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Testing
C++ Standards: C++14, C++17, and C++2a Compilers: VS 2017/2019, GCC 6.5.0/7.5.0/8.4.0/9.3.0, and Clang 8.0/9.0/10.0 Boost Versions: 1.68, 1.70, 1.72, and 1.73
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
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
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.