Package 'csquares'

Convert lon-lat coordinates into c-square codes

Description

Takes WGS84 longitude and latitude coordinates and finds the closest matching c-squares for a given resolution.

Usage

as_csquares(x, resolution, csquares, ...)

## Default S3 method:
as_csquares(x, resolution, csquares, ...)

## S3 method for class 'character'
as_csquares(x, resolution, csquares, validate = TRUE, ...)

## S3 method for class 'numeric'
as_csquares(x, resolution = 1, csquares, ...)

## S3 method for class 'data.frame'
as_csquares(x, resolution = 1, csquares, ...)

## S3 method for class 'sf'
as_csquares(x, resolution = 1, csquares, ..., use_centroids = TRUE)

## S3 method for class 'sfc'
as_csquares(x, resolution = 1, csquares, ..., use_centroids = TRUE)

## S3 method for class 'stars'
as_csquares(x, resolution = 1, csquares, ...)

Arguments

x	An object to be coerced to a csquares object. x can be a vector of character strings representing c-squares code. It can also be a numeric matrix with two columns containing the x and y coordinates. x can also be a simple features object (sf) or a spatial arrays object (stars).
resolution	Resolution (in WGS84 degrees) to be used for creating c-squares codes. As per c-square specifications, the resolution should be 10 or less, yet greater than 0. It should be a tenfold of 1 or 5. Valid resolutions are therefore: 10, 5, 1, 0.5, 0.1, etc.
csquares	If x is not a vector of character strings (but for instance a data.frame), the csquares argument should specify the name of the element of x containing the c-square codes as character strings.
...	Currently ignored
validate	A logical value indicating whether the created object needs to be validated. Defaults to TRUE. Validation can be time-consuming so set to FALSE to save computing time.
use_centroids	In case x is a simple features object and use_centroids is TRUE, the centroid of each geometry is used for deriving c-squares. If it is FALSE all coordinates in the geometry are used.

Value

Returns a csquares object that contains c-squares codes.

Author(s)

Pepijn de Vries

Examples

as_csquares(cbind(x = 5.2399066, y = 52.7155812), resolution = 1)
orca_csq <- as_csquares(orca, csquares = "csquares")

---

Drop c-square information from object

Description

Drops c-square data from an object, but keeps the parent class of the object intact. You cannot deselect the csquare column from a csquares object as this will render the object invalid. Use drop_csquares instead.

Usage

drop_csquares(x, ...)

Arguments

x	An object of class csquares from which the c-square information needs to be dropped.
...	ignored

Value

Returns a copy of x inheriting its parent classes but with out csquares info.

Author(s)

Pepijn de Vries

Examples

csq <- as_csquares("1000")
drop_csquares(csq)

csq <-
  data.frame(csquares = "1000", foo = "bar") |>
  as_csquares(csquares = "csquares")

drop_csquares(csq)

---

Expand c-squares with wildcards to all matching c-squares

Description

The asterisk (*) can be used as a wildcard, for a compact notation of csquares. expand_wildcards will replace all wild cards with valid combinations of values and expands the compact notation to an explicit notation without wildcards. Check out vignette("wildcards") for more details.

Usage

expand_wildcards(x, csquares, ...)

Arguments

x	A character string containing csquares codes with wildcards (asterisk character); or a data.frame that contains a column with csquares codes with wildcards
csquares	When x is data.frame this argument should specify the column name that contains the csquares codes with wildcards.
...	ignored

Value

Returns a csquares object with full notation

Author(s)

Pepijn de Vries

Examples

expand_wildcards("1000:*")
expand_wildcards("1000:***")
expand_wildcards("1000:1**")
expand_wildcards("1000:***:*")
expand_wildcards(c("1000:*", "1000:***", "1000:1**", "1000:***:*"))

expand_wildcards(data.frame(csq = "1000:*", foo = "bar"), csquares = "csq")

