C++ implementation of the Python Numpy library

David Pilger

Last update: Jan 3, 2023

Overview

NumCpp: A Templatized Header Only C++ Implementation of the Python NumPy Library

Author: David Pilger [email protected]

Version:

License

Testing

C++ Standards:

Compilers:
Visual Studio: 2017, 2019
GNU: 6.5, 7.5, 8.4, 9.3, 10.1
Clang: 6, 7, 8, 9, 10

Boost Versions:
1.68+

From NumPy To NumCpp – A Quick Start Guide

This quick start guide is meant as a very brief overview of some of the things that can be done with NumCpp. For a full breakdown of everything available in the NumCpp library please visit the Full Documentation.

CONTAINERS

The main data structure in NumCpp is the NdArray. It is inherently a 2D array class, with 1D arrays being implemented as 1xN arrays. There is also a DataCube class that is provided as a convenience container for storing an array of 2D NdArrays, but it has limited usefulness past a simple container.

NumPy	NumCpp
`a = np.array([[1, 2], [3, 4], [5, 6]])`	`nc::NdArray a = { {1, 2}, {3, 4}, {5, 6} }`
`a.reshape([2, 3])`	`a.reshape(2, 3)`
`a.astype(np.double)`	`a.astype()`

INITIALIZERS

Many initializer functions are provided that return NdArrays for common needs.

NumPy	NumCpp
`np.linspace(1, 10, 5)`	`nc::linspace(1, 10, 5)`
`np.arange(3, 7)`	`nc::arange(3, 7)`
`np.eye(4)`	`nc::eye(4)`
`np.zeros([3, 4])`	`nc::zeros(3, 4)`
	`nc::NdArray(3, 4) a = 0`
`np.ones([3, 4])`	`nc::ones(3, 4)`
	`nc::NdArray(3, 4) a = 1`
`np.nans([3, 4])`	`nc::nans(3, 4)`
	`nc::NdArray(3, 4) a = nc::constants::nan`
`np.empty([3, 4])`	`nc::empty(3, 4)`
	`nc::NdArray(3, 4) a`

SLICING/BROADCASTING

NumCpp offers NumPy style slicing and broadcasting.

NumPy	NumCpp
`a[2, 3]`	`a(2, 3)`
`a[2:5, 5:8]`	`a(nc::Slice(2, 5), nc::Slice(5, 8))`
	`a({2, 5}, {5, 8})`
`a[:, 7]`	`a(a.rSlice(), 7)`
`a[a > 5]`	`a[a > 50]`
`a[a > 5] = 0`	`a.putMask(a > 50, 666)`

RANDOM

The random module provides simple ways to create random arrays.

NumPy	NumCpp
`np.random.seed(666)`	`nc::random::seed(666)`
`np.random.randn(3, 4)`	`nc::random::randN(nc::Shape(3,4))`
	`nc::random::randN({3, 4})`
`np.random.randint(0, 10, [3, 4])`	`nc::random::randInt(nc::Shape(3,4),0,10)`
	`nc::random::randInt({3, 4},0,10)`
`np.random.rand(3, 4)`	`nc::random::rand(nc::Shape(3,4))`
	`nc::random::rand({3, 4})`
`np.random.choice(a, 3)`	`nc::random::choice(a, 3)`

CONCATENATION

Many ways to concatenate NdArray are available.

NumPy	NumCpp
`np.stack([a, b, c], axis=0)`	`nc::stack({a, b, c}, nc::Axis::ROW)`
`np.vstack([a, b, c])`	`nc::vstack({a, b, c})`
`np.hstack([a, b, c])`	`nc::hstack({a, b, c})`
`np.append(a, b, axis=1)`	`nc::append(a, b, nc::Axis::COL)`

DIAGONAL, TRIANGULAR, AND FLIP

The following return new NdArrays.

