Computes nearest-available-value imputation for missing values in space
bru_fill_missing(
data,
where,
values,
layer = NULL,
selector = NULL,
batch_size = 50
)
An infilled vector of values
A SpatialPointsDataFrame, SpatialPixelsDataFrame, SpatialGridDataFrame, SpatRaster, Raster, or sf object containing data to use for filling
A, matrix, data.frame, or SpatialPoints or SpatialPointsDataFrame, or sf object, containing the locations of the evaluated values
A vector of values to be filled in where is.na(values)
is
TRUE
Specifies what data column or columns from which to
extract data, see component()
for details.
Size of nearest-neighbour calculation blocks, to limit the memory and computational complexity.
if (FALSE) {
if (bru_safe_inla()) {
points <-
sp::SpatialPointsDataFrame(
matrix(1:6, 3, 2),
data = data.frame(val = c(NA, NA, NA))
)
input_coord <- expand.grid(x = 0:7, y = 0:7)
input <-
sp::SpatialPixelsDataFrame(
input_coord,
data = data.frame(val = as.vector(input_coord$y))
)
points$val <- bru_fill_missing(input, points, points$val)
print(points)
# To fill in missing values in a grid:
print(input$val[c(3, 30)])
input$val[c(3, 30)] <- NA # Introduce missing values
input$val <- bru_fill_missing(input, input, input$val)
print(input$val[c(3, 30)])
}
}
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