---

Basic csquares methods

Description

Basic S3 methods for handling csquares objects

Usage

## S3 method for class 'csquares'
format(x, ...)

## S3 method for class 'csquares'
print(x, short = TRUE, ...)

## S3 method for class 'csquares'
as.character(x, ...)

## S3 method for class 'csquares'
summary(object, ...)

## S3 method for class 'csquares'
as.data.frame(x, ...)

## S3 method for class 'csquares'
c(...)

## S3 method for class 'csquares'
rbind(..., deparse.level = 1)

## S3 method for class 'csquares'
cbind(..., deparse.level = 1)

## S3 method for class 'csquares'
x[i, j, ..., drop = FALSE]

## S3 method for class 'csquares'
x[[i]]

## S3 method for class 'csquares'
x$name

## S3 replacement method for class 'csquares'
x[i, j] <- value

## S3 replacement method for class 'csquares'
x[[i]] <- value

## S3 replacement method for class 'csquares'
x$i <- value

## S3 method for class 'csquares'
merge(x, y, ...)

## S3 replacement method for class 'csquares'
names(x) <- value

Arguments

x, object	A csquares object to be handled by the s3 methods
...	Passed on to generic methods
short	logical option to print csquares vctrs_vec. If TRUE it will only print one line, if FALSE it will print up to options("max.print") records.
deparse.level	integer controlling the construction of labels in the case of non-matrix-like arguments (for the default method): deparse.level = 0 constructs no labels; the default deparse.level = 1 typically and deparse.level = 2 always construct labels from the argument names, see the ‘Value’ section below.
i, j, name	Indices/name for selecting subsets of x
drop	logical value indicating if unused dimensions should be dropped
value	Replacement values for a subset. a csquares object or a character string that can be coerced to a csquares object
y	A data.frame to be merged with x

Value

Returns (a subsetted / formatted / modified version of) x

---

Get ICES geometries

Description

Functions to convert ICES rectangles

Usage

ices_centroids(ices_rect)

ices_rectangles(ices_rect)

ices_to_csquares(ices_rect)

ices_from_csquares(csquares)

Arguments

ices_rect	A character vector containing valid ICES rectangle codes
csquares	A csquares object, or an object that can be coerced with as_csquares().

Value

In case of ices_centroids a sf::st_sf() object is returned, with POINT geometries representing the centroids of the ICES rectangles.

In case of ices_rectangles a sf::st_sf() object is returned, with POLYGON geometries representing the outline of the ICES rectangles.

In case of ices_to_csquares a csquares object inheriting from sf::st_sf() is returned, the csquares code should represent the ICES rectangles.

In case of ices_from_csquares a character vector is returned with ICES rectangle codes that correspond with the csquares. The method is fast yet crude: it only checks in which ICES rectangles the centroids of the csquares are located. It does not check if the resolution matches. NA values are returned when csquares are situated outside the area covered by ICES rectangles.

Author(s)

Pepijn de Vries

Examples

ices_rects <-
  c("31F21", "31F22", "31F23", "31F24", "31F25", "31F26", "31F27", "31F28", "31F29",
    "32F2", "33F2", "34F2", "35F2",
    "31F3", "32F3", "33F3", "34F3", "35F3",
    "31F4", "32F4", "33F4", "34F4", "35F4")
ices_centroids(ices_rects)
ices_rectangles(ices_rects)
ices_csq <- ices_to_csquares(ices_rects)
ices_from_csquares(ices_csq)

---

Valid ICES rectangle columns

Description

Get all valid column codes of ICES rectangles. Note that ICES subrectangles are not compatible with csquares. For more details see vignette("ices").

Usage

ices_columns()

Value

A character vector with all allowed codes for the columns in ICES rectangles.

Examples

ices_columns()

---

Match c-squares against other c-squares (with wildcards)

Description

Checks if csquares codes in table matches values in x. Wildcards are allowed in table for this comparison. Check out vignette("wildcards") for more details.

Usage

in_csquares(x, table, strict = FALSE, mode = "any", ...)

Arguments

x	An object of class 'csquares' that will be checked for matching values in table
table	A character string representing a csquares code. The code can contain wildcards (asterisk * and percentage ⁠%⁠ characters, both having identical meaning). Any symbol in x will result in a positive match against the wildcard. table can also be of class csquares, but these objects cannot contain wildcards.
strict	When set to FALSE, a match is positive when the start of x, matches against values in table, even when x has a higher resolution. When set to TRUE, a match is only positive when the resolution of x and table is identical.
mode	Two modes are allowed: "all" and "any". When an element of x consists of multiple raster cells, it the mode will determine whether a match is positive or not. In case of "all", all raster cells in the element of x need to match with the cells in table, for a positive match. In case of "any", any match will do.
...	Ignored

