.rs/ndarray/latest/ndarray/type.Array.html). /// /// This method uses internal [`Vec`](https://doc.rust-lang.org/std/vec/struct.Vec.html) /// of `ndarray::Array` as numpy array. /// /// # Example /// ``` /// # #[macro_use] extern crate ndarray; /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::from_owned_array(py, array![[1, 2], [3, 4]]); /// assert_eq!(pyarray.readonly().as_array(), array![[1, 2], [3, 4]]); /// }); /// ``` pub fn from_owned_array<'py>(py: Python<'py>, arr: Array<T, D>) -> &'py Self { IntoPyArray::into_pyarray(arr, py) } /// Get the immutable reference of the specified element, with checking the passed index is valid. /// /// Please consider the use of safe alternatives /// ([`PyReadonlyArray::get`](../struct.PyReadonlyArray.html#method.get) /// or [`get_owned`](#method.get_owned)) instead of this. /// # Example /// ``` /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let arr = PyArray::arange(py, 0, 16, 1).reshape([2, 2, 4]).unwrap(); /// assert_eq!(*unsafe { arr.get([1, 0, 3]) }.unwrap(), 11); /// }); /// ``` /// /// # Safety /// If the internal array is not readonly and can be mutated from Python code, /// holding the slice might cause undefined behavior. #[inline(always)] pub unsafe fn get(&self, index: impl NpyIndex<Dim = D>) -> Option<&T> { let offset = index.get_checked::<T>(self.shape(), self.strides())?; Some(&*self.data().offset(offset)) } /// Get the immutable reference of the specified element, without checking the /// passed index is valid. /// /// See [NpyIndex](../convert/trait.NpyIndex.html) for what types you can use as index. /// /// Passing an invalid index can cause undefined behavior(mostly SIGSEGV). /// /// # Example /// ``` /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let arr = PyArray::arange(py, 0, 16, 1).reshape([2, 2, 4]).unwrap(); /// assert_eq!(unsafe { *arr.uget([1, 0, 3]) }, 11); /// }); /// ``` #[inline(always)] pub unsafe fn uget<Idx>(&self, index: Idx) -> &T where Idx: NpyIndex<Dim = D>, { let offset = index.get_unchecked::<T>(self.strides()); &*self.data().offset(offset) } /// Same as [uget](#method.uget), but returns `&mut T`. #[inline(always)] #[allow(clippy::mut_from_ref)] pub unsafe fn uget_mut<Idx>(&self, index: Idx) -> &mut T where Idx: NpyIndex<Dim = D>, { let offset = index.get_unchecked::<T>(self.strides()); &mut *(self.data().offset(offset) as *mut _) } /// Get dynamic dimensioned array from fixed dimension array. /// /// See [get](#method.get) for usage. pub fn to_dyn(&self) -> &PyArray<T, IxDyn> { let python = self.py(); unsafe { PyArray::from_borrowed_ptr(python, self.as_ptr()) } } /// Get the copy of the specified element in the array. /// /// See [NpyIndex](../convert/trait.NpyIndex.html) for what types you can use as index. /// /// # Example /// ``` /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let arr = PyArray::arange(py, 0, 16, 1).reshape([2, 2, 4]).unwrap(); /// assert_eq!(arr.get_owned([1, 0, 3]), Some(11)); /// }); /// ``` pub fn get_owned(&self, index: impl NpyIndex<Dim = D>) -> Option<T> { unsafe { self.get(index) }.cloned() } /// Returns the copy of the internal data of `PyArray` to `Vec`. /// /// Returns `ErrorKind::NotContiguous` if the internal array is not contiguous. /// See also [`as_slice`](#method.as_slice) /// /// # Example /// ``` /// use numpy::PyArray2; /// use pyo3::types::IntoPyDict; /// pyo3::Python::with_gil(|py| { /// let locals = [("np", numpy::get_array_module(py).unwrap())].into_py_dict(py); /// let array: &PyArray2<i64> = py /// .eval("np.array([[0, 1], [2, 3]], dtype='int64')", Some(locals), None) /// .unwrap() /// .downcast() /// .unwrap(); /// assert_eq!