NumPy	NumCpp
`np.diagonal(a)`	`nc::diagonal(a)`
`np.triu(a)`	`nc::triu(a)`
`np.tril(a)`	`nc::tril(a)`
`np.flip(a, axis=0)`	`nc::flip(a, nc::Axis::ROW)`
`np.flipud(a)`	`nc::flipud(a)`
`np.fliplr(a)`	`nc::fliplr(a)`

ITERATION

NumCpp follows the idioms of the C++ STL providing iterator pairs to iterate on arrays in different fashions.

NumPy	NumCpp
`for value in a`	`for(auto it = a.begin(); it < a.end(); ++it)`
	`for(auto& value : a)`

LOGICAL

Logical FUNCTIONS in NumCpp behave the same as NumPy.

NumPy	NumCpp
`np.where(a > 5, a, b)`	`nc::where(a > 5, a, b)`
`np.any(a)`	`nc::any(a)`
`np.all(a)`	`nc::all(a)`
`np.logical_and(a, b)`	`nc::logical_and(a, b)`
`np.logical_or(a, b)`	`nc::logical_or(a, b)`
`np.isclose(a, b)`	`nc::isclose(a, b)`
`np.allclose(a, b)`	`nc::allclose(a, b)`

COMPARISONS

NumPy	NumCpp
`np.equal(a, b)`	`nc::equal(a, b)`
	`a == b`
`np.not_equal(a, b)`	`nc::not_equal(a, b)`
	`a != b`
`rows, cols = np.nonzero(a)`	`auto [rows, cols] = nc::nonzero(a)`

MINIMUM, MAXIMUM, SORTING

NumPy	NumCpp
`np.min(a)`	`nc::min(a)`
`np.max(a)`	`nc::max(a)`
`np.argmin(a)`	`nc::argmin(a)`
`np.argmax(a)`	`nc::argmax(a)`
`np.sort(a, axis=0)`	`nc::sort(a, nc::Axis::ROW)`
`np.argsort(a, axis=1)`	`nc::argsort(a, nc::Axis::COL)`
`np.unique(a)`	`nc::unique(a)`
`np.setdiff1d(a, b)`	`nc::setdiff1d(a, b)`
`np.diff(a)`	`nc::diff(a)`

REDUCERS

Reducers accumulate values of NdArrays along specified axes. When no axis is specified, values are accumulated along all axes.

NumPy	NumCpp
`np.sum(a)`	`nc::sum(a)`
`np.sum(a, axis=0)`	`nc::sum(a, nc::Axis::ROW)`
`np.prod(a)`	`nc::prod(a)`
`np.prod(a, axis=0)`	`nc::prod(a, nc::Axis::ROW)`
`np.mean(a)`	`nc::mean(a)`
`np.mean(a, axis=0)`	`nc::mean(a, nc::Axis::ROW)`
`np.count_nonzero(a)`	`nc::count_nonzero(a)`
`np.count_nonzero(a, axis=0)`	`nc::count_nonzero(a, nc::Axis::ROW)`

I/O

Print and file output methods. All NumCpp classes support a print() method and << stream operators.

NumPy	NumCpp
`print(a)`	`a.print()`
	`std::cout << a`
`a.tofile(filename, sep=’\n’)`	`a.tofile(filename, "\n")`
`np.fromfile(filename, sep=’\n’)`	`nc::fromfile(filename, "\n")`
`np.dump(a, filename)`	`nc::dump(a, filename)`
`np.load(filename)`	`nc::load(filename)`

MATHEMATICAL FUNCTIONS

NumCpp universal functions are provided for a large set number of mathematical functions.