Value

Returns a vector of logical values with the same number of elements or rows as x

Author(s)

Pepijn de Vries

Examples

library(dplyr)

in_csquares(orca$csquares, c("3400:2", "5515:3"))
in_csquares(orca$csquares, "3400:2|5515:3")

## Percentage symbols are interpreted the same as asterisk symbols
## both are wild cards
in_csquares(orca$csquares, "1%%%:%") |>
  table()

## Same as above
in_csquares(orca$csquares, "1***:*") |>
  table()
 
## Also same as above
in_csquares(orca$csquares, "1***", strict = FALSE) |>
  table()

## Strict interpretation results in no matches
in_csquares(orca$csquares, "1***", strict = TRUE) |>
  table()

## Filter orca data to North Eastern quadrant (1***:*) only:
orca |>
  filter(
    in_csquares(csquares, "1***:*")
  ) |>
  nrow()

---

Join csquares objects using tidyverse conventions

Description

When a csquares object inherits from class data.frame, you can apply tidyverse joins to the object (?dplyr::join). The functions implemented here make sure that the csquares properties are preserved. The functions should be called via the dplyr generics. So load the dplyr package first, then call the function without the .csquares suffix (see examples). When x inherits from stars, only left_join is supported.

Usage

inner_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

left_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

right_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

full_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

semi_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

anti_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

st_join.csquares(x, y, join, ..., suffix = c(".x", ".y"))

Arguments

x, y	A pair of data frames, data frame extensions (e.g. a tibble), or lazy data frames (e.g. from dbplyr or dtplyr). See Methods, below, for more details.
by	A join specification created with join_by(), or a character vector of variables to join by. If NULL, the default, ⁠*_join()⁠ will perform a natural join, using all variables in common across x and y. A message lists the variables so that you can check they're correct; suppress the message by supplying by explicitly. To join on different variables between x and y, use a join_by() specification. For example, join_by(a == b) will match x$a to y$b. To join by multiple variables, use a join_by() specification with multiple expressions. For example, join_by(a == b, c == d) will match x$a to y$b and x$c to y$d. If the column names are the same between x and y, you can shorten this by listing only the variable names, like join_by(a, c). join_by() can also be used to perform inequality, rolling, and overlap joins. See the documentation at ?join_by for details on these types of joins. For simple equality joins, you can alternatively specify a character vector of variable names to join by. For example, by = c("a", "b") joins x$a to y$a and x$b to y$b. If variable names differ between x and y, use a named character vector like by = c("x_a" = "y_a", "x_b" = "y_b"). To perform a cross-join, generating all combinations of x and y, see cross_join().
copy	If x and y are not from the same data source, and copy is TRUE, then y will be copied into the same src as x. This allows you to join tables across srcs, but it is a potentially expensive operation so you must opt into it.
suffix	If there are non-joined duplicate variables in x and y, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
...	Other parameters passed onto methods.
join	geometry predicate function with the same profile as st_intersects; see details

Author(s)

Pepijn de Vries

Examples

if (requireNamespace(c("sf", "dplyr"))) {
  library(csquares)
  library(sf)
  library(dplyr)
  orca_sf <- orca |> as_csquares(csquares = "csquares") |> st_as_sf()
  right_table <- data.frame(csquares = c("1000:1", "1004:1"), foo = "bar")
  
  orca_join <- left_join (orca_sf, right_table, by = "csquares")
  orca_join <- right_join(orca_sf, right_table, by = "csquares")
  orca_join <- inner_join(orca_sf, right_table, by = "csquares")
  orca_join <- anti_join (orca_sf, right_table, by = "csquares")
  orca_join <- semi_join (orca_sf, right_table, by = "csquares")
  orca_grid <- new_csquares(orca_sf, 5)
  orca_grid <- left_join(orca_grid, orca, by = "csquares")
}

---

Create a c-squares raster from a bounding box

Description

Creates a spatial raster (stars) with c-square codes for a specified bounding box, using a specified resolution. The raster will be conform c-squares specifications.

Usage

new_csquares(x, resolution = 1, crs = 4326)

Arguments

x	An object of class bbox or an object that can be coerced to a bbox. It defines the bounding box for the c-squares grid created by this function.
resolution	Resolution (in WGS84 degrees) to be used for creating c-squares codes. As per c-square specifications, the resolution should be 10 or less, yet greater than 0. It should be a tenfold of 1 or 5. Valid resolutions are therefore: 10, 5, 1, 0.5, 0.1, etc.
crs	The projection to be used for the created grid. By default it is WGS84 (EPSG:4326).

