Package 'cppdoubles'

Description

Fast and efficient methods for comparing floating point numbers using relative differences.

Usage

x %~==% y

x %~>=% y

x %~>% y

x %~<=% y

x %~<% y

double_equal(x, y, tol = get_tolerance())

double_gte(x, y, tol = get_tolerance())

double_gt(x, y, tol = get_tolerance())

double_lte(x, y, tol = get_tolerance())

double_lt(x, y, tol = get_tolerance())

Arguments

Details

When either x[i] or y[i] contain a number very close to zero, absolute differences are used, otherwise relative differences are used.

The output of double_equal() is commutative, which means the order of arguments don't matter whereas this is not the case for all.equal.numeric().

The calculation is done in C++ and is quite efficient. Recycling follows the usual R rules and is done without allocating additional memory.

Value

A logical vector.

Examples

library(cppdoubles)

### Basic usage ###

# Standard equality operator
sqrt(2)^2 == 2

# approximate equality operator
sqrt(2)^2 %~==% 2

sqrt(2)^2 %~>=% 2
sqrt(2)^2 %~<=% 2
sqrt(2)^2 %~>% 2
sqrt(2)^2 %~<% 2

# Alternatively
double_equal(2, sqrt(2)^2)
double_gte(2, sqrt(2)^2)
double_lte(2, sqrt(2)^2)
double_gt(2, sqrt(2)^2)
double_lt(2, sqrt(2)^2)

rel_diff(1, 1 + 2e-10)
double_equal(1, 1 + 2e-10, tol = sqrt(.Machine$double.eps))
double_equal(1, 1 + 2e-10, tol = 1e-10)

# Optionally set a threshold for all comparison
options(cppdoubles.tolerance = 1e-10)
double_equal(1, 1 + 2e-10)

# Floating point errors magnified example

x1 <- 1.1 * 100 * 10^200
x2 <- 110 * 10^200

abs_diff(x1, x2) # Large absolute difference
rel_diff(x1, x2) # Very small relative difference as expected

double_equal(x1, x2)

# all.equal is not commutative but double_equal is
all.equal(10^-8, 2 * 10^-8)
all.equal(2 * 10^-8, 10^-8)

double_equal(10^-8, 2 * 10^-8)
double_equal(2 * 10^-8, 10^-8)

# All comparisons are vectorised and recycled

double_equal(sqrt(1:10),
             sqrt(1:5),
             tol = c(-Inf, 1e-10, Inf))

# One can check for whole numbers like so
whole_number <- function(x, tol = get_tolerance()){
  double_equal(x, round(x))
}
whole_number(seq(-5, 5, 0.25))

Description

A memory-efficient alternative to all.equal.numeric().

Usage

all_equal(x, y, tol = get_tolerance(), na.rm = FALSE)

Arguments

Details

all_equal compares each pair of double-precision floating point numbers in the same way as double_equal. If any numbers differ, the algorithm breaks immediately, which can offer significant speed when there are differences at the start of a vector. All arguments are recycled except na.rm.

Value

A logical vector of length 1.

The result should match all(double_equal(x, y)), including the way NA values are handled.

Examples

library(cppdoubles)
library(bench)
x <- seq(0, 1, 0.2)
y <- sqrt(x)^2

all_equal(x, y)

# Comparison to all.equal
z <- runif(10^4, 1, 100)
ones <- rep(1, length(z))
mark(base = isTRUE(all.equal(z, z)),
            cppdoubles = all_equal(z, z),
            iterations = 100)
mark(base = isTRUE(all.equal(z, ones)),
            cppdoubles = all_equal(z, ones),
            iterations = 100)

Description

Calculate absolute differences with abs_diff() and relative differences with rel_diff()

Usage

rel_diff(x, y, scale = NA_real_)

abs_diff(x, y)

Arguments

Details

Relative difference

The relative difference in this package is calculated as abs_diff(x / scale, y / scale) except in the case that both x and y are approximately 0 which results in 0.

The scale is calculated as max(abs(x), abs(y)) by default when scale is NA. This has the nice property of making rel_diff() a commutative function in which the order of the arguments doesn't matter. You can of course supply your own scale.

For info, an R way to calculate the relative difference is as follows

  r_rel_diff <- function(x, y){
    ax <- abs(x)
    ay <- abs(y)
    scale <- pmax(ax, ay)
    ifelse(
      ax < sqrt(.Machine$double.eps) & ay < sqrt(.Machine$double.eps),
      0,
      abs_diff(x / scale, y / scale)
    )
  }

This is much slower than the C++ written rel_diff.

Comparison with all.equal()

As mentioned above, unlike base::all.equal(), rel_diff() is commutative. To match the relative difference calculation used by all.equal(), simply set scale = x.

Therefore, to make a vectorised binary version of all.equal(), we can write for example the following:

  all.equal2 <- \(x, y, tol = get_tolerance()) rel_diff(x, y, scale = x) < tol

Value

A numeric vector.

Description

Get and set package-wide tolerance

Usage

get_tolerance()

set_tolerance(x)

Arguments

Value

Either sets or gets the tolerance to be used package-wide.