knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.height = 4.375, fig.width = 7, dev = "jpeg" ) old_par <- par(no.readonly = TRUE)
This vignette covers ways of interacting with a Quadtree
object after it has been created - for example, extracting values and modifying values.
library(terra) library(quadtree) habitat <- terra::rast(system.file("extdata", "habitat.tif", package="quadtree")) rast <- habitat qt <- quadtree(rast, .15)
There are a number of functions for retrieving basic info about a Quadtree
.
A basic summary of a quadtree can be shown by just typing the variable name or using the summary()
function:
qt
projection()
can be used to get and set the projection of the Quadtree
. In this case there is no projection, so an empty string is returned.
projection(qt)
n_cells()
returns the number of cells in the quadtree. It has one optional parameter, terminal_only
- if TRUE
, the number of cells of the quadtree that are terminal (i.e. have no children) is returned. If FALSE
, the total number of nodes in the quadtree is returned.
n_cells(qt) n_cells(qt, terminal_only = FALSE)
extent()
can be used to return the extent of the quadtree. It has one optional parameter original
- if FALSE
(the default), it returns the total extent covered by the quadtree. If TRUE
, the function returns the extent of the original raster used to create the quadtree, before NA
rows/columns were added to pad the dimensions. You may need to preface extent()
with quadtree::
to avoid conflicts with the raster
package.
quadtree::extent(qt) quadtree::extent(qt, original = TRUE)
Values can be 'extracted' at point locations using the extract()
function. This function has one optional parameter - extents
. If extents
is FALSE
(the default), then only the values at the point locations are returned. If extents
is TRUE
, then a matrix is returned that also returns the x and y limits of each cell in addition to the cell value.
pts <- cbind(x = c(5609, 3959, 20161, 27662, 32763), y = c(10835, 29586, 31836, 10834, 36337)) plot(qt, crop = TRUE, border_lwd = .3, na_col = NULL) points(pts, pch = 16)
quadtree::extract(qt, pts) quadtree::extract(qt, pts, extents = TRUE)
In addition to extracting values from cells, it is possible to determine neighbor relationships between cells via the get_neighbors()
function. Given a point, get_neighbors()
returns the cells that neighbor the cell that the point falls in. Note that cells that are diagonal from each either (i.e. only touch at the corner) are considered to be neighbors.
get_neighbors(qt, as.numeric(pts[3,]))
A key concept to understand is that Quadtree
objects are pointers to C++ objects, and copying these objects simply by assigning them to a new variable makes a shallow copy rather than a deep copy. This is important to note because this differs from how R objects normally behave. For example, if I have a data frame named df1
, I can make a copy of it by doing df2 <- df1
. This makes a deep copy of df1
- if I were to modify df2
, df1
would remain unchanged. This is not the case with Quadtree
objects. The R object that users interact with is a pointer to a C++ object. If I were to attempt to make copy of a quadtree qt1
by doing qt2 <- qt1
, this simply copies the pointer to the C++ object, so qt1
and qt2
point to the same object. Thus, if qt2
is modified (for example, by using a function like set_values()
or transform_values()
), qt1
will also be modified.
The copy()
function can be used to make a deep copy of a Quadtree
object. This is useful if the user wishes to make changes to a quadtree without modifying the original.
qt_copy <- copy(qt) qt qt_copy
In the next section ("Modifying cell values"), this function is used in the examples to create copies of a quadtree before modifying it so that the original remains unchanged.
Two functions are provided for modifying cell values: set_values()
and transform_values()
.
set_values()
takes a matrix of points and associated values and changes the values of the cells the points fall in. Note that only the values of the terminal cells that the point falls in are changed.
qt2 <- copy(qt) set_values(qt2, pts, rep(2, nrow(pts))) plot(qt2, crop = TRUE, border_lwd = .3)
transform_values()
uses a function to change all cell values. For example, we could use this function to cube all of the cell values:
qt3 <- copy(qt) transform_values(qt3, function(x) x^3) par(mfrow = c(1,2)) plot(qt, crop = TRUE, na_col = NULL, border_lwd = .3, zlim = c(0, 1), legend = FALSE, main = "original quadtree") plot(qt3, crop = TRUE, na_col = NULL, border_lwd = .3, zlim = c(0, 1), legend = FALSE, main = "values cubed")
One of the disadvantages of using C++ classes via Rcpp is that the objects are not preserved between sessions. For example, we could save a Quadtree
to a RData
file using save()
, but when we loaded it back in we would get an error.
qt_temp <- copy(qt) filepath <- tempfile() save(qt_temp, file = filepath) load(filepath) qt_temp
The quadtree
package provides read and write functionality via the cereal
C++ library, which is used to serialize C++ objects. read_quadtree()
and write_quadtree()
can be used to read and write Quadtree
objects.
filepath <- tempfile() write_quadtree(filepath, qt) qt_read <- read_quadtree(filepath) qt_read
Functions are also provided for converting a Quadtree
to different data types.
as_vector()
returns the cell values as a numeric vector. It has one optional parameter - terminal_only
. If TRUE
(the default), only the values of the terminal cells are returned. If FALSE
, the values of all cells (including those with children) are returned.
vec1 <- as_vector(qt) length(vec1) summary(vec1) vec2 <- as_vector(qt, FALSE) length(vec2) summary(vec2)
as_data_frame()
converts the quadtree to a data frame. In the resulting data frame, each row represents a single cell and has columns describing the cell ID, x and y limits, value, level (i.e. node depth), the size of its smallest child, the ID of its parent, and whether it has children. As with as_vector()
, there is one optional parameter called terminal_only
- when TRUE
(the default) only the terminal cells are returned, and when FALSE
, all cells are returned.
df1 <- as_data_frame(qt) dim(df1) head(df1) df2 <- as_data_frame(qt, FALSE) dim(df2) head(df2)
A Quadtree
can also be converted to a raster using the as_raster()
function. This function has one optional parameter named rast
, which is used as the template for the output raster. If NULL
(the default), a raster is automatically created, where the quadtree extent is used as the raster extent and the smallest cell in the quadtree is used to determine the resolution of the raster. Note that the value of a raster cell is determined by the value of the quadtree cell located at the centroid of the raster cell - thus, if a raster cell overlaps several quadtree cells, whichever quadtree cell the centroid of the raster cell falls in will determine the raster cell's value. If the default value for rast
is used, the raster cells will never overlap with more than one quadtree cell.
rast <- as_raster(qt) plot(rast)
par(old_par)
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