Value

Returns a stars and csquares object based on the provided bounding box and resolution.

Author(s)

Pepijn de Vries

Examples

library(sf)
nc <- st_read(system.file("shape/nc.shp", package = "sf"))
new_csquares(nc)

---

Killer whale realm

Description

Killer whale realm

Usage

orca

Format

orca

The orca object is a Killer whale realm data set extracted from the data as provided by Costello (2017) and published by Costello et al. (2017). It is a data frame with 2,058 rows and two columns:

csquares

c-squares codes indicating spatial grid cells

orcinus_orca

logical values indicating whether the corresponding c-squares grid cell belongs to the killer whales (Orcinus orca) biogeographic realm or not.

References

• Costello, M.J. (2017); University of Auckland doi:10.17608/k6.auckland.5086654 Licence CC BY 4.0

• Costello M.J., Tsai P., Wong P.S., Cheung A.K.L, Basher Z. & Chaudhary C. (2017); "Marine biogeographic realms and species endemicity" Nature Communications 8, 1057 doi:10.1038/s41467-017-01121-2

---

Resample csquares to a different resolution

Description

Resample csquares objects to higher or lower resolutions.

Usage

resample_csquares(x, method = "target", ..., resolution, magnitude = 1L)

Arguments

x	A csquares object to be resampled to a different resolution
method	Method for determining the resolution of the resulting csquares. Should be one of "target", "min", "max", "up", or "down". "target" will resample x to the level specified with resolution
...	When x inherits the stars class and the resulting object has a lower resolution than x, the dots are passed on to dplyr::summarise(). This allows you to summarise columns to the lower resolution.
resolution	Resolution (in WGS84 degrees) to be used for creating c-squares codes. As per c-square specifications, the resolution should be 10 or less, yet greater than 0. It should be a tenfold of 1 or 5. Valid resolutions are therefore: 10, 5, 1, 0.5, 0.1, etc.
magnitude	When method == "up" or "down", this parameter specifies the number of steps to increase or decrease the resolution. Should be a positive integer.

Value

A csquares object based on x

Author(s)

Pepijn de Vries

Examples

csq    <- as_csquares(c("1000", "5000:2|5000:100", "3000:100:100"))
csq_df <- as_csquares(data.frame(csq = csq, foobar = letters[1:3]), csquares = "csq")

## Resample csquares based on the one with the lowest resolution:
resample_csquares(csq,    "min")

## Resample csquares to a specific resolution
resample_csquares(csq,    "target", resolution = 5)

## Same, but applied to a csquares object inheriting from a data.frame
resample_csquares(csq_df, "target", resolution = 5)

## Same, but applied to a csquares object inheriting the `sf` class
## Note that the geometry is updated based on the resampled csquares
if (requireNamespace("sf")) {
  library(sf)
  csq_sf <- st_as_sf(csq_df)
  resample_csquares(csq_sf, "target", resolution = 5)
}

## Resample csquares one step down.
resample_csquares(csq,    "down")
resample_csquares(csq_df, "down")

if (requireNamespace(c("dplyr", "stars"))) {
  ## Csquares objects can inherit from the stars class as well.
  ## These too can be resampled. But additional columns need
  ## to be summarised when the resulting resolution is lower
  ## than the original:
  g <-
    sf::st_bbox(c(xmin = 4.0, xmax = 6.5, ymin = 52.5, ymax = 53), crs = 4326) |>
      new_csquares(resolution = 0.1) |>
      ## add a column with some random positive numbers:
      dplyr::mutate(random = .data$csquares |> length() |> rnorm() |> exp())

  ## Resample stars object to lower resolution
  g_sum <- resample_csquares(g, resolution = 10, random = sum(random, na.rm = TRUE))

  ## And back to a higher resolution (note that you have lost information as it was summarised
  ## in the previous step)
  resample_csquares(g_sum, "up", random = sum(random, na.rm = TRUE))
}

---

Create a simple features object from c-squares

Description

Converts a character string of c-squares in a spatially explicit simple features object (sf. It can also convert data.frames with a column of c-squares codes to an sf object.

