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Creating numeric series

Source: vignettes/creating-numeric-series.Rmd
creating-numeric-series.Rmd

The discretes package lets you create basic numeric series in two main ways:

Arithmetic series — Use arithmetic() or the wrappers integers(), natural1(), and natural0() for common cases (all integers, positive integers starting at 1, non-negative integers starting at 0).

From a numeric vector — Use as_discretes() to turn an existing numeric vector into a numeric series.

Once you have a base series, you can create new ones by subsetting, combining, or transforming.

Subsetting and combining

Arithmetic and standard functions

Arithmetic — The operations +, -, *, /, ^ are supported when one side is a number and the other is a numeric series. For example:

integers()^2
#> Loading required namespace: testthat
#> Union series of length Inf:
#> 0, 1, 4, 9, 16, 25, ...
2 * natural1() - 1   # odd positive integers
#> Linear-transformed series of length Inf:
#> 1, 3, 5, 7, 9, 11, ...
1 / 2^integers()     # reciprocals of powers of 2
#> Reciprocal series of length Inf:
#> ..., 0.25, 0.5, 1, 2, 4, 8, ...

Length-0 vectors are allowed, too, but result in empty series (like for base R vectors)

numeric(0L) * natural1()
#> Empty series.

Mathematical functions — exp() is supported. For non-negative series, log(), log2(), log10(), and sqrt() are also supported:

log(natural0())
#> Transformed series of length Inf:
#> -Inf, 0, 0.6931472, 1.098612, 1.386294, 1.609438, ...

Other functions may be able to be applied as well; use dsct_transform() for those (see below).

Custom transformations: dsct_transform()

For other transformations, use dsct_transform(). On a numeric vector, the function is applied directly:

dsct_transform(0:10, cos) # Same as cos(0:10)
#>  [1]  1.0000000  0.5403023 -0.4161468 -0.9899925 -0.6536436  0.2836622
#>  [7]  0.9601703  0.7539023 -0.1455000 -0.9111303 -0.8390715

When transforming an object of class "discretes" there are more restrictions so that querying the series can be defined from the base series.

  1. The function and its inverse must be vectorized and element-wise (no cumsum()-style dependence on other elements).
  2. You must supply the domain and range of the function. This defaults to all real numbers.
  3. The function must be strictly monotonic over the given domain.

Here is an example of applying the function pnorm(). The range is (0, 1), so it must be given explicitly:

dsct_transform(
  natural0(),
  fun = pnorm,
  inv = qnorm,
  range = c(0, 1)
)
#> Transformed series of length Inf:
#> 0.5, 0.8413447, 0.9772499, 0.9986501, 0.9999683, 0.9999997, ...

For a function that is monotonic only on an interval, restrict the domain. For example, cos() is decreasing on [0, pi] with range [-1, 1], and inverse acos(). Specify dir = "decreasing" to indicate that this is a decreasing function.

dsct_transform(
  integers(from = 0, to = 3),
  fun = cos,
  inv = acos,
  domain = c(0, pi),
  range = c(-1, 1),
  dir = "decreasing"
)
#> Transformed series of length 4:
#> -0.9899925, -0.4161468, 0.5403023, 1