dpilger26/NumCpp
NumCpp
NumCpp ist ein C++-Framework und eine Bibliothek für numerische Berechnungen, die ein Toolkit für die Verwaltung mehrdimensionaler Arrays und mathematische Routinen bereitstellt. Es fungiert als C++-Implementierung des NumPy-Ökosystems und bietet ein wissenschaftliches Rechen-Framework für die Verwaltung von Tensoren und die Durchführung komplexer algebraischer Gleichungen.
Das Projekt ermöglicht eine leistungsstarke Array-Manipulation innerhalb einer C++-Umgebung, ohne auf eine Python-Laufzeit angewiesen zu sein. Es zeichnet sich dadurch aus, dass es eine NumPy-ähnliche Schnittstelle für die Ausführung linearer Algebra, die Verwaltung mehrdimensionaler Datenstrukturen und die Durchführung numerischer Verarbeitung bietet.
Die Bibliothek deckt ein breites Spektrum an Funktionen ab, einschließlich matrixalgebraischer Operationen, Array-Geometrieverwaltung durch Slicing und Reshaping sowie die Generierung von Zufallsverteilungen. Sie enthält zudem Tools für die Datensatzanalyse, Array-Statistiken sowie den Import und Export numerischer Daten über Binär- und Textformate.
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.