Usage

st_as_sf.csquares(x, ..., use_geometry = TRUE)

st_as_sfc.csquares(x, ..., use_geometry = TRUE)

Arguments

x	A vector of character strings. Each element should hold a valid c-square code. x can also be a data.frame with a column of c-square codes. (Note that wildcard characters are not supported)
...	Ignored
use_geometry	If use_geometry is TRUE and x inherits a spatial feature, its geometry will be used to cast the object. This is much faster than its alternative when use_geometry is FALSE. In the latter case, the c-square codes are first translated into explicit spatial information. The latter is more reliable as it does not rely on the assumption that the geometry of x corresponds with the csquares codes in the object. In short: use TRUE for speed, use FALSE for reliability.

Value

In case of st_as_sfc.csquares a list of geometries (sfc, (MULTI)POLYGONS) is returned. In case of st_as_sf.csquares an object of class (sf) is returned.

Author(s)

Pepijn de Vries

Examples

library(sf)
st_as_sfc(as_csquares("7500:110:3|7500:110:1|1500:110:3|1500:110:1"))
st_as_sf(as_csquares("7500:110:3|7500:110:1|1500:110:3|1500:110:1"))

---

Coerce csqaures object into a stars object

Description

Take a csquares object created with new_csquares or as_csquares and coerce it to a spatiotemporal array (stars).

Usage

st_as_stars.csquares(x, ...)

Arguments

x	An object of class csquares created with new_csquares or as_csquares
...	ignored.

Value

Returns a spatiotemporal array (stars) object based on x.

Author(s)

Pepijn de Vries

Examples

library(stars)
st_as_stars(as_csquares("7500:110:3|7500:110:1|1500:110:3|1500:110:1"))
st_as_stars(as_csquares(orca, csquares = "csquares"))

---

Tidyverse methods for csquares objects (drop the 'csquares'-suffix)

Description

Tidyverse methods for csquares objects that inherit from data.frame, tibble, sf, or in some cases stars. Load the tidyverse package containing the generic implementation (dplyr or tidyr), and call the function without the .csquares suffix. See examples and vignette("tidy") for more details. The methods implemented here ensure that the csquare class is preserved.

Usage

filter.csquares(.data, ..., .dots)

select.csquares(.data, ...)

as_tibble.csquares(x, ...)

arrange.csquares(.data, ..., .dots)

group_by.csquares(.data, ..., add = FALSE)

ungroup.csquares(.data, ...)

rowwise.csquares(.data, ...)

mutate.csquares(.data, ..., .dots)

rename.csquares(.data, ...)

rename_with.csquares(.data, .fn, .cols, ...)

slice.csquares(.data, ..., .dots)

distinct.csquares(.data, ..., .keep_all = FALSE)

summarise.csquares(.data, ..., .dots)

pivot_longer.csquares(
  data,
  cols,
  ...,
  cols_vary = "fastest",
  names_to = "name",
  names_prefix = NULL,
  names_sep = NULL,
  names_pattern = NULL,
  names_ptypes = NULL,
  names_transform = NULL,
  names_repair = "check_unique",
  values_to = "value",
  values_drop_na = FALSE,
  values_ptypes = NULL,
  values_transform = NULL
)

pivot_wider.csquares(
  data,
  ...,
  id_cols = NULL,
  id_expand = FALSE,
  names_from = NULL,
  names_prefix = "",
  names_sep = "_",
  names_glue = NULL,
  names_sort = FALSE,
  names_vary = "fastest",
  names_expand = FALSE,
  names_repair = "check_unique",
  values_from = NULL,
  values_fill = NULL,
  values_fn = NULL,
  unused_fn = NULL
)

group_split.csquares(.tbl, ..., .keep = TRUE)

nest.csquares(.data, ...)

unite.csquares(data, col, ..., sep = "_", remove = TRUE)

unnest.csquares(data, ..., .preserve = NULL)

unnest.csquares_nested(data, cols, ...)

drop_na.csquares(x, ...)

Arguments

.data, ..., .dots, data, x, add, .fn, .cols, .keep_all, cols, cols_vary, names_to, names_prefix, names_sep, names_pattern, names_ptypes, names_transform, names_repair, values_to, values_drop_na, values_ptypes, values_transform, id_cols, id_expand, names_from, names_glue, names_sort, names_vary, names_expand, values_from, values_fill, values_fn, unused_fn, .tbl, .keep, col, sep, remove, .preserve

Passed to tidyverse generic methods. Consult their documentation.

