netcdf_scheme_helpers: Use slabR Schemes with netcdf Files

In Jack-H-Laverick/nemomedusR: Tools for summarising NEMO-MEDUSA model output

Use slabR Schemes with netcdf Files

Description

These functions streamline the process of using slabR to summarise arrays contained within netcdf files

Usage

scheme_to_start(slabr_scheme = scheme, fill = 1)

scheme_to_count(slabr_scheme = scheme, fill = -1)

scheme_reframe(slabr_scheme)

Arguments

slabr_scheme	a dataframe containing a slabR summary scheme.
fill	a vector of values to add to the end of start or count objects to control extra dimensions.

Details

ncdf4 uses a convention of 2 vectors, start and count, to read in a subset of a file. 'sceheme_to_start()' and 'scheme_to_count' create the vectors to read in the minimum amount of data that contains the points needed in the summary scheme. The 'fill' argument allows you to add additional elements to the end of these vectors if necessary. NEMO_MEUDSA model outputs have a useless 4th dimension of length 1. The 'fill' default accounts for this.

Reading in a subset of data may change the indices needed in the summary scheme. If the X, Y and layer vectors used to generate the scheme were from the whole netcdf file, then using it on a smaller subset will result in index out of bound errors. 'scheme_reframe()' fixes this by rescaling the indices to start from the smallest in each dimension, now matching the netcdf subset.

See Also

Other NEMO-MEDUSA spatial tools: calculate_depth_share(), calculate_proximity_weight(), scheme_column(), scheme_interp_slice(), scheme_strathE2E(), stratify(), voronoi_grid(), xyindex_to_nindex()

Jack-H-Laverick/nemomedusR documentation built on Dec. 12, 2022, 5:21 a.m.