(array.to_vec().unwrap(), vec![0, 1, 2, 3]); /// }); /// ``` pub fn to_vec(&self) -> Result<Vec<T>, NotContiguousError> { unsafe { self.as_slice() }.map(ToOwned::to_owned) } /// Construct PyArray from `ndarray::ArrayBase`. /// /// This method allocates memory in Python's heap via numpy api, and then copies all elements /// of the array there. /// /// # Example /// ``` /// # #[macro_use] extern crate ndarray; /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::from_array(py, &array![[1, 2], [3, 4]]); /// assert_eq!(pyarray.readonly().as_array(), array![[1, 2], [3, 4]]); /// }); /// ``` pub fn from_array<'py, S>(py: Python<'py>, arr: &ArrayBase<S, D>) -> &'py Self where S: Data<Elem = T>, { ToPyArray::to_pyarray(arr, py) } /// Get the immutable view of the internal data of `PyArray`, as /// [`ndarray::ArrayView`](https://docs.rs/ndarray/latest/ndarray/type.ArrayView.html). /// /// Please consider the use of safe alternatives /// ([`PyReadonlyArray::as_array`](../struct.PyReadonlyArray.html#method.as_array) /// or [`to_array`](#method.to_array)) instead of this. /// /// # Safety /// If the internal array is not readonly and can be mutated from Python code, /// holding the `ArrayView` might cause undefined behavior. pub unsafe fn as_array(&self) -> ArrayView<'_, T, D> { let (shape, ptr, inverted_axises) = self.ndarray_shape_ptr(); let mut res = ArrayView::from_shape_ptr(shape, ptr); inverted_axises.invert(&mut res); res } /// Returns the internal array as `ArrayViewMut`. See also [`as_array`](#method.as_array). /// /// # Safety /// If another reference to the internal data exists(e.g., `&[T]` or `ArrayView`), /// it might cause undefined behavior. pub unsafe fn as_array_mut(&self) -> ArrayViewMut<'_, T, D> { let (shape, ptr, inverted_axises) = self.ndarray_shape_ptr(); let mut res = ArrayViewMut::from_shape_ptr(shape, ptr); inverted_axises.invert(&mut res); res } /// Get a copy of `PyArray` as /// [`ndarray::Array`](https://docs.rs/ndarray/latest/ndarray/type.Array.html). /// /// # Example /// ``` /// # #[macro_use] extern crate ndarray; /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let py_array = PyArray::arange(py, 0, 4, 1).reshape([2, 2]).unwrap(); /// assert_eq!( /// py_array.to_owned_array(), /// array![[0, 1], [2, 3]] /// ) /// }); /// ``` pub fn to_owned_array(&self) -> Array<T, D> { unsafe { self.as_array() }.to_owned() } } impl<T: Element> PyArray<T, Ix1> { /// Construct one-dimension PyArray from slice. /// /// # Example /// ``` /// use numpy::PyArray; /// let array = [1, 2, 3, 4, 5]; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::from_slice(py, &array); /// assert_eq!(pyarray.readonly().as_slice().unwrap(), &[1, 2, 3, 4, 5]); /// }); /// ``` pub fn from_slice<'py>(py: Python<'py>, slice: &[T]) -> &'py Self { let array = PyArray::new(py, [slice.len()], false); unsafe { array.copy_ptr(slice.as_ptr(), slice.len()); } array } /// Construct one-dimension PyArray /// from [`Vec`](https://doc.rust-lang.org/std/vec/struct.Vec.html). /// /// # Example /// ``` /// use numpy::PyArray; /// let vec = vec![1, 2, 3, 4, 5]; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::from_vec(py, vec); /// assert_eq!