BASIC FUNCTIONS

NumPy	NumCpp
`np.abs(a)`	`nc::abs(a)`
`np.sign(a)`	`nc::sign(a)`
`np.remainder(a, b)`	`nc::remainder(a, b)`
`np.clip(a, 3, 8)`	`nc::clip(a, 3, 8)`
`np.interp(x, xp, fp)`	`nc::interp(x, xp, fp)`

EXPONENTIAL FUNCTIONS

NumPy	NumCpp
`np.exp(a)`	`nc::exp(a)`
`np.expm1(a)`	`nc::expm1(a)`
`np.log(a)`	`nc::log(a)`
`np.log1p(a)`	`nc::log1p(a)`

POWER FUNCTIONS

NumPy	NumCpp
`np.power(a, 4)`	`nc::power(a, 4)`
`np.sqrt(a)`	`nc::sqrt(a)`
`np.square(a)`	`nc::square(a)`
`np.cbrt(a)`	`nc::cbrt(a)`

TRIGONOMETRIC FUNCTIONS

NumPy	NumCpp
`np.sin(a)`	`nc::sin(a)`
`np.cos(a)`	`nc::cos(a)`
`np.tan(a)`	`nc::tan(a)`

HYPERBOLIC FUNCTIONS

NumPy	NumCpp
`np.sinh(a)`	`nc::sinh(a)`
`np.cosh(a)`	`nc::cosh(a)`
`np.tanh(a)`	`nc::tanh(a)`

CLASSIFICATION FUNCTIONS

NumPy	NumCpp
`np.isnan(a)`	`nc::isnan(a)`
`np.isinf(a)`	`nc::isinf(a)`

LINEAR ALGEBRA

NumPy	NumCpp
`np.linalg.norm(a)`	`nc::norm(a)`
`np.dot(a, b)`	`nc::dot(a, b)`
`np.linalg.det(a)`	`nc::linalg::det(a)`
`np.linalg.inv(a)`	`nc::linalg::inv(a)`
`np.linalg.lstsq(a, b)`	`nc::linalg::lstsq(a, b)`
`np.linalg.matrix_power(a, 3)`	`nc::linalg::matrix_power(a, 3)`
`Np.linalg.multi_dot(a, b, c)`	`nc::linalg::multi_dot({a, b, c})`
`np.linalg.svd(a)`	`nc::linalg::svd(a)`

Comments

NdArrayCore.hpp Visual Studio error

In https://github.com/dpilger26/NumCpp/blob/master/include/NumCpp/NdArray/NdArrayCore.hpp Line 4690, You've commented: // NOTE: this needs to be defined outside of the class to get rid of a compiler // error in Visual Studio

But I see it's already outside of the class, yet I get a Visual Studio compilation error:

Severity Code Description Project File Line Suppression State Error(active) E0135 class template "nc::NdArray<dtype, Allocator>" has no member "nonzero" my_lib C : \NumCpp - master\include\NumCpp\NdArray\NdArrayCore.hpp 4693

What is needed to be done in order to fix this error ?

opened by TomAvrech 8

Problem for random seed

nc::random::seed(unsigned int(time(NULL)));
cout << nc::random::randFloat<float>(0, 1) << endl;

Here is my code, but the final executable program products the same number every time it starts. However, the following code can generate different numbers each time.

mt19937_64 generator;
generator.seed(unsigned int(time(NULL)));
boost::random::uniform_real_distribution<float> rand(0, 1);
cout << rand(generator) << endl;

question

opened by linlll 8

How to realize element-wise slice in Numcpp?
In Numpy, I can slice the array like this:

test_np = np.array([1, 2, 3, 4, 5]) indice = [2, 4] slice_np = test_np[indice]#[3, 5]

However, I have not found any API that can slice the array in Numcpp like this. It seems either Slice() or at() can not slice the array like this. Does it exist any API in Numcpp that can slice like this? Thanks!
enhancement
opened by TangToy 7
Compilation error: ambiguous overload for operator

I just installed Numcpp on a new machine and tried to compile a piece of code which was working on another machine. However, on the new machine, I get compilation error: ambiguous overload for ‘operator+’ (operand types are ‘nc::NdArray<double>’ and ‘int’). There are errors related to the ambiguity for nearly all the operators. I was wondering if you could help me fix this issue. I am using Boost 1.7, Clang 6.0, and tried different versions of gcc, including 7 , 8.3.0, 9.2. Thanks in advance.

opened by Houman-HM 7
Numpy diag in Numcpp

Hey, I was wondering if you could let me know how I can get numpy.diag in Numcpp. I could not find anything regarding that method in the documentation. There is nc:diagonal, which is different with numpy.diag. Wondering if you have already implemented numpy.diag .

