Read data from a file (or source) using the NetCDF library directly.

read_ncdf(
.x,
...,
var = NULL,
ncsub = NULL,
curvilinear = character(0),
eps = 1e-12,
ignore_bounds = FALSE,
make_time = TRUE,
make_units = TRUE
)

## Arguments

.x NetCDF file or source ignored variable name or names (they must be on matching grids) matrix of start, count columns (see Details) length two character named vector with names of variables holding longitude and latitude values for all raster cells. stars attempts to figure out appropriate curvilinear coordinates if they are not supplied. numeric; dimension value increases are considered identical when they differ less than eps logical; should bounds values for dimensions, if present, be ignored? if TRUE (the default), an atttempt is made to provide a date-time class from the "time" variable if TRUE (the default), an attempt is made to set the units property of each variable

## Details

The following logic is applied to coordinates. If any coordinate axes have regularly spaced coordinate variables they are reduced to the offset/delta form with 'affine = c(0, 0)', otherwise the values of the coordinates are stored and used to define a rectilinear grid.

If the data has two or more dimensions and the first two are regular they are nominated as the 'raster' for plotting.

If the curvilinear argument is used it specifies the 2D arrays containing coordinate values for the first two dimensions of the data read. It is currently assumed that the coordinates are 2D and that they relate to the first two dimensions in that order.

If var is not set the first set of variables on a shared grid is used.

start and count columns of ncsub must correspond to the variable dimemsion (nrows) and be valid index using var.get.nc convention (start is 1-based). If the count value is NA then all steps are included. Axis order must match that of the variable/s being read.

## Examples

f <- system.file("nc/reduced.nc", package = "stars")
#> no 'var' specified, using sst, anom, err, ice#> other available variables:
#>  lon, lat, zlev, time#> No projection information found in nc file.
#>  Coordinate variable units found to be degrees,
#>  assuming WGS84 Lat/Lon.#> stars object with 4 dimensions and 4 attributes
#> attribute(s):
#>                Min. 1st Qu. Median       Mean 3rd Qu.  Max.  NA's
#> sst [°C]      -1.80   -0.03 13.655 12.9940841 24.8125 32.97  4448
#> anom [°C]     -7.95   -0.58 -0.080 -0.1847324  0.2100  2.99  4449
#> err [°C]       0.11    0.16  0.270  0.2626872  0.3200  0.84  4448
#> ice [percent]  0.01    0.47  0.920  0.7178118  0.9600  1.00 13266
#> dimension(s):
#>      from  to offset delta  refsys point         values x/y
#> lon     1 180     -1     2  WGS 84    NA           NULL [x]
#> lat     1  90    -90     2  WGS 84    NA           NULL [y]
#> zlev    1   1     NA    NA      NA    NA              0
#> time    1   1     NA    NA POSIXct    NA 1981-12-31 UTC    read_ncdf(f, var = c("anom"))
#> No projection information found in nc file.
#>  Coordinate variable units found to be degrees,
#>  assuming WGS84 Lat/Lon.#> stars object with 4 dimensions and 1 attribute
#> attribute(s):
#>            Min. 1st Qu. Median       Mean 3rd Qu. Max. NA's
#> anom [°C] -7.95   -0.58  -0.08 -0.1847324    0.21 2.99 4449
#> dimension(s):
#>      from  to offset delta  refsys point         values x/y
#> lon     1 180     -1     2  WGS 84    NA           NULL [x]
#> lat     1  90    -90     2  WGS 84    NA           NULL [y]
#> zlev    1   1     NA    NA      NA    NA              0
#> time    1   1     NA    NA POSIXct    NA 1981-12-31 UTC    read_ncdf(f, ncsub = cbind(start = c(1, 1, 1, 1), count = c(10, 12, 1, 1)))
#> no 'var' specified, using sst, anom, err, ice#> other available variables:
#>  lon, lat, zlev, time#> No projection information found in nc file.
#>  Coordinate variable units found to be degrees,
#>  assuming WGS84 Lat/Lon.#> stars object with 4 dimensions and 4 attributes
#> attribute(s):
#>                Min. 1st Qu. Median        Mean 3rd Qu. Max. NA's
#> sst [°C]      -1.39 -0.7200 -0.515 -0.53399999  -0.275 0.03   90
#> anom [°C]     -1.07 -0.3625  0.195  0.05866667   0.555 0.92   90
#> err [°C]       0.30  0.3000  0.300  0.30299999   0.300 0.32   90
#> ice [percent]  0.01  0.1100  0.170  0.20937500   0.255 0.52  104
#> dimension(s):
#>      from to offset delta  refsys point         values x/y
#> lon     1 10     -1     2  WGS 84    NA           NULL [x]
#> lat     1 12    -90     2  WGS 84    NA           NULL [y]
#> zlev    1  1     NA    NA      NA    NA              0
#> time    1  1     NA    NA POSIXct    NA 1981-12-31 UTC

#' precipitation data in a curvilinear NetCDF
prec_file = system.file("nc/test_stageiv_xyt.nc", package = "stars")
prec = read_ncdf(prec_file, curvilinear = c("lon", "lat"), ignore_bounds = TRUE)
#> no 'var' specified, using Total_precipitation_surface_1_Hour_Accumulation#> other available variables:
#>  time_bounds, lon, lat, time#> No projection information found in nc file.
#>  Coordinate variable units found to be degrees,
#>  assuming WGS84 Lat/Lon.
##plot(prec) ## gives error about unique breaks
## remove NAs, zeros, and give a large number
## of breaks (used for validating in detail)
qu_0_omit = function(x, ..., n = 22) {
x = units::drop_units(na.omit(x))
c(0, quantile(x[x > 0], seq(0, 1, length.out = n)))
}
library(dplyr)
prec_slice = slice(prec, index = 17, along = "time")
plot(prec_slice, border = NA, breaks = qu_0_omit(prec_slice[[1]]), reset = FALSE)
nc = sf::read_sf(system.file("gpkg/nc.gpkg", package = "sf"), "nc.gpkg")
plot(st_geometry(nc), add = TRUE, reset = FALSE, col = NA)