(pyarray.readonly().as_slice().unwrap(), &[1, 2, 3, 4, 5]); /// }); /// ``` pub fn from_vec<'py>(py: Python<'py>, vec: Vec<T>) -> &'py Self { IntoPyArray::into_pyarray(vec, py) } /// Construct one-dimension PyArray from a type which implements /// [`ExactSizeIterator`](https://doc.rust-lang.org/std/iter/trait.ExactSizeIterator.html). /// /// # Example /// ``` /// use numpy::PyArray; /// use std::collections::BTreeSet; /// let vec = vec![1, 2, 3, 4, 5]; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::from_exact_iter(py, vec.iter().map(|&x| x)); /// assert_eq!(pyarray.readonly().as_slice().unwrap(), &[1, 2, 3, 4, 5]); /// }); /// ``` pub fn from_exact_iter(py: Python<'_>, iter: impl ExactSizeIterator<Item = T>) -> &Self { let array = Self::new(py, [iter.len()], false); unsafe { for (i, item) in iter.enumerate() { *array.uget_mut([i]) = item; } } array } /// Construct one-dimension PyArray from a type which implements /// [`IntoIterator`](https://doc.rust-lang.org/std/iter/trait.IntoIterator.html). /// /// If no reliable [`size_hint`](https://doc.rust-lang.org/std/iter/trait.Iterator.html#method.size_hint) is available, /// this method can allocate memory multiple time, which can hurt performance. /// /// # Example /// ``` /// use numpy::PyArray; /// let set: std::collections::BTreeSet<u32> = [4, 3, 2, 5, 1].into_iter().cloned().collect(); /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::from_iter(py, set); /// assert_eq!(pyarray.readonly().as_slice().unwrap(), &[1, 2, 3, 4, 5]); /// }); /// ``` pub fn from_iter(py: Python<'_>, iter: impl IntoIterator<Item = T>) -> &Self { let iter = iter.into_iter(); let (min_len, max_len) = iter.size_hint(); let mut capacity = max_len.unwrap_or_else(|| min_len.max(512 / mem::size_of::<T>())); let array = Self::new(py, [capacity], false); let mut length = 0; unsafe { for (i, item) in iter.enumerate() { length += 1; if length > capacity { capacity *= 2; array .resize(capacity) .expect("PyArray::from_iter: Failed to allocate memory"); } *array.uget_mut([i]) = item; } } if capacity > length { array.resize(length).unwrap() } array } /// Extends or trancates the length of 1 dimension PyArray. /// /// # Example /// ``` /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::arange(py, 0, 10, 1); /// assert_eq!(pyarray.len(), 10); /// pyarray.resize(100).unwrap(); /// assert_eq!(pyarray.len(), 100); /// }); /// ``` pub fn resize(&self, new_elems: usize) -> PyResult<()> { self.resize_([new_elems], 1, NPY_ORDER::NPY_ANYORDER) } /// Iterates all elements of this array. /// See [NpySingleIter](../npyiter/struct.NpySingleIter.html) for more. pub fn iter<'py>( &'py self, ) -> PyResult<crate::NpySingleIter<'py, T, crate::npyiter::ReadWrite>> { crate::NpySingleIterBuilder::readwrite(self).build() } fn resize_<D: IntoDimension>( &self, dims: D, check_ref: c_int, order: NPY_ORDER, ) -> PyResult<()> { let dims = dims.into_dimension(); let mut np_dims = dims.to_npy_dims(); let res = unsafe { PY_ARRAY_API.PyArray_Resize( self.as_array_ptr(), &mut np_dims as *mut npyffi::PyArray_Dims, check_ref, order, ) }; if