Thanks in advance.
enhancement

opened by Houman-HM 7
there are some bugs when i try to build Readme

hi

i try to build Numcpp on ubuntu1604. there are some bugs . cake is 3.15.2 and boost is 1.68. ***there is the log Scanning dependencies of target Example [ 50%] Building CXX object CMakeFiles/Example.dir/ReadMe.cpp.o In file included from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions.hpp:57:0, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp.hpp:37, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/ReadMe.cpp:1: /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp: In function 'nc::NdArray nc::asarray(const std::array<_Tp, _Nm>&)': /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp:55:23: error: missing template arguments before '(' token return NdArray(inArray); ^ /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp: In function 'nc::NdArray nc::asarray(const std::vector<_RealType>&)': /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp:72:23: error: missing template arguments before '(' token return NdArray(inVector); ^ /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp: In function 'nc::NdArray nc::asarray(const std::deque<_Tp>&)': /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp:89:23: error: missing template arguments before '(' token return NdArray(inDeque); ^ /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp: In function 'nc::NdArray nc::asarray(const std::set&)': /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp:106:23: error: missing template arguments before '(' token return NdArray(inSet); ^ /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp: In function 'nc::NdArray nc::asarray(std::initializer_list<Tp>&)': /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp:124:23: error: missing template arguments before '(' token return NdArray(inList); ^ /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp: In function 'nc::NdArray nc::asarray(std::initializer_list<std::initializer_list<Tp> >&)': /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Functions/asarray.hpp:142:23: error: missing template arguments before '(' token return NdArray(inList); ^ In file included from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/DCM.hpp:35:0, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations.hpp:31, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp.hpp:44, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/ReadMe.cpp:1: /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/Quaternion.hpp: At global scope: /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/Quaternion.hpp:61:70: error: array must be initialized with a brace-enclosed initializer std::array<double, 4> components = { 0.0, 0.0, 0.0, 1.0 }; ^ /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/Quaternion.hpp:61:70: error: too many initializers for 'std::array<double, 4ul>' In file included from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/DCM.hpp:35:0, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations.hpp:31, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp.hpp:44, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/ReadMe.cpp:1: /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/Quaternion.hpp: In static member function 'static nc::rotations::Quaternion nc::rotations::Quaternion::identity()': /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/Quaternion.hpp:357:35: error: use of deleted function 'constexpr nc::rotations::Quaternion::Quaternion()' return Quaternion(); ^ In file included from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/DCM.hpp:35:0, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations.hpp:31, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp.hpp:44, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/ReadMe.cpp:1: /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/Quaternion.hpp:179:13: note: 'constexpr nc::rotations::Quaternion::Quaternion() noexcept' is implicitly deleted because its exception-specification does not match the implicit exception-specification 'noexcept (false)' Quaternion() noexcept = default; ^ In file included from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/DCM.hpp:35:0, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations.hpp:31, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp.hpp:44, from /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/ReadMe.cpp:1: /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/Quaternion.hpp: In member function 'nc::NdArray nc::rotations::Quaternion::toNdArray() const': /home/lisas/numcpp_new/numcpp_new/NumCpp/examples/ReadMe/../../include/NumCpp/Rotations/Quaternion.hpp:655:31: error: missing template arguments before '(' token return NdArray(components); ^ CMakeFiles/Example.dir/build.make:62: recipe for target 'CMakeFiles/Example.dir/ReadMe.cpp.o' failed make[2]: *** [CMakeFiles/Example.dir/ReadMe.cpp.o] Error 1 CMakeFiles/Makefile2:75: recipe for target 'CMakeFiles/Example.dir/all' failed make[1]: *** [CMakeFiles/Example.dir/all] Error 2 Makefile:83: recipe for target 'all' failed make: *** [all] Error 2

best lisa shi

opened by shixinlishixinli 6
can stack function change the input parameter type to list or vector?

