dpilger26/NumCpp
NumCpp
NumCpp is a C++ framework and numerical computing library that provides a toolkit for multi-dimensional array management and mathematical routines. It functions as a C++ implementation of the NumPy ecosystem, offering a scientific computing framework for managing tensors and performing complex algebraic equations.
The project enables high-performance array manipulation within a C++ environment without relying on a Python runtime. It distinguishes itself by providing a NumPy-like interface for executing linear algebra, managing multi-dimensional data structures, and performing numerical processing.
The library covers a broad range of capabilities, including matrix algebraic operations, array geometry management through slicing and reshaping, and the generation of random distributions. It also includes tools for dataset analysis, array statistics, and the import and export of numerical data via binary and text formats.
Features
- Multi-Dimensional Arrays - Implements a comprehensive framework for creating and manipulating multi-dimensional arrays for scientific computing.
- NumPy-Compatible Implementations - Replicates the multi-dimensional array operations and numerical functions of the Python NumPy ecosystem in C++.
- Strided - Utilizes strided memory mapping to allow efficient array reshaping and slicing without copying data.
- Generic Type Safety - Leverages C++ templates to provide generic, type-safe multi-dimensional arrays for any numerical data type.
- Array Broadcasting - Provides array broadcasting to virtually expand smaller arrays for element-wise arithmetic operations.
- Array Geometry Management - Provides logic for controlling array geometry through reshaping, stride modifications, and size adjustments.
- Array Manipulations - Implements high-performance functions for modifying array contents, including efficient slicing, reshaping, and broadcasting.
- Array Slicing - Implements powerful array slicing to extract sub-sections based on boundaries or predicates.
- Dimensional Reductions - Implements dimensional reduction operations to aggregate multi-dimensional data along specific axes.
- Element-wise Array Operations - Implements high-performance element-wise operations that apply mathematical functions across every array member.
- Linear Algebra Routines - Provides linear algebra routines to solve algebraic equations and compute matrix norms or determinants.
- Matrix Numerical Computations - Provides algorithms for the representation and manipulation of multi-dimensional arrays using linear algebra.
- Array Initialization - Offers programmatic creation of arrays using linear spacing, identity matrices, and fixed values.
- Numerical Array Operations - Performs complex mathematical calculations, indexing, and reshaping on multi-dimensional arrays for scientific computing.
- Numerical Libraries - Offers optimized algorithms for matrix operations and mathematical calculations on large datasets.
- Contiguous Memory Buffers - Uses contiguous memory buffers to store multi-dimensional data, ensuring high cache locality and performance.
- Array Reorientation - Enables data reorientation through diagonal extraction, triangular matrix creation, and axis flipping.
- Array Binary Serialization - Enables fast loading and saving of arrays by writing raw memory contents and shape metadata directly to disk.
- Data Import and Export - Enables the import and export of numerical arrays using binary dumps and delimited text formats.
- Logical Array Operations - Provides element-wise logical operations to evaluate conditions and filter multi-dimensional data.
- Array Concatenations - Ships functions to join multiple arrays via stacking or appending into a single structure.
- Array Reductions - Accumulates values along specified axes to compute sums, products, and means for data aggregation.
- Random Distribution Generation - Produces arrays populated with random values from normal and integer distributions for simulation and testing.
- Array Statistical Aggregations - Calculates summary statistics like minimums, maximums, and unique values along specified axes.
- Scientific Computing - Provides a computational framework for performing complex mathematical modeling and large-scale scientific data analysis.
- Statistical Analysis Libraries - Provides comprehensive toolsets for calculating descriptive statistics and correlations across multi-dimensional datasets.
- Scalar Mathematical Functions - Implements absolute value, trigonometric, logarithmic, and power functions for numeric types across arrays.
- Array Equality Comparison - Provides utilities for element-wise equality checks and identifying divergent indices between numerical datasets.
- Mathematical Libraries - C++ implementation of NumPy.
- Mathematics - Template-based C++ implementation of NumPy.
- Mathematics and Statistics - C++ implementation of NumPy-style functionality.
