Read gridded data in various formats — read

read_grid is a generic function to read gridded data from a file. A transformation can optionally be applied to those data.

Usage

read_grid(
  file_name,
  parameter,
  is_forecast = TRUE,
  dttm = NULL,
  file_format = NULL,
  file_format_opts = list(),
  vertical_coordinate = c("pressure", "model", "height", NA),
  lead_time = NULL,
  members = NULL,
  transformation = c("none", "interpolate", "regrid", "xsection", "subgrid"),
  transformation_opts = list(),
  param_defs = get("harp_params"),
  show_progress = TRUE,
  data_frame = FALSE,
  readable_times = TRUE,
  spread_members = FALSE,
  ...
)

read_grid_interpolate(file_name, parameter, file_format = NULL, ...)

Arguments

file_name: A character string with the (full) file name.
parameter: The parameter to be read.
is_forecast: Logical. If TRUE (the default), data are filtered based on the forecast initialization time and the lead time. If FALSE, the data are filtered on the valid time.
dttm: A vector of date time strings of the form YYYYMMDD, YYYYMMDDhh, YYYYMMDDhhmm, or YYYYMMDDhhmmss. For forecast data these would be the forecast initialization times. seq_dttm can be used to generate a vector of equally spaced date-time strings.
file_format: The file format. Possible values include grib, netcdf, FA, hdf5... Whatever the value is, it is supposed to correspond to a function "read_XXX" that can deal with the format. If not specified, the format can often be guessed correctly from file extension or the first few bytes.
file_format_opts: Options for the file format as generated by one of the options functions, e.g. netcdf_opts.
vertical_coordinate: The vertical coordinate for upper air data. May be "pressure" for pressure levels, "model" for model levels or "height" for height levels.
lead_time: The lead times to read from a forecast file. If set to NULL, all lead times will be read from the file.
members: For ensemble data, the ensemble members to read from the file. If set to NULL all members will be read.
transformation: The transformation to apply to the gridded data. Can be "none", "interpolate", "regrid" or "xsection".
transformation_opts: Options for the transformation as generated by interpolate_opts, regrid_opts or xsection_opts.
param_defs: A list of parameter definitions that includes the file format to be read. By default the built in list harp_params is used. Modifications and additions to this list can be made using modify_param_def and add_param_def respectively.
show_progress: Show progress when reading large amounts of data.
data_frame: Logical. For compatibility with current version of harpSpatial, make sure only a geofield is returned rather than a data frame when set to FALSE.
readable_times: When data_frame = TRUE, whether to convert times in unix format to a data-time format. The default is TRUE.
spread_members: When data_frame = TRUE, whether to spread the members into a column for each member.
...: All arguments passed to the specified reader function.

Value

A geofield or (possibly) a plain matrix.

Examples

if (requireNamespace("Rgrib2", quietly = TRUE) & requireNamespace("harpData", quietly = TRUE)) {
  read_grid(
    system.file(
      "grib/AROME_Arctic/2018/07/10/00/fc2018071000+000grib_fp",
      package = "harpData"
    ),
    parameter = "T2m"
  )
  read_grid(
    system.file(
      "grib/AROME_Arctic/2018/07/10/00/fc2018071000+000grib_fp",
       package = "harpData"
    ),
    parameter = "S10m"
  )
  read_grid(
    system.file(
      "grib/AROME_Arctic/2018/07/10/00/fc2018071000+000grib_fp",
       package = "harpData"
    ),
    parameter = "tcc"
  )
}
#> Reading /home/andrewts/R/x86_64-pc-linux-gnu-library/4.3/harpData/grib/AROME_Arctic/2018/07/10/00/fc2018071000+000grib_fp
#> Reading /home/andrewts/R/x86_64-pc-linux-gnu-library/4.3/harpData/grib/AROME_Arctic/2018/07/10/00/fc2018071000+000grib_fp
#> Reading /home/andrewts/R/x86_64-pc-linux-gnu-library/4.3/harpData/grib/AROME_Arctic/2018/07/10/00/fc2018071000+000grib_fp
#> eidb : TCC Total cloud cover  
#> Time:
#>  2018/07/10 00:00 +0
#> Domain summary:
#> 100 x 100 domain
#> Projection summary:
#> proj= lcc 
#> NE = ( 23.31109 , 78.2607 )
#> SW = ( 8.042 , 77.968 )
#> Data summary:
#> 0.01281738 1 1 0.9805575 1 1