i'm try to use vstack to stack a series ndarray,but the size of series is uncertain and the initializer_list can't convert from vector or list. so,can i change the implement of the stack function?

opened by novioleo 6
Creating NdArray from cv::Mat having double values

Hi I am trying to use NumCpp in my iOS project. I have a cv::Mat object with double values in it. But I am unable to create NdArray from this source. It is only allowing me to use nc::uint8 as type.

auto ncArray = nc::NdArray(textSource.data, textSource.rows, textSource.cols);

What can I do to have NdArray with double type from cv::Mat object ? Kindly provide some guidance on it.
question

opened by nasircsms 5
include problem in vscode

Describe the bug I clone the whole directory into my project file, and I wrote include "NumCpp/include/NumCpp.hpp". Then error shows up. It says that 'NumCpp/Coordinates/Coordinate.hpp' file not found. So I delete that line of code, and I found out that every include statements in NumCpp.hpp are causing errors. But I am not sure what is happening.

Expected behavior Include NumCpp.hpp file without any error or warning occurring.

Screenshots

Additional context I am using vscode on arm64 m1 MacBook pro.

Thanks.

opened by Rocky14683 4
When compiling with NumCpp getting a lot of errors
Describe the bug Installed NumCpp latest on ArchLinux using CMake, and when building using g++ getting a lot of errors. Except for the include line, I haven't even used it anywhere inside my code.

To Reproduce Steps to reproduce the behavior:

Install NumCpp using CMake

Include in a cpp file like this: #include <NumCpp.hpp>

Compile using g++ like this: g++ test.cpp -o test

Get errors: log.txt

Expected behavior Should compile normally

Screenshots If applicable, add screenshots to help explain your problem.

Additional context g++ verion: g++ (GCC) 11.2.0 c++ standard used: c++14

Expected behavior A clear and concise description of what you expected to happen.

Screenshots If applicable, add screenshots to help explain your problem.

Additional context Add any other context about the problem here.
enhancement question
opened by erikthegamer1242 4
NumCpp on Ubuntu and macOS

I am going to Numpy library C++ API on Ubuntu and macOS. how can i build NumCpp on Ubuntu and macOS? If possible, please share how to build on various platform.

opened by mauricewells 4

Could NOT find Boost

Hi I tried to install it on Ubuntu 20.04. Following error occured:

-- Compiling with C++ standard: 17
CMake Error at /usr/share/cmake-3.16/Modules/FindPackageHandleStandardArgs.cmake:146 (message):
  Could NOT find Boost (missing: Boost_INCLUDE_DIR) (Required is at least
  version "1.68.0")
Call Stack (most recent call first):
  /usr/share/cmake-3.16/Modules/FindPackageHandleStandardArgs.cmake:393 (_FPHSA_FAILURE_MESSAGE)
  /usr/share/cmake-3.16/Modules/FindBoost.cmake:2179 (find_package_handle_standard_args)
  CMakeLists.txt:47 (find_package)


-- Configuring incomplete, errors occurred!

I have done following steps:

git clone https://github.com/dpilger26/NumCpp.git
cd NumCpp
mkdir build
cd build
cmake ..

I tried to solve it with:

sudo apt install build-essential libboost-system-dev libboost-thread-dev libboost-program-options-dev libboost-test-dev

Well it does not help.

Thanks in advance.

opened by Michdo93 4

Does NumCpp support broadcast?

I did subtract operation between a vector1 with shape [2, 47] and vector2 with shape [1, 47]. The error message is:

Function: operator-
Line: 412
Error: Array dimensions do not match.libc++abi: terminating with uncaught exception of type std::invalid_argument: File: xxx/NumCpp/include/NumCpp/NdArray/NdArrayOperators.hpp
Function: operator-
Line: 412
Error: Array dimensions do not match.

