numops
Lightweight Numerical Operations
Provides dependency-free helpers for recurring numerical tasks on vectors, matrices, and arrays. Operations cover bounds, interpolation, remapping, division, Euclidean norms, normalization, and adjacent differences. Multi-input operations use strict scalar recycling, reject incompatible lengths, and preserve names, dimensions, and dimension names where applicable. Explicit handling of invalid intervals, zero denominators, and zero norms gives consistent behavior for common edge cases.
numops
numops provides small, dependency-free numerical operations for vectors, matrices, and arrays. It collects common tasks that otherwise require repeated base R expressions and gives them consistent validation, scalar recycling, and shape-preserving behavior.
Installation
You can install the development version of numops from GitHub with:
# install.packages("pak")
pak::pak("Macosso/numops")
Overview
| Task | Functions |
|---|---|
| Restrict or wrap values | clamp(), clamp01(), in_range(), wrap() |
| Transform ranges | lerp(), inv_lerp(), remap(), midpoint() |
| Handle division by zero | divide_or() |
| Compute or normalize Euclidean length | l2_norm(), normalize_l2() |
| Preserve-length differences | adjacent_difference() |
Usage
library(numops)
Bounds and periodic values
Clamp values to a closed interval or wrap them to a half-open periodic interval:
clamp01(c(-1, 0.25, 1.5))
#> [1] 0.00 0.25 1.00
wrap(c(-10, 0, 370), lower = 0, upper = 360)
#> [1] 350 0 10
Interpolation and remapping
Interpolate between endpoints or map values from one interval to another:
lerp(10, 20, c(0, 0.25, 1))
#> [1] 10.0 12.5 20.0
remap(c(0, 50, 100), from = c(0, 100), to = c(-1, 1))
#> [1] -1 0 1
Values outside the source interval are extrapolated rather than clamped.
Division with a fallback
Choose the result returned where a denominator is zero:
divide_or(
c(12, 8, 5),
c(3, 0, 2),
default = NA_real_
)
#> [1] 4.0 NA 2.5
Vector, matrix, and array norms
Use margin to compute or normalize independent slices. For matrices,
margin = 1 selects rows and margin = 2 selects columns:
x <- matrix(
c(3, 4, 0, 1, 2, 2),
nrow = 2,
byrow = TRUE
)
l2_norm(x, margin = 1)
#> [1] 5 3
normalize_l2(x, margin = 1)
#> [,1] [,2] [,3]
#> [1,] 0.6000000 0.8000000 0.0000000
#> [2,] 0.3333333 0.6666667 0.6666667
Recycling and output shape
Functions with multiple numeric inputs use strict scalar recycling. Each input must have length one or a shared length; other length combinations are errors. Length-one inputs are recycled to the shared length.
Names, dimensions, and dimnames are copied from the first input already having the shared length. Functions that transform a single object preserve its shape.
Getting help
If you find a bug or have a feature request, please open an issue on the GitHub issue tracker.