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91 lines
4 KiB
R
91 lines
4 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/reduce.R
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\name{reduce_time.cube}
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\alias{reduce_time.cube}
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\title{Reduce a data cube over the time dimension}
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\usage{
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\method{reduce_time}{cube}(
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x,
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expr,
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...,
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FUN,
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names = NULL,
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load_pkgs = FALSE,
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load_env = FALSE
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)
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}
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\arguments{
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\item{x}{source data cube}
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\item{expr}{either a single string, or a vector of strings defining which reducers will be applied over which bands of the input cube}
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\item{...}{optional additional expressions (if \code{expr} is not a vector)}
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\item{FUN}{a user-defined R function applied over pixel time series (see Details)}
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\item{names}{character vector; names of the output bands, if FUN is provided, the length of names is used as the expected number of output bands}
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\item{load_pkgs}{logical or character; if TRUE, all currently attached packages will be attached automatically before executing FUN in spawned R processes, specific packages can alternatively be provided as a character vector.}
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\item{load_env}{logical or environment; if TRUE, the current global environment will be restored automatically before executing FUN in spawned R processes, can be set to a custom environment.}
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}
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\value{
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proxy data cube object
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}
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\description{
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Create a proxy data cube, which applies one or more reducer functions to selected bands over pixel time series of a data cube
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}
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\details{
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The function can either apply a built-in reducer if expr is given, or apply a custom R reducer function if FUN is provided.
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In the former case, notice that expressions have a very simple format: the reducer is followed by the name of a band in parantheses. You cannot add
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more complex functions or arguments. Possible reducers currently are "min", "max", "sum", "prod", "count", "mean", "median", "var", "sd", "which_min", "which_max",
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"Q1" (1st quartile), and "Q3" (3rd quartile).
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User-defined R reducer functions receive a two-dimensional array as input where rows correspond to the band and columns represent the time dimension. For
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example, one row is the time series of a specific band. FUN should always return a numeric vector with the same number of elements, which will be interpreted
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as bands in the result cube. Notice that it is recommended to specify the names of the output bands as a character vector. If names are missing,
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the number and names of output bands is tried to be derived automatically, which may fail in some cases.
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For more details and examples on how to write user-defined functions, please refer to the gdalcubes website
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at \url{https://gdalcubes.github.io/source/concepts/udfs.html}.
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}
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\note{
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Implemented reducers will ignore any NAN values (as na.rm=TRUE does)
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This function returns a proxy object, i.e., it will not start any computations besides deriving the shape of the result.
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}
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\examples{
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# create image collection from example Landsat data only
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# if not already done in other examples
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if (!file.exists(file.path(tempdir(), "L8.db"))) {
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L8_files <- list.files(system.file("L8NY18", package = "gdalcubes"),
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".TIF", recursive = TRUE, full.names = TRUE)
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create_image_collection(L8_files, "L8_L1TP", file.path(tempdir(), "L8.db"), quiet = TRUE)
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}
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L8.col = image_collection(file.path(tempdir(), "L8.db"))
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v = cube_view(extent=list(left=388941.2, right=766552.4,
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bottom=4345299, top=4744931, t0="2018-01", t1="2018-06"),
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srs="EPSG:32618", nx = 497, ny=526, dt="P1M")
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L8.cube = raster_cube(L8.col, v)
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L8.rgb = select_bands(L8.cube, c("B02", "B03", "B04"))
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L8.rgb.median = reduce_time(L8.rgb, "median(B02)", "median(B03)", "median(B04)")
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L8.rgb.median
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\donttest{
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plot(L8.rgb.median, rgb=3:1)
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}
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# user defined reducer calculating interquartile ranges
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L8.rgb.iqr = reduce_time(L8.rgb, names=c("iqr_R", "iqr_G","iqr_B"), FUN = function(x) {
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c(diff(quantile(x["B04",],c(0.25,0.75), na.rm=TRUE)),
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diff(quantile(x["B03",],c(0.25,0.75), na.rm=TRUE)),
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diff(quantile(x["B02",],c(0.25,0.75), na.rm=TRUE)))
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})
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L8.rgb.iqr
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\donttest{
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plot(L8.rgb.iqr, key.pos=1)
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}
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}
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