It seems that NumCpp could not automatically transform vector2 into shape [2, 47]. How could I do this manually?

opened by for-just-we 1

Does NumCpp generates vectorized instructions (AVX512)?

Does NumCpp generates vectorized instructions (e.g. AVX512) after compiling with proper flags?

NumPy is able to leverage performance benefits from SIMD (vectorized) instruction set as per this link.

opened by IshaanKarnik 0
vsplit is wanted

Is your feature request related to a problem? Please describe. It would be great to have numpy.vsplit function in NumCpp, if I am not missing this in the current lib.
enhancement

opened by Ten000hours 0

Releases(Version_2.8.0)

Version_2.8.0(Jul 23, 2022)
Version 2.8.0

fixed error in inv when a zero was on the diagnol for Issue #132

fixed Issue #140

added bit_count, Computes the number of 1-bits in the absolute value of the input

added swapRows and swapCols methods to NdArray, and also free functions

added pinv, https://numpy.org/doc/stable/reference/generated/numpy.linalg.pinv.html

added take for Issue #149, https://numpy.org/doc/stable/reference/generated/numpy.take.html

new non-global random interface

added ellipse metrics to imageProcessing::Centroids

documentation updates

various minor performance improvements and bug fixes

Source code(tar.gz)
Source code(zip)
Version_2.7.0(Jan 5, 2022)
added bartlett, https://numpy.org/doc/stable/reference/generated/numpy.bartlett.html

added blackman, https://numpy.org/doc/stable/reference/generated/numpy.blackman.html

added corrcoef, https://numpy.org/doc/stable/reference/generated/numpy.corrcoef.html

added cov, https://numpy.org/doc/stable/reference/generated/numpy.cov.html

added cov_inv, the inverse covariance matrix, aka the concentration matrix

added extract, https://numpy.org/doc/stable/reference/generated/numpy.extract.html

added geomspace, https://numpy.org/doc/stable/reference/generated/numpy.geomspace.html

added hamming, https://numpy.org/doc/stable/reference/generated/numpy.hamming.html

added hanning, https://numpy.org/doc/stable/reference/generated/numpy.hanning.html

added inner, https://numpy.org/doc/stable/reference/generated/numpy.inner.html

added isneginf, https://numpy.org/doc/stable/reference/generated/numpy.isneginf.html

added isposinf, https://numpy.org/doc/stable/reference/generated/numpy.isposinf.html

added kaiser, https://numpy.org/doc/stable/reference/generated/numpy.kaiser.html

added logb, logarithm of with an arbitrary base b

added logspace, https://numpy.org/doc/stable/reference/generated/numpy.logspace.html

added nth_root, the nth root of a value

added place, https://numpy.org/doc/stable/reference/generated/numpy.place.html

added select function, https://numpy.org/doc/stable/reference/generated/numpy.select.html

fmod and the modulus % operator now work with float dtypes

added Hamming EDAC (Error Dectection and Correction) encode and decode functions, https://en.wikipedia.org/wiki/Hamming_code

various minor performance improvements and bug fixes

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Version_2.6.2(Sep 29, 2021)
tofile and fromfile will now work for generic struct dtypes

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Version_2.6.1(Sep 28, 2021)
Added more delimiter support to fromfile method

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Version_2.6.0(Sep 27, 2021)
Added linalg::solve

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Version_2.5.1(Sep 17, 2021)

Made behavior of interp function consistent with NumPy when passing in non-sorted data
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Version_2.5.0(Aug 5, 2021)
added additional NdArray slice overloads

Removed NO_MULTITHREAD compiler flag and replaced with NUMCPP_USE_MULTITHREAD so that single threaded is now the default

renamed NO_USE_BOOST compiler flag to NUMCPP_NO_USE_BOOST

renamed INCLUDE_BOOST_PYTHON_INTERFACE compiler flat to NUMCPP_INCLUDE_BOOST_PYTHON_INTERFACE

renamed INCLUDE_PYBIND_PYTHON_INTERFACE compiler flag to NUMCPP_INCLUDE_PYBIND_PYTHON_INTERFACE

