7 repository-uri
Merging multiple arrays through concatenation, stacking, or coordinate grid creation.
Distinct from Array Manipulations: Focuses on combining multiple arrays into one, distinct from modifying the contents of a single array.
Explore 7 awesome GitHub repositories matching scientific & mathematical computing · Array Combinations. Refine with filters or upvote what's useful.
This project is a structured learning curriculum and technical reference for mastering deep learning with TensorFlow. It provides a comprehensive guide for building, training, and deploying neural networks, combining theoretical fundamentals with practical implementation examples. The repository distinguishes itself by covering the end-to-end machine learning workflow, from low-level tensor mathematics and linear algebra to the creation of complex model architectures. It includes specific guidance on developing data pipelines for diverse data types, such as images, text, and time-series seque
Implements merging of multiple tensors through concatenation, stacking, and other array combination methods.
This project is an educational resource and a collection of instructional materials for performing data manipulation and statistical analysis using Python. It provides a comprehensive set of guides and code examples for using the Pandas, NumPy, and Matplotlib libraries to analyze structured data. The resource includes a dedicated guide for reshaping, cleaning, and aggregating tabular data and time series via Pandas, alongside a reference for high-performance vectorized operations and linear algebra using NumPy. It also features tutorials for creating publication-quality charts, distribution p
Provides capabilities to join multiple arrays along specified axes or split arrays into sub-arrays.
LearnPython is a programming tutorial consisting of a collection of practical code examples used to demonstrate Python language features and programming patterns. It serves as a comprehensive learning resource that implements core language concepts through functional code. The project provides specialized guides and samples covering several key domains. These include asynchronous network programming with event loops and coroutines, data visualization using numerical datasets for 2D and 3D plots, and web scraping for fetching content and automating login flows. It also features instructions on
Shows how to combine arrays through concatenation and stacking to manage data layouts.
collect.js is a dependency-free JavaScript library that provides a fluent, chainable interface for manipulating arrays and objects. It mirrors the Laravel Collection API, offering a consistent set of methods for data transformation across JavaScript and Laravel backend environments. The library stores collection data as plain arrays internally and supports fluent method chaining, where each method returns a new collection instance. The library distinguishes itself by closely replicating the Laravel Collection API in JavaScript, mapping each PHP method to an equivalent JavaScript implementatio
Merges a collection of arrays into a single flat collection.
ndarray is a multidimensional array library for Rust that serves as a linear algebra framework and scientific computing tool. It provides the core infrastructure for creating and manipulating n-dimensional arrays, functioning as both a parallel array processor and a toolkit for numerical data analysis. The library distinguishes itself by providing efficient slicing and memory views, allowing for data sharing without copying. It leverages optimized backend math libraries for high-speed matrix multiplication and distributes heavy mathematical iterations across multiple CPU threads to accelerate
Joins arrays together by stacking them along new axes or concatenating them along existing ones.
more-itertools is an extension library for the Python itertools module. It serves as a toolkit for manipulating iterables, providing a wide range of routines for data transformation, combinatorial generation, and iterator state management. The library distinguishes itself through advanced state management and complex sequence generation. It provides capabilities for peeking at future elements, seeking within sequences, and producing unique permutations, combinations, and set partitions from collections that may contain duplicate elements. Its broader capability surface covers data processing
Generates partial products to explore combinations across multiple collections without producing every possible pair.
xtensor is a C++ multidimensional array library for numerical computing that provides N-dimensional containers with an interface mirroring the NumPy API. It utilizes a lazy evaluation expression engine to defer numerical computations until assignment, which minimizes memory allocations and intermediate copies. The library features a foreign memory array adaptor that allows it to wrap external buffers, such as NumPy arrays, to perform numerical operations in-place without duplicating data. It further optimizes performance through lazy broadcasting and a system that manages the lifetime of temp
Provides methods to merge multiple arrays via concatenation, stacking, or the creation of coordinate grids.