SpatialImage-class | R Documentation |
SpatialImage
classThe SpatialImage
class hierarchy provides representations of images
from a variety of sources. It is used by the SpatialExperiment
class to manage the loading of images across multiple studies.
SpatialImage(x, is.url)
will return a SpatialImage
object.
The class of the object depends on the type of x
:
If x
is a raster object, a LoadedSpatialImage
is
returned. This represents an image that is fully realized into memory,
where the raster representation is stored inside the output object.
If x
is a string and is.url=TRUE
or it starts with
"http://"
, "http://"
or "ftp://"
,
a RemoteSpatialImage
is returned. This represents an image
that is remotely hosted and retrieved only on request.
If x
is a string and is.url=TRUE
or it does not
start with a URL-like prefix, a StoredSpatialImage
is returned.
This represents an image that is stored in a local file
and is loaded into memory only on request.
For a SpatialImage
object x
, imgRaster(x, ...)
will return a raster object (see ?as.raster
).
This is effectively a matrix of RGB colors for each pixel in the image.
For a StoredSpatialImage
object x
, additional arguments
in ...
are passed to image_read
.
This controls how the image is read into memory.
For a RemoteSpatialImage
object x
, the image file is first
downloaded before the raster is returned. Here, ...
may contain an
extra cache
argument, which should be a BiocFileCache
object
(from the BiocFileCache package) specifying the file cache location.
The default location is determined by
options("SpatialExperiment.remote.cache.path")
,
otherwise it defaults to a subdirectory in the R temporary directory.
Any further named arguments in ...
are passed to image_read
.
as.raster(x, ...)
is the same as imgRaster(x, ...)
.
For StoredSpatialImage
and RemoteSpatialImage
objects,
loading the image with imgRaster
will automatically
store the loaded raster object in an in-memory cache.
Any subsequent imgRaster
call will retrieve the raster
from the cache, avoiding costly retrieval from the file system.
The cache policy is to evict the least recently used images when a new image would be added that exceeds the maximum cache size. If the new image by itself exceeds the maximum cache size, all images are evicted from the cache to trigger garbage collection and free up memory.
By default, the maximum size of the cache is 4 GB. This can be
modified by setting options("SpatialExperiment.cache.size")
to some number of bytes, e.g., 2^32
.
Two basic image transformations are currently
supported for any SpatialImage
x
, namely,
rotateImg(x, degrees)
for clockwise (degrees > 0
) and
counter-clockwise (degrees < 0
) rotation, and
mirrorImg(x, axis)
for horizontal (axis = "h"
) and
vertical (axis = "v"
) mirroring.
Note that, both rotateImg()
and mirrorImg()
operate
on the raster
matrix of the input SpatialImage
.
Thus, any SpatialImage
will automatically be coerced
into a LoadedSpatialImage
upon rotation/mirroring.
dim(x)
will return an integer vector of length 2,
containing the width and height of the image in pixels.
Note that this calls imgRaster
under the hood and thus
may interact with the file and memory caches as described above.
For any SpatialImage x
, as(x, "LoadedSpatialImage")
will
create a LoadedSpatialImage
containing an in-memory raster object.
For a RemoteSpatialImage x
, as(x, "StoredSpatialImage")
will
create a StoredSpatialImage
pointing to the file cache location.
Aaron Lun
path <- system.file(
"extdata", "10xVisium", "section1", "outs", "spatial",
"tissue_lowres_image.png", package="SpatialExperiment")
spi <- SpatialImage(path)
plot(imgRaster(spi))
# the following operations all use the cache
# so there is no need to reload the image
nrow(spi)
ncol(spi)
plot(as.raster(spi))
# coercing to an explicitly in-memory raster
spi <- as(spi, "LoadedSpatialImage")
plot(as.raster(spi))
###################
# transformations #
###################
# (counter-)clockwise rotation
spi1 <- rotateImg(spi, degrees = +90)
spi2 <- rotateImg(spi, degrees = -90)
par(mfrow = c(1, 3))
plot(as.raster(spi))
plot(as.raster(spi1))
plot(as.raster(spi2))
# horizontal/vertical mirroring
spi1 <- mirrorImg(spi, axis = "h")
spi2 <- mirrorImg(spi, axis = "v")
par(mfrow = c(1, 3))
plot(as.raster(spi))
plot(as.raster(spi1))
plot(as.raster(spi2))
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