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Version_2.4.2(May 8, 2021)
fixed a type error with percentile and nanpercentile

updated doxygen API css

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Version_2.4.1(Feb 5, 2021)
fixed a build error for multiply defined symbols of isLittleEndian

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Version_2.4.0(Jan 31, 2021)
Compile with NO_USE_BOOST definition to remove the Boost libraries as a dependency, with reduced functionality:

gcd with a pair of values (still available using a C++17 compliant compiler)

gcd array

lcm with a pair of values (still available using a C++17 compliant compiler)

lcm array

polynomial::chebyshev_t

polynomial::chebyshev_u

polynomial::hermite (still available using a C++17 compliant compiler)

polynomial::laguerre (still available using a C++17 compliant compiler)

polynomial::legendre_p (still available using a C++17 compliant compiler)

polynomial::legendre_q

polynomial::spherical_harmonic

random::beta

random::laplace

random::nonCentralChiSquared

random::triangle

random::uniformOnSphere

special::airy_ai

special::airy_ai_prime

special::airy_bi

special::airy_bi_prime

special::bernoulli

special::bessel_in (still available using a C++17 compliant compiler)

special::bessel_in_prime

special::bessel_jn (still available using a C++17 compliant compiler)

special::bessel_jn_prime

special::bessel_kn (still available using a C++17 compliant compiler)

special::bessel_kn_prime

special::bessel_yn (still available using a C++17 compliant compiler)

special::bessel_yn_prime

special::beta (still available using a C++17 compliant compiler)

special::cyclic_hankel_1

special::cyclic_hankel_2

special::digamma

special::erf

special::erf_inv

special::erfc

special::erfc_inv

special::gamma

special::gamma1pm1

special::log_gamma

special::polygamma

special::prime

special::riemann_zeta (still available using a C++17 compliant compiler)

special::spherical_bessel_jn (still available using a C++17 compliant compiler)

special::spherical_bessel_yn (still available using a C++17 compliant compiler)

special::spherical_hankel_1

special::spherical_hankel_2

special::trigamma

Added replace option into random::choice

Added nan_to_num function

Added complete and incomplete elliptical integrals of the first, second, and third kind to special namespace (requires either Boost or C++17 compliant compiler)

Added exponential integral to special namespace (requires either Boost or C++17 compliant compiler)

Added NO_MULTITHREAD compile definition to turn off algorithm multithreading from compliant compilers

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Version_2.3.1(Sep 9, 2020)
Added option for user defined bin edges in histogram() function.

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Version_2.3.0(Aug 31, 2020)
Added slicing to DataCube class

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Version_2.2.0(Aug 20, 2020)
Added additional where() overloads

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Version_2.1.0(Jul 23, 2020)
Improved installation and usage with CMake find_package support

Various minor improvements

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Version_2.0.0(Jun 21, 2020)
Dropped support of C++11, now requires a C++14 or higher compiler

Added support for std::complex<T>, closing Issue #58

Added more NdArray constructors for STL containers including std::vector<std::vector<T>>, closing Issue #59

Added polyfit routine inline with Numpy polyfit, closing Issue #61

Added ability to use NdArray as container for generic structs

Non-linear least squares fitting using Gauss-Newton

Root finding routines

Numerical integration routines

lu_decomposition and pivotLU_decomposition added to Linalg namespace

New STL iterators added to NdArray

iterator

const_iterator

reverse_iterator

const_reverse_iterator

column_iterator

const_column_iterator

reverse_column_iterator

const_reverse_column_iterator

Added rodriguesRotation and wahbasProblem to Rotations namespace

Various efficiency and/or bug fixes

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Version_1.3.0(Nov 20, 2020)

This is the final release version that will support C++11. Version 2.x.x will require a C++14+ compliant compiler.
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