broadcast (version 0.1.7)

cast_hier2dim: Cast Hierarchical List into Dimensional list

Description

cast_hier2dim() casts a hierarchical/nested list into a dimensional list (i.e. an array of type list).

This method comes with 2 helper functions:
hier2dim and hiernames2dimnames methods.
See their help page for details.

Usage

cast_hier2dim(x, ...)
# S3 method for default
cast_hier2dim(
  x,
  in2out = TRUE,
  maxdepth = 16L,
  recurse_all = FALSE,
  padding = list(NULL),
  direction.names = 0L,
  ...
)

Value

An array of type list, with the dimensions given by hier2dim.

If the output needs padding (indicated by hier2dim), the output will have more elements than x, filled with a padding value (as specified in the padding argument).

If direction.names = 0 (default), the result will not have any dimnames;

the dimnames can then still be constructed using hiernames2dimnames.

If direction.names is 1 or -1, the result will have dimnames.

Arguments

x

a nested list.
If x has redundant nesting, it is advisable (though not necessary) to reduce the redundant nesting using dropnests.

...

further arguments passed to or from methods.

in2out, recurse_all

see broadcast_casting.

maxdepth

a single, positive integer, giving the maximum depth to recurse into the list.
The surface-level elements of a list is depth 1.

padding

a list of length 1, giving the padding value to use when padding is required.
Padding is used to ensure every all slices of the same dimension in the output have equal number of elements (for example, all rows must have the same number of columns).

direction.names

see argument direction from the hiernames2dimnames method.

See Also

broadcast_casting, hier2dim, hiernames2dimnames

Examples

# Example 1: Basics ====
x <- list(
  group1 = list(
    class1 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    ),
    class2 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    )
  ),
  group2 = list(
    class1 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    ),
    class2 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    )
  )
)

# predict what dimensions `x` would have if casted as dimensional:
hier2dim(x)

x2 <- cast_hier2dim(x) # cast as dimensional

# since the original list uses the same names for all elements within the same depth,
# dimnames can be set easily:
dimnames(x2) <- hiernames2dimnames(x)

print(x2)


################################################################################


# Example 2: Cast from outside to inside ====
x <- list(
  group1 = list(
    class1 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    ),
    class2 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    )
  ),
  group2 = list(
    class1 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    ),
    class2 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    )
  )
)

# by default, `in2out = TRUE`;
# for this example, `in2out = FALSE` is used

# predict what dimensions `x` would have if casted as dimensional:
hier2dim(x, in2out = FALSE)

x2 <- cast_hier2dim(x, in2out = FALSE) # cast as dimensional

# since the original list uses the same names for all elements within the same depth,
# dimnames can be set easily:
# because in2out = FALSE, go from the shallow names to the deeper names:
dimnames(x2) <- hiernames2dimnames(x, in2out = FALSE)

print(x2)


################################################################################


# Example 3: padding ====

# For Example 3, take the same list as before, but remove x$group1$class2:

x <- list(
  group1 = list(
    class1 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    )
  ),
  group2 = list(
    class1 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    ),
    class2 = list(
      height = rnorm(10, 170),
      weight = rnorm(10, 80),
      sex = sample(c("M", "F", NA), 10, TRUE)
    )
  )
)


hier2dim(x) # as indicated here, dimension 2 (i.e. columns) will have padding

# casting this to a dimensional list will resulting in padding with `NULL`:
x2 <- cast_hier2dim(x)
print(x2)
# The `NULL` values are added for padding.
# This is because all slices of the same dimension need to have the same number of elements.  
# For example, all rows need to have the same number of columns.

# one can also use custom padding:
x2 <- cast_hier2dim(x, padding = list(~ "this is padding"))
print(x2)

dimnames(x2) <- hiernames2dimnames(x)

print(x2)


# we can also use in2out = FALSE:
x2 <- cast_hier2dim(x, in2out = FALSE, padding = list(~ "this is padding"))
dimnames(x2) <- hiernames2dimnames(x, in2out = FALSE)
print(x2)