res.is_null() { Err(PyErr::fetch(self.py())) } else { Ok(()) } } } impl<T: Element> PyArray<T, Ix2> { /// Construct a two-dimension PyArray from `Vec<Vec<T>>`. /// /// This function checks all dimension of inner vec, and if there's any vec /// where its dimension differs from others, it returns `ArrayCastError`. /// /// # Example /// ``` /// # #[macro_use] extern crate ndarray; /// use numpy::PyArray; /// let vec2 = vec![vec![1, 2, 3]; 2]; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::from_vec2(py, &vec2).unwrap(); /// assert_eq!(pyarray.readonly().as_array(), array![[1, 2, 3], [1, 2, 3]]); /// assert!(PyArray::from_vec2(py, &[vec![1], vec![2, 3]]).is_err()); /// }); /// ``` pub fn from_vec2<'py>(py: Python<'py>, v: &[Vec<T>]) -> Result<&'py Self, FromVecError> { let last_len = v.last().map_or(0, |v| v.len()); if v.iter().any(|v| v.len() != last_len) { return Err(FromVecError::new(v.len(), last_len)); } let dims = [v.len(), last_len]; let array = Self::new(py, dims, false); unsafe { for (y, vy) in v.iter().enumerate() { for (x, vyx) in vy.iter().enumerate() { *array.uget_mut([y, x]) = vyx.clone(); } } } Ok(array) } } impl<T: Element> PyArray<T, Ix3> { /// Construct a three-dimension PyArray from `Vec<Vec<Vec<T>>>`. /// /// This function checks all dimension of inner vec, and if there's any vec /// where its dimension differs from others, it returns error. /// /// # Example /// ``` /// # #[macro_use] extern crate ndarray; /// use numpy::PyArray; /// let vec3 = vec![vec![vec![1, 2]; 2]; 2]; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::from_vec3(py, &vec3).unwrap(); /// assert_eq!( /// pyarray.readonly().as_array(), /// array![[[1, 2], [1, 2]], [[1, 2], [1, 2]]] /// ); /// assert!(PyArray::from_vec3(py, &[vec![vec![1], vec![]]]).is_err()); /// }); /// ``` pub fn from_vec3<'py>(py: Python<'py>, v: &[Vec<Vec<T>>]) -> Result<&'py Self, FromVecError> { let len2 = v.last().map_or(0, |v| v.len()); if v.iter().any(|v| v.len() != len2) { return Err(FromVecError::new(v.len(), len2)); } let len3 = v.last().map_or(0, |v| v.last().map_or(0, |v| v.len())); if v.iter().any(|v| v.iter().any(|v| v.len() != len3)) { return Err(FromVecError::new(v.len(), len3)); } let dims = [v.len(), len2, len3]; let array = Self::new(py, dims, false); unsafe { for (z, vz) in v.iter().enumerate() { for (y, vzy) in vz.iter().enumerate() { for (x, vzyx) in vzy.iter().enumerate() { *array.uget_mut([z, y, x]) = vzyx.clone(); } } } } Ok(array) } } impl<T: Element, D> PyArray<T, D> { /// Copies self into `other`, performing a data-type conversion if necessary. /// # Example /// ``` /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let pyarray_f = PyArray::arange(py, 2.0, 5.0, 1.0); /// let pyarray_i = PyArray::<i64, _>::new(py, [3], false); /// assert!(pyarray_f.copy_to(pyarray_i).is_ok()); /// assert_eq!(pyarray_i.readonly().as_slice().unwrap(), &[2, 3, 4]); /// }); /// ``` pub fn copy_to<U: Element>(&self, other: &PyArray<U, D>) -> PyResult<()> { let self_ptr = self.as_array_ptr(); let other_ptr = other.as_array_ptr(); let result = unsafe { PY_ARRAY_API.PyArray_CopyInto(other_ptr, self_ptr) }; if result == -1 { Err(PyErr::fetch(self.py())) } else { Ok(()) } } /// Cast the `PyArray<T>` to `PyArray<U>`, by allocating a new array. /// # Example /// ``` /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let pyarray_f = PyArray::arange(py, 2.0, 5.0, 1.0); /// let pyarray_i = pyarray_f.cast::<i32>(false).unwrap(); /// assert!