Package 'SeedMaker'

Generate a vector of seeds

Description

seed_gen() generates a vector of seeds from a single seed.

Usage

seed_gen(seed, n, sample_vector = 1:1e+06)

Arguments

seed	A number, interpreted as an integer, or NULL (see set.seed()).
n	The number of seeds to generate.
sample_vector	The values from which to sample (without replacement).

Details

length(sample_vector) must be >= n.

The values of sample_vector must be unique, positive integers.

Value

An integer vector containing n randomly drawn values from sample_vector.

Examples

seeds1 <- seed_gen(
  seed = 1234,
  n = 10
)

seeds2 <- seed_gen(
  seed = 1234,
  n = 10,
  sample_vector = 1:100
)

---

Construct a list containing a collection of seeds

Description

seed_maker() constructs a hierarchical list containing a collection of seeds from a single seed.

Usage

seed_maker(
  seed,
  level_names,
  n_per_level,
  sample_vector = rep(list(rlang::expr(1:1e+06)), length(level_names)),
  index_level = rep(TRUE, length(level_names)),
  flatten = FALSE
)

Arguments

seed	A number, interpreted as an integer, or NULL (see set.seed()).
level_names	A character vector, or list of character vectors, indicating the element name(s) to use for each level of the returned list.
n_per_level	An integer vector indicating the number of elements to produce at each level of the returned list.
sample_vector	A list of expressions that are evaluable as integer vectors indicating the values from which to sample (without replacement) at each level of the returned list.
index_level	A logical vector indicating whether to index the root name of a respective level.
flatten	"Flatten" the lowest level of the returned list into a named vector?

Details

length(level_names) must be equal to length(n_per_level) must be equal equal to length(sample_vector) must be equal to length(index_level). When these arguments are greater than length 1, the intermediate seeds used to produce the seeds at the lowest level of the returned list are not included therein. In other words, only the collection of seeds at the lowest list level are returned.

If level_names is a character vector, each of its elements is used as the root name for the list elements produced at the respective level. See seeds_list1 and seeds_list2 in Examples.

If level_names is a list of character vectors:

• The element contained in a length 1 vector is used as the root name for the list elements produced at the respective level.

• Elements contained in a vector that is greater than length 1 are used verbatim as the names for the list elements produced at the respective level. The corresponding value of n_per_level must match the length of the vector.

See seeds_list3, seeds_list4, and seeds_list5 in Examples.

For each element, i, of sample_vector:

• length(eval(sample_vector[[i]])) must be >= n_per_level[i].

• The values of eval(sample_vector[[i]]) must be unique, positive integers.

See seeds_list6, seeds_list7, and seeds_list8 in Examples.

Element name indexing applies to root name-provided levels only. Thus, for each element, i, of index_level, if length(level_names[[i]]) is greater than 1, the value of index_level[i] is ignored. Otherwise:

• When index_level[i] is TRUE, the element names at the respective level are indexed from 1 - n_per_level[i].

• When index_level[i] is FALSE, the element name at the respective level is used verbatim, so long as n_per_level[i] = 1, since suppressing element name indexing makes sense only for single-element levels.

See seeds_list9, seeds_list10, seeds_list11, seeds_list12, and seeds_list13 in Examples.

When flatten is set to TRUE, each set of seeds at the lowest level of the returned list is converted into a named vector (versus remaining in the default structure, which is a list of single value elements). When only a single level is specified (via level_names, n_per_level, sample_vector, and index_level all being length 1), a named integer vector is returned instead of a list. See seeds_flat1, seeds_flat2, seeds_flat5, seeds_flat9, seeds_flat10, and seeds_flat11 in Examples.

Value

When flatten is set to FALSE, a hierarchical list with length(level_names) levels containing a collection of seeds.

When flatten is set to TRUE, a hierarchical list with length(level_names) - 1 level(s) containing a collection of seeds (where "0 levels" corresponds to a named integer vector - see Details).

Examples

seeds_list1 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(10)
)

seeds_list2 <- seed_maker(
  seed = 1234,
  level_names = c("sim", "dataset"),
  n_per_level = c(10, 15)
)

seeds_list3 <- seed_maker(
  seed = 1234,
  level_names = list("sim", c("component_a", "component_b", "component_c")),
  n_per_level = c(10, 3)
)

try(seeds_list4 <- seed_maker(
  seed = 1234,
  level_names = list("sim", c("component_a", "component_b", "component_c")),
  n_per_level = c(10, 4)
))

seeds_list5 <- seed_maker(
  seed = 1234,
  level_names = list(
    "sim",
    c("component_a", "component_b", "component_c"),
    "dataset"
  ),
  n_per_level = c(10, 3, 5)
)

seeds_list6 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(10),
  sample_vector = list(1:100)
)

seeds_list7 <- seed_maker(
  seed = 1234,
  level_names = c("sim", "dataset"),
  n_per_level = c(10, 15),
  sample_vector = list(1:100, 1:1000)
)

seeds_list8 <- seed_maker(
  seed = 1234,
  level_names = list(
    "sim",
    c("component_a", "component_b", "component_c"),
    "dataset"
  ),
  n_per_level = c(10, 3, 5),
  sample_vector = list(1:100, 1:1000, 1:10000)
)

seeds_list9 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(1)
)

try(seeds_list10 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(10),
  index_level = FALSE
))

seeds_list11 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(1),
  index_level = FALSE
)

seeds_list12 <- seed_maker(
  seed = 1234,
  level_names = list("sim", c("component_a", "component_b", "component_c")),
  n_per_level = c(1, 3),
  index_level = c(FALSE, TRUE)
)

seeds_list13 <- seed_maker(
  seed = 1234,
  level_names = list("sim", c("component_a", "component_b", "component_c")),
  n_per_level = c(1, 3),
  index_level = c(FALSE, FALSE)
)

identical(seeds_list12, seeds_list13)

seeds_flat1 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(10),
  flatten = TRUE
)

is.list(seeds_flat1)
is.integer(seeds_flat1)

seeds_flat2 <- seed_maker(
  seed = 1234,
  level_names = c("sim", "dataset"),
  n_per_level = c(10, 15),
  flatten = TRUE
)

is.list(seeds_flat2$sim1)
is.integer(seeds_flat2$sim1)

seeds_flat5 <- seed_maker(
  seed = 1234,
  level_names = list(
    "sim",
    c("component_a", "component_b", "component_c"),
    "dataset"
  ),
  n_per_level = c(10, 3, 5),
  flatten = TRUE
)

is.list(seeds_flat5$sim1$component_a)
is.integer(seeds_flat5$sim1$component_a)

seeds_flat9 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(1),
  flatten = TRUE
)

is.list(seeds_flat9)
is.integer(seeds_flat9)

try(seeds_flat10 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(10),
  index_level = FALSE,
  flatten = TRUE
))

seeds_flat11 <- seed_maker(
  seed = 1234,
  level_names = c("sim"),
  n_per_level = c(1),
  index_level = FALSE,
  flatten = TRUE
)

is.list(seeds_flat11)
is.integer(seeds_flat11)

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