C++ implementation of the Python Numpy library.zip

/// @file /// @author David Pilger <dpilger26@gmail.com> /// [GitHub Repository](https://github.com/dpilger26/NumCpp) /// /// License /// Copyright 2018-2023 David Pilger /// /// Permission is hereby granted, free of charge, to any person obtaining a copy of this /// software and associated documentation files(the "Software"), to deal in the Software /// without restriction, including without limitation the rights to use, copy, modify, /// merge, publish, distribute, sublicense, and/or sell copies of the Software, and to /// permit persons to whom the Software is furnished to do so, subject to the following /// conditions : /// /// The above copyright notice and this permission notice shall be included in all copies /// or substantial portions of the Software. /// /// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, /// INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR /// PURPOSE AND NONINFRINGEMENT.IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE /// FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR /// OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER /// DEALINGS IN THE SOFTWARE. /// /// Description /// Holds 1D and 2D arrays, the main work horse of the NumCpp library /// #pragma once #include <array> #include <cmath> #include <deque> #include <filesystem> #include <forward_list> #include <fstream> #include <initializer_list> #include <iostream> #include <iterator> #include <list> #include <memory> #include <numeric> #include <set> #include <string> #include <type_traits> #include <utility> #include <vector> #include "NumCpp/Core/Constants.hpp" #include "NumCpp/Core/DtypeInfo.hpp" #include "NumCpp/Core/Enums.hpp" #include "NumCpp/Core/Internal/Endian.hpp" #include "NumCpp/Core/Internal/Error.hpp" #include "NumCpp/Core/Internal/StaticAsserts.hpp" #include "NumCpp/Core/Internal/StdComplexOperators.hpp" #include "NumCpp/Core/Internal/StlAlgorithms.hpp" #include "NumCpp/Core/Internal/TypeTraits.hpp" #include "NumCpp/Core/Shape.hpp" #include "NumCpp/Core/Slice.hpp" #include "NumCpp/Core/Types.hpp" #include "NumCpp/NdArray/NdArrayIterators.hpp" #include "NumCpp/Utils/essentiallyEqual.hpp" #include "NumCpp/Utils/essentiallyEqualComplex.hpp" #include "NumCpp/Utils/num2str.hpp" #include "NumCpp/Utils/power.hpp" #include "NumCpp/Utils/sqr.hpp" #include "NumCpp/Utils/value2str.hpp" namespace nc { namespace type_traits { //============================================================================ // Class Description: /// Template class for determining if dtype is a valid index type for NdArray /// template<typename> struct is_ndarray_int : std::false_type { }; //============================================================================ // Class Description: /// Template class for determining if dtype is a valid index typefor NdArray /// template<typename dtype, typename Allocator> struct is_ndarray_int<NdArray<dtype, Allocator>> { static constexpr bool value = std::is_integral_v<dtype>; }; //============================================================================ // Class Description: /// is_ndarray_int helper /// template<typename T> constexpr bool is_ndarray_int_v = is_ndarray_int<T>::value; //============================================================================ // Class Description: /// Template class for determining if dtype is an unsigned integer type /// template<typename> struct is_ndarray_signed_int : std::false_type { }; //============================================================================ // Class Description: /// Template class for determining if dtype is an unsigned integer type /// template<typename dtype, typename Allocator> struct is_ndarray_signed_int<NdArray<dtype, Allocator>> { static constexpr bool value = std::is_signed_v<dtype>; }; //============================================================================ // Class Description: /// is_ndarray_int helper /// template<typename T> constexpr bool is_ndarray_signed_int_v = is_ndarray_signed_int<T>::value; //============================================================================ // Class Description: /// is_ndarray_int /// template<typename T> using ndarray_int_concept = std::enable_if_t<is_ndarray_int_v<T>, int>; } // namespace type_traits //================================================================================ // Class Description: /// Holds 1D and 2D arrays, the main work horse of the NumCpp library template<typename dtype, class Allocator = std::allocator<dtype>> class NdArray { private: STATIC_ASSERT_VALID_DTYPE(dtype); static_assert(std::is_same_v<dtype, typename Allocator::value_type>, "value_type and Allocator::value_type must match"); using AllocType = typename std::allocator_traits<Allocator>::template rebind_alloc<dtype>; using AllocTraits = std::allocator_traits<AllocType>; public: using self_type = NdArray<dtype, Allocator>; using value_type = dtype; using allocator_type = Allocator; using pointer = typename AllocTraits::pointer; using const_pointer = typename AllocTraits::const_pointer; using reference = dtype&; using const_reference = const dtype&; using size_type = uint32; using index_type = int32; using difference_type = typename AllocTraits::difference_type; using iterator = NdArrayIterator<dtype, pointer, difference_type>; using const_iterator = NdArrayConstIterator<dtype, const_pointer, difference_type>; using reverse_iterator = std::reverse_iterator<iterator>; using const_reverse_iterator = std::reverse_iterator<const_iterator>; using column_iterator = NdArrayColumnIterator<dtype, size_type, pointer, difference_type>; using const_column_iterator = NdArrayConstColumnIterator<dtype, size_type, const_pointer, difference_type>; using reverse_column_iterator = std::reverse_iterator<column_iterator>; using const_reverse_column_iterator = std::reverse_iterator<const_column_iterator>; //============================================================================ // Method Description: /// Defualt Constructor, not very usefull... /// NdArray() = default; //============================================================================ // Method Description: /// Constructor /// /// @param inSquareSize: square number of rows and columns /// explicit NdArray(size_type inSquareSize) : shape_{ inSquareSize, inSquareSize }, size_{ inSquareSize * inSquareSize } { newArray(); } //============================================================================ // Method Description: /// Constructor /// /// @param inNumRows /// @param inNumCols /// NdArray(size_type inNumRows, size_type inNumCols) : shape_{ inNumRows, inNumCols }, size_{ inNumRows * inNumCols } { newArray(); } //======