Skip to contents

Compute basic statistics for gridded (NetCDF or raster) data

Source: R/basic_stats_nc.R
basic_stats_nc.Rd

Computes a comprehensive set of over 30 summary statistics for every grid cell in a spatial time series. The function accepts an sxts object, a Raster* object, or a NetCDF file path with variable name. When filename and varname are supplied, the data are first imported via nc2xts and additional arguments are forwarded to that function. For raster inputs the layer names are parsed for dates, and the raster values are converted to an xts matrix. The returned raster has one layer per statistic; layer names correspond to the rows of the basic_stats output.

Usage

basic_stats_nc(
  data = NULL,
  filename = NA,
  varname = NA,
  ignore_zeros = FALSE,
  zero_threshold = 0.01,
  ...
)

Arguments

data

An sxts object, or a Raster* object. Leave as NULL when supplying filename and varname instead.

filename

A NetCDF file name to import. Ignored when data is supplied directly.

varname

The name of the variable to extract from filename.

ignore_zeros

Logical. If TRUE, values at or below zero_threshold are excluded from distributional statistics. Default is FALSE.

zero_threshold

Numeric threshold below which values are treated as zero. Default is 0.01.

...

Additional arguments passed to nc2xts when filename and varname are provided.

Value

A RasterBrick with one layer per statistic. The layer names correspond to the statistic labels (e.g. "Mean", "StDev", "Skewness", "Pdr", etc.). The spatial reference (projection and extent) is inherited from the input.

Examples

if (FALSE) { # \dontrun{
# From an sxts object (e.g. output of nc2xts)
s <- nc2xts(filename = "precip.nc", varname = "pr")
r <- basic_stats_nc(data = s, ignore_zeros = TRUE)
raster::plot(r[["Mean"]])

# Direct from NetCDF (shortcut — nc2xts is called internally)
r <- basic_stats_nc(filename = "precip.nc", varname = "pr",
                     ignore_zeros = TRUE)
} # }