pixelApply-methods {Cardinal} | R Documentation |
Apply an existing or a user-specified function over either all of the features or all of the pixels of an SImageSet
or SparseImagingExperiment
. These are provided for convenience by analogy to the 'apply' family of functions, but allowing greater control over how the functions are applied over an imaging dataset.
## S4 method for signature 'SparseImagingExperiment' pixelApply(.object, .fun, ..., .blocks = FALSE, .simplify = TRUE, .use.names = TRUE, .outpath = NULL, BPREDO = list(), BPPARAM = bpparam()) ## S4 method for signature 'SparseImagingExperiment' featureApply(.object, .fun, ..., .blocks = FALSE, .simplify = TRUE, .use.names = TRUE, .outpath = NULL, BPREDO = list(), BPPARAM = bpparam()) ## S4 method for signature 'SImageSet' pixelApply(.object, .fun, ..., .pixel, .feature, .feature.groups, .pixel.dependencies, .simplify = TRUE, .use.names = TRUE, .verbose = FALSE) ## S4 method for signature 'SImageSet' featureApply(.object, .fun, ..., .feature, .pixel, .pixel.groups, .feature.dependencies, .simplify = TRUE, .use.names = TRUE, .verbose = FALSE)
.object |
An imaging dataset. |
.fun |
The function to be applied. |
... |
Additional arguments passed to |
.blocks |
If FALSE (the default), each feature-vector or image-vector will be loaded and processed individually. If TRUE, or a number, the data will be split into that many blocks, and the function (specified by |
.simplify |
Should the result be simplified into a matrix or array rather than a list, if appropriate? |
.use.names |
Should the names of elements of |
.outpath |
The path to a file where the output data will be written. Results will be kept in-memory if this is NULL. Results will be coerced to a numeric vector before being written to file. |
BPREDO |
See documentation for |
BPPARAM |
An optional instance of |
.pixel |
A subset of pixels to use, given by an |
.feature |
A subset of features to use, given in the same manner as pixels. |
.pixel.groups |
A grouping |
.feature.groups |
A grouping |
.pixel.dependencies |
Not currently used. This may be used in the future to allow caching when applying functions to data on disk. |
.feature.dependencies |
Not currently used. May be used for caching in the future. |
.verbose |
Used for debugging. Currently ignored. |
The use of .pixel
and .feature
can be used to apply the function over only a subset of pixels or features (or both), allowing faster computation when calculation on only a subset of data is needed.
For pixelApply
, the function is applied to the feature vector belonging to each pixel. The use of .feature.groups
allows codetapply-like functionality on the feature vectors, applied separately to each pixel.
For featureApply
, the function is applied to the vector of intensity values (i.e., the flattened image) corresponding to each feature. The use of .feature.groups
allows codetapply-like functionality on the flattened image intensity vectors, applied separately to each feature.
The fData
from .object
is installed into the environment of .fun
for pixelApply
, and the pData
from .object
is installed into the environment of .fun
for featureApply
. This allows access to the symbols from fData
or pData
during the execution of .fun
. If .fun
already has an environment, it is retained as the parent of the installed environment.
Additionally, the following objects are made available by installing them into the .fun
environment:
.Object
: The passed .object
. (Note the case.)
.Index
: The index of the current iteration.
It is expected that these methods will be expanded in the future for different types of imaging datasets (e.g., data read directly from disk).
If .simplify = FALSE
, a list. Otherwise, a matrix, or a higher-dimensional array if grouping is specified.
Kylie A. Bemis
data <- matrix(1:256, nrow=4) coord <- expand.grid(x=1:4, y=1:4, z=1:4) sset <- SImageSet(data=data, coord=coord) fData(sset)$flag <- rep(c(TRUE, FALSE), 2) pixelApply(sset, max, .feature.groups=flag) pData(sset)$flag <- rep(c(TRUE, FALSE), 32) featureApply(sset, max, .pixel.groups=flag)