Experimental features

Multi-file support

Multiple files can also be aggregated over a given dimensions (or the record dimension). In this example, 3 sea surface temperature fields from the 1992-01-01 to 1992-01-03 are aggregated using the OpenDAP service from PODAAC.

using NCDatasets, Printf, Dates

function url(dt)
  doy = @sprintf("%03d",Dates.dayofyear(dt))
  y = @sprintf("%04d",Dates.year(dt))
  yyyymmdd = Dates.format(dt,"yyyymmdd")
  return "https://podaac-opendap.jpl.nasa.gov:443/opendap/allData/ghrsst/data/GDS2/L4/GLOB/CMC/CMC0.2deg/v2/$y/$doy/$(yyyymmdd)120000-CMC-L4_GHRSST-SSTfnd-CMC0.2deg-GLOB-v02.0-fv02.0.nc"
end

ds = NCDataset(url.(DateTime(1992,1,1):Dates.Day(1):DateTime(1992,1,3)),aggdim = "time");
SST2 = ds["analysed_sst"][:,:,:];
close(ds)

If there is a network or server issue, you will see an error message like NetCDF: I/O failure.

Experimental functions

NCDatasets.ancillaryvariables — Function

ncvar = NCDatasets.ancillaryvariables(ncv::NCDatasets.CFVariable,modifier)

Return the first ancillary variables from the NetCDF variable ncv with the standard name modifier modifier. It can be used for example to access related variable like status flags.

source

Base.filter — Function

data = NCDatasets.filter(ncv, indices...; accepted_status_flags = nothing)

Load and filter observations by replacing all variables without an acepted status flag to missing. It is used the attribute ancillary_variables to identify the status flag.

# da["data"] is 2D matrix
good_data = NCDatasets.filter(ds["data"],:,:, accepted_status_flags = ["good_data","probably_good_data"])

source