gdalcubes/man/apply_pixel.cube.Rd

94 lines
4 KiB
R

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/apply_pixel.R
\name{apply_pixel.cube}
\alias{apply_pixel.cube}
\title{Apply arithmetic expressions over all pixels of a data cube}
\usage{
\method{apply_pixel}{cube}(
x,
expr,
names = NULL,
keep_bands = FALSE,
...,
FUN,
load_pkgs = FALSE,
load_env = FALSE
)
}
\arguments{
\item{x}{source data cube}
\item{expr}{character vector with one or more arithmetic expressions (see Details)}
\item{names}{optional character vector with the same length as expr to specify band names for the output cube}
\item{keep_bands}{logical; keep bands of input data cube, defaults to FALSE, i.e. original bands will be dropped}
\item{...}{not used}
\item{FUN}{user-defined R function that is applied on all pixels (see Details)}
\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.}
\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.}
}
\value{
a proxy data cube object
}
\description{
Create a proxy data cube, which applies arithmetic expressions over all pixels of a data cube. Expressions may access band values by name.
}
\details{
The function can either apply simple arithmetic C expressions given as a character vector (expr argument), or apply a custom R reducer function if FUN is provided.
In the former case, gdalcubes uses the \href{https://github.com/codeplea/tinyexpr}{tinyexpr library} to evaluate expressions in C / C++, you can look at the \href{https://github.com/codeplea/tinyexpr#functions-supported}{library documentation}
to see what kind of expressions you can execute. Pixel band values can be accessed by name. Predefined variables that can be used within the expression include integer pixel indexes (\code{ix}, \code{iy}, \code{it}), and
pixel coordinates (\code{left}, \code{right}, \code{top}, \code{bottom}), \code{t0}, \code{t1}), where the last two values are provided seconds since epoch time.
FUN receives values of the bands from one pixel as a (named) vector and should return a numeric vector with identical length for all pixels. Elements of the
result vectors will be interpreted as bands in the result data cube. Notice that by default, since FUN is executed in a separate
R process, it cannot access any variables from outside and required packages must be loaded within FUN. To restore the current environment and
automatically load packages, set \code{load_env} and/or \code{load_pkgs} to \code{TRUE}.
For more details and examples on how to write user-defined functions, please refer to the gdalcubes website
at \url{https://gdalcubes.github.io/source/concepts/udfs.html}.
}
\note{
This function returns a proxy object, i.e., it will not start any computations besides deriving the shape of the result.
}
\examples{
# create image collection from example Landsat data only
# if not already done in other examples
if (!file.exists(file.path(tempdir(), "L8.db"))) {
L8_files <- list.files(system.file("L8NY18", package = "gdalcubes"),
".TIF", recursive = TRUE, full.names = TRUE)
create_image_collection(L8_files, "L8_L1TP", file.path(tempdir(), "L8.db"), quiet = TRUE)
}
# 1. Apply a C expression
L8.col = image_collection(file.path(tempdir(), "L8.db"))
v = cube_view(extent=list(left=388941.2, right=766552.4,
bottom=4345299, top=4744931, t0="2018-04", t1="2018-06"),
srs="EPSG:32618", nx = 497, ny=526, dt="P1M")
L8.cube = raster_cube(L8.col, v)
L8.cube = select_bands(L8.cube, c("B04", "B05"))
L8.ndvi = apply_pixel(L8.cube, "(B05-B04)/(B05+B04)", "NDVI")
L8.ndvi
\donttest{
plot(L8.ndvi)
}
# 2. Apply a user defined R function
L8.ndvi.noisy = apply_pixel(L8.cube, names="NDVI_noisy",
FUN=function(x) {
rnorm(1, 0, 0.1) + (x["B05"]-x["B04"])/(x["B05"]+x["B04"])
})
L8.ndvi.noisy
\donttest{
plot(L8.ndvi.noisy)
}
}