Coarsening spatial resolution for gridded data

Description

coarseR is a helper function that helps coarsening spatial resolution of the input matrix for the HiClimR function.

Usage

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coarseR(x=x, lon=lon, lat=lat, lonStep=1, latStep=1, verbose = TRUE)

Arguments

x

an (N rows by M columns) matrix of 'double' values: N objects (spatial points or stations) to be clustered by M observations (temporal points or years). For gridded data, the N objects should be created from the original matrix x0 using as.vector(t(x0)), where x0 is an (n rows by m columns) matrix, n = length(unique(lon)) and m = length(unique(lat)).

lon

a vector of longitudes with length N. For gridded data, the length may have the value (n) provided that n * m = N where n = length(unique(lon)) and m = length(unique(lat)).

lat

a vector of latitudes with length N or m. See lon.

lonStep

an integer greater than or equal to 1 for longitdue step to coarsen gridded data in the longitudinal direction. If lonStep = 1, gridded data will not be coarsened in the longitudinal direction (the default). If lonStep = 2, every other grid in longitudinal direction will be retained.

latStep

an integer greater than or equal to 1 for latitude step to coarsen gridded data in the latitudinal direction. If latStep = 1, gridded data will not be coarsened in the latitudinal direction (the default). If latStep = 2, every other grid in latitudinal direction will be retained. lonStep and latStep are independent so that user can optionally apply different coarsening level to each dimension.

verbose

logical to print processing information if verbose = TRUE.

Details

For high-resolution data, the computational and memory requirements may not be met on old machines. This function enables the user to use coarser data in any spatial dimension:longitude, latitude, or both. It is available for testing or running HiClimR package on old computers or machines with small memory resources. The rows of output matrix (x component) will be also named by longitude and latitude coordinates. If lonStep = 1 and latStep = 1, coarseR function will just rename rows of matrix x.

Value

A list with the following components:

lon

longitude mesh vector for the coarsened data.

lat

latitude mesh vector for the coarsened data.

rownum

original row numbers for the coarsened data.

x

coarsened data of the input data matrix x.

Author(s)

Hamada Badr <badr@jhu.edu>, Ben Zaitchik <zaitchik@jhu.edu>, and Amin Dezfuli <dez@jhu.edu>.

References

Hamada S. Badr, Zaitchik, B. F. and Dezfuli, A. K. (2015): A Tool for Hierarchical Climate Regionalization, Earth Science Informatics, 1-10, http://dx.doi.org/10.1007/s12145-015-0221-7.

Hamada S. Badr, Zaitchik, B. F. and Dezfuli, A. K. (2014): Hierarchical Climate Regionalization, CRAN, http://cran.r-project.org/package=HiClimR.

See Also

HiClimR, validClimR, geogMask, coarseR, fastCor, grid2D, and minSigCor.

Examples

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require(HiClimR)

## Load test case data
x <- TestCase$x

## Generate longitude and latitude mesh vectors
xGrid <- grid2D(lon = unique(TestCase$lon), lat = unique(TestCase$lat))
lon <- c(xGrid$lon)
lat <- c(xGrid$lat)

## Coarsening spatial resolution
xc <- coarseR(x = x, lon = lon, lat = lat, lonStep = 2, latStep = 2)
lon <- xc$lon
lat <- xc$lat
x <- xc$x