convert objects into a stars object

st_as_stars(.x, ...)

# S3 method for list
st_as_stars(.x, ..., dimensions = NULL)

# S3 method for default
st_as_stars(.x = NULL, ..., raster = NULL)

# S3 method for stars
st_as_stars(.x, ..., curvilinear = NULL, crs = st_crs(4326))

# S3 method for bbox
st_as_stars(
  .x,
  ...,
  nx,
  ny,
  dx = dy,
  dy = dx,
  xlim = .x[c("xmin", "xmax")],
  ylim = .x[c("ymin", "ymax")],
  values = 0,
  n = 64800,
  pretty = FALSE,
  inside = FALSE,
  nz
)

# S3 method for sf
st_as_stars(.x, ..., name = attr(.x, "sf_column"))

# S3 method for Raster
st_as_stars(.x, ..., att = 1, ignore_file = FALSE)

# S3 method for ncdfgeom
st_as_stars(.x, ..., sf_geometry = NA)

# S3 method for stars_proxy
st_as_stars(
  .x,
  ...,
  downsample = 0,
  url = attr(.x, "url"),
  envir = parent.frame()
)

# S3 method for data.frame
st_as_stars(.x, ..., dims = 1:2, xy = dims[1:2], y_decreasing = TRUE)

# S3 method for xts
st_as_stars(.x, ..., dimensions)

# S3 method for OpenStreetMap
st_as_stars(.x, ..., as_col = FALSE)

Arguments

.x	object to convert
...	in case `.x` is of class `bbox`, arguments passed on to pretty
dimensions	object of class dimensions
raster	character; the names of the dimensions that denote raster dimensions
curvilinear	only for creating curvilinear grids: named length 2 list holding longitude and latitude matrices; the names of this list should correspond to raster dimensions referred to
crs	object of class `crs` with the coordinate reference system of the values in `curvilinear`; see details
nx	integer; number of cells in x direction; see details
ny	integer; number of cells in y direction; see details
dx	numeric; cell size in x direction; see details
dy	numeric; cell size in y direction; see details
xlim	length 2 numeric vector with extent (min, max) in x direction
ylim	length 2 numeric vector with extent (min, max) in y direction
values	value(s) to populate the raster values with
n	the (approximate) target number of grid cells
pretty	logical; should cell coordinates have pretty values?
inside	logical; should all cells entirely fall inside the bbox, potentially not covering it completely?
nz	integer; number of cells in z direction; if missing no z-dimension is created.
name	character; name for the geometry dimensions
att	see factorValues; column in the RasterLayer's attribute table
ignore_file	logical; if `TRUE`, ignore the Raster object file name
sf_geometry	sf data.frame with geometry and attributes to be added to stars object. Must have same number of rows as timeseries instances.
downsample	integer: if larger than 0, downsample with this rate (number of pixels to skip in every row/column); if length 2, specifies downsampling rate in x and y.
url	character; URL of the stars endpoint where the data reside
envir	environment to resolve objects in
dims	the column names or indexes that form the cube dimensions
xy	the x and y raster dimensions
y_decreasing	logical; if TRUE, (numeric) y values get a negative delta (decrease with increasing index)
as_col	logical; return rgb numbers (FALSE) or (character) color values (TRUE)?

Details

if curvilinear is a stars object with longitude and latitude values, its coordinate reference system is typically not that of the latitude and longitude values.

For the bbox method: if pretty is TRUE, raster cells may extend the coordinate range of .x on all sides. If in addition to nx and ny, dx and dy are also missing, these are set to a single value computed as sqrt(diff(xlim)*diff(ylim)/n). If nx and ny are missing, they are computed as the ceiling of the ratio of the (x or y) range divided by (dx or dy), unless inside is TRUE, in which case ceiling is replaced by floor. Postive dy will be made negative. Further named arguments (...) are passed on to pretty.

For the ncdfgeom method: objects are point-timeseries with optional line or polygon geometry for each timeseries specified with the sf_geometry parameter. See ncdfgeom for more about this NetCDF-based format for geometry and timeseries.

for the xts methods, if dimensions are provided, time has to be the first dimension.

Examples

data(Produc, package = "plm")
st_as_stars(Produc, y_decreasing = FALSE)
#> stars object with 2 dimensions and 9 attributes
#> attribute(s):
#>     region           pcap              hwy            water        
#>  Min.   :1.000   Min.   :  2627   Min.   : 1827   Min.   :  228.5  
#>  1st Qu.:3.000   1st Qu.:  7097   1st Qu.: 3858   1st Qu.:  764.5  
#>  Median :5.000   Median : 17572   Median : 7556   Median : 2266.5  
#>  Mean   :4.958   Mean   : 25037   Mean   :10218   Mean   : 3618.8  
#>  3rd Qu.:7.000   3rd Qu.: 27692   3rd Qu.:11267   3rd Qu.: 4318.7  
#>  Max.   :9.000   Max.   :140217   Max.   :47699   Max.   :24592.3  
#>      util               pc               gsp              emp         
#>  Min.   :  538.5   Min.   :  4053   Min.   :  4354   Min.   :  108.3  
#>  1st Qu.: 2488.3   1st Qu.: 21651   1st Qu.: 16502   1st Qu.:  475.0  
#>  Median : 7008.8   Median : 40671   Median : 39987   Median : 1164.8  
#>  Mean   :11199.5   Mean   : 58188   Mean   : 61014   Mean   : 1747.1  
#>  3rd Qu.:11598.5   3rd Qu.: 64796   3rd Qu.: 68126   3rd Qu.: 2114.1  
#>  Max.   :80728.1   Max.   :375342   Max.   :464550   Max.   :11258.0  
#>      unemp       
#>  Min.   : 2.800  
#>  1st Qu.: 5.000  
#>  Median : 6.200  
#>  Mean   : 6.602  
#>  3rd Qu.: 7.900  
#>  Max.   :18.000  
#> dimension(s):
#>       from to offset delta refsys point              values x/y
#> state    1 48     NA    NA     NA    NA ALABAMA,...,WYOMING [x]
#> year     1 17   1986    -1     NA    NA                NULL [y]