(pyarray_f.copy_to(pyarray_i).is_ok()); /// assert_eq!(pyarray_i.readonly().as_slice().unwrap(), &[2, 3, 4]); /// }); /// ``` pub fn cast<'py, U: Element>(&'py self, is_fortran: bool) -> PyResult<&'py PyArray<U, D>> { let ptr = unsafe { let dtype = U::get_dtype(self.py()); PY_ARRAY_API.PyArray_CastToType( self.as_array_ptr(), dtype.into_ptr() as _, if is_fortran { -1 } else { 0 }, ) }; if ptr.is_null() { Err(PyErr::fetch(self.py())) } else { Ok(unsafe { PyArray::<U, D>::from_owned_ptr(self.py(), ptr) }) } } /// Construct a new array which has same values as self, same matrix order, but has different /// dimensions specified by `dims`. /// /// Since a returned array can contain a same pointer as self, we highly recommend to drop an /// old array, if this method returns `Ok`. /// /// # Example /// /// ``` /// # #[macro_use] extern crate ndarray; /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let array = PyArray::from_exact_iter(py, 0..9); /// let array = array.reshape([3, 3]).unwrap(); /// assert_eq!(array.readonly().as_array(), array![[0, 1, 2], [3, 4, 5], [6, 7, 8]]); /// assert!(array.reshape([5]).is_err()); /// }); /// ``` #[inline(always)] pub fn reshape<'py, ID, D2>(&'py self, dims: ID) -> PyResult<&'py PyArray<T, D2>> where ID: IntoDimension<Dim = D2>, D2: Dimension, { self.reshape_with_order(dims, NPY_ORDER::NPY_ANYORDER) } /// Same as [reshape](method.reshape.html), but you can change the order of returned matrix. pub fn reshape_with_order<'py, ID, D2>( &'py self, dims: ID, order: NPY_ORDER, ) -> PyResult<&'py PyArray<T, D2>> where ID: IntoDimension<Dim = D2>, D2: Dimension, { let dims = dims.into_dimension(); let mut np_dims = dims.to_npy_dims(); let ptr = unsafe { PY_ARRAY_API.PyArray_Newshape( self.as_array_ptr(), &mut np_dims as *mut npyffi::PyArray_Dims, order, ) }; if ptr.is_null() { Err(PyErr::fetch(self.py())) } else { Ok(unsafe { PyArray::<T, D2>::from_owned_ptr(self.py(), ptr) }) } } } impl<T: Element + AsPrimitive<f64>> PyArray<T, Ix1> { /// Return evenly spaced values within a given interval. /// Same as [numpy.arange](https://numpy.org/doc/stable/reference/generated/numpy.arange.html). /// /// See also [PyArray_Arange](https://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_Arange). /// /// # Example /// ``` /// use numpy::PyArray; /// pyo3::Python::with_gil(|py| { /// let pyarray = PyArray::arange(py, 2.0, 4.0, 0.5); /// assert_eq!(pyarray.readonly().as_slice().unwrap(), &[2.0, 2.5, 3.0, 3.5]); /// let pyarray = PyArray::arange(py, -2, 4, 3); /// assert_eq!(pyarray.readonly().as_slice().unwrap(), &[-2, 1]); /// }); pub fn arange(py: Python, start: T, stop: T, step: T) -> &Self { unsafe { let ptr = PY_ARRAY_API.PyArray_Arange( start.as_(), stop.as_(), step.as_(), T::npy_type() as i32, ); Self::from_owned_ptr(py, ptr) } } } #[test] fn test_get_unchecked() { pyo3::Python::with_gil(|py| { let array = PyArray::from_slice(py, &[1i32, 2, 3]); unsafe { assert_eq!(*array.uget([1]), 2); } }) } #[test] fn test_dyn_to_owned_array() { pyo3::Python::with_gil(|py| { let array = PyArray::from_vec2(py, &[vec![1, 2], vec![3, 4]]).unwrap(); array.to_dyn().to_owned_array(); }) }