Broadcasted Array Operations Like 'NumPy'
broadcast Package Overview
Details on Broadcasted Operators
Details on Casting Functions
Simple and Fast Casting/Pivoting of an Array
Predict Broadcasted Dimensions
Broadcasted Ifelse
Broadcasted Boolean Operations
Broadcasted Bit-wise Operations
Broadcasted Complex Numeric Operations
Broadcasted Decimal Numeric Operations
Broadcasted Integer Numeric Operations with Extra Overflow Protection
Broadcasted Operations for Recursive Arrays
Broadcasted Operations that Take Raw Arrays and Return Raw Arrays
Broadcasted General Relational Operators
Broadcasted String Operations
Apply Function to Pair of Arrays with Broadcasting
Dimensional Binding of Arrays with Broadcasting
Check or Set if an Array is a Broadcaster
Cast Dimensional List into a Flattened List
Cast Dimensional List into Hierarchical List
Cast Hierarchical List into Dimensional list
Drop Redundant List Nesting
Helper Functions For cast_hier2dim
Simple Linear Algebra Functions for Statistics
Get the Number of Dimensions of an Array
Replicate Array Dimensions
Atomic and List Type Casting With Names and Dimensions Preserved
Implements efficient 'NumPy'-like broadcasted operations for atomic and recursive arrays. In the context of operations involving 2 (or more) arrays, “broadcasting” refers to efficiently recycling array dimensions without allocating additional memory. Besides linking to 'Rcpp', 'broadcast' does not use any external libraries in any way; 'broadcast' was essentially made from scratch and can be installed out-of-the-box. The implementations available in 'broadcast' include, but are not limited to, the following. 1) Broadcasted element-wise operations on any 2 arrays; they support a large set of relational, arithmetic, Boolean, string, and bit-wise operations. 2) A faster, more memory efficient, and broadcasted abind-like function, for binding arrays along an arbitrary dimension. 3) Broadcasted ifelse-like, and apply-like functions. 4) Casting functions, that cast subset-groups of an array to a new dimension, cast nested lists to dimensional lists, and vice-versa. 5) A few linear algebra functions for statistics. The functions in the 'broadcast' package strive to minimize computation time and memory usage (which is not just better for efficient computing, but also for the environment).
Useful links