Details

Note that the implementation of summarise.csquares has changed since version 0.0.5.002, to better reflect the dplyr generic implementation. To get results similar to the earlier implementation please use resample_csquares().

Author(s)

Pepijn de Vries

Examples

if (requireNamespace(c("dplyr", "tidyr"))) {
  library(dplyr)
  library(tidyr)
  
  ## Create a csquares object from the orca dataset:
  orca_csq <- as_csquares(orca, csquares = "csquares")
  
  ## Filter values that belong to the killer whale realm:
  orca2 <- filter(orca_csq, orcinus_orca == TRUE)
  
  ## Mutate the object to hold information on the quadrant:
  orca_csq <- mutate(orca_csq, quadrant = csquares |> as.character() |> substr(1,1))
  
  ## Select the quadrant column:
  orca2 <- select(orca_csq, quadrant)
  
  ## Convert it into a tibble:
  orca_csq <- as_tibble(orca_csq)
  
  ## Arrange by quadrant:
  orca2 <- arrange(orca_csq, quadrant)
  
  ## Group by quadrant:
  orca_csq <- group_by(orca_csq, quadrant)
  
  ## Summarise per quadrant:
  summarise(orca_csq, realm_frac = sum(orcinus_orca)/n())
  
  #' Introduce a group split:
  orca2 <- group_split(orca_csq)
  
  ## Ungroup the object:
  orca_csq <- ungroup(orca_csq)
  
  ## Take a slice of the first three rows:
  slice(orca_csq, 1:3)
  
  ## Take a sample of 10 rows with replacement:
  slice_sample(orca_csq, n = 10, replace = TRUE)
  
  ## Rename a column:
  rename(orca_csq, quad = "quadrant")
  rename_with(orca_csq, toupper, starts_with("quad"))
  
  ## Distinct will remove any duplicated rows:
  orca_csq[c(1, 1, 1),] |> distinct()
  
  ## Pivot to a wide format:
  pivot_wider(orca_csq, names_from = "quadrant", values_from = "orcinus_orca")
  pivot_wider(orca_csq, names_from = "orcinus_orca", values_from = "orcinus_orca",
              id_cols = "quadrant", values_fn = length)
  
  ## Pivot to a long format (note that you can't pivot the csquares column to long)
  tibble(csq = "1000", a = 1, b = 2, d = 3) |>
    as_csquares(csquares = "csq") |>
    pivot_longer(c("a", "b", "d"), names_to = "letter", values_to = "numeric")
  
  ## Unite two columns into one:
  unite(orca_csq, "quad_realm", any_of(c("quadrant", "orcinus_orca")))
  
  ## As the csquares column gets nested in the example below,
  ## the resulting object is no longer of class csquares:
  orca_nest <- nest(orca_csq, nested_data = c("csquares", "orcinus_orca"))
  
  ## Unnest it:
  unnest(orca_nest, "nested_data")
}

---

Test if a csquares object is valid

Description

Tests if a csquares object is correctly specified and can be translated into valid coordinates

Usage

validate_csquares(x)

Arguments

x	An object of class csquares to be evaluated.

Value

Returns a logical value indicating whether the csquares object is valid or not.

Author(s)

Pepijn de Vries

Examples

validate_csquares(
  as_csquares("7500:110:3|7500:110:1|1500:110:3|1500:110:1")
)

---

vctrs methods for csquares objects

Description

Implementations to support csquare vctrs operations. There is no need to call these functions directly.

Usage

vec_cast.csquares(x, to, ...)

## S3 method for class 'csquares'
vec_cast.csquares(x, to, ...)

## S3 method for class 'character'
vec_cast.csquares(x, to, ...)

## Default S3 method:
vec_cast.csquares(x, to, ...)

vec_ptype2.csquares(x, y, ...)

## S3 method for class 'character'
vec_ptype2.csquares(x, y, ...)

## S3 method for class 'csquares'
vec_ptype2.csquares(x, y, ...)

## Default S3 method:
vec_ptype2.csquares(x, y, ..., x_arg = "x", y_arg = "y")

Arguments

x, y	Vector types.
to	Types to cast to. If NULL, x will be returned as is.
...	Ignored.
x_arg, y_arg	Argument names for x and y.

---