R/dotprops.R
dotprops: Neurons as point clouds with tangent vectors (but no connectivity)
dotprops
makes dotprops representation from raw 3D points
(extracting vertices from S3 objects that have them)
dotprops.dotprops
will default to the original vale of
k
and copy over all attributes that are not set by
dotprops.default
.
dotprops.neuronlist
will run for every object in the
neuronlist using nlapply
. ...
arguments will be passed to
nlapply
in addition to the named argument OmitFailures
.
is.dotprops(x) as.dotprops(x, ...) dotprops(x, ...) # S3 method for character dotprops(x, ...) # S3 method for dotprops dotprops(x, k = attr(x, "k"), ...) # S3 method for im3d dotprops(x, ...) # S3 method for neuronlist dotprops(x, ..., OmitFailures = NA) # S3 method for neuron dotprops(x, Labels = NULL, resample = NA, ...) # S3 method for default dotprops(x, k = NULL, Labels = NULL, na.rm = FALSE, ...)
x | Object to be tested/converted |
---|---|
... | Additional arguments passed to methods |
k | Number of nearest neighbours to use for tangent vector calculation (set to k=20 when passed NULL) |
OmitFailures | Whether to omit neurons for which |
Labels | Vector of labels for each point e.g. identifying axon vs
dendrite. The default value |
resample | When finite, a new length to which all segmented edges will
be resampled. See |
na.rm | Whether to remove |
k
will default to 20 nearest neighbours when unset (i.e. when
it has default value of NA) unless x
is a dotprops object (when the
original value of k
is reused).
The dotprops format is essentially identical to that developed in:
Masse N.Y., Cachero S., Ostrovsky A., and Jefferis G.S.X.E. (2012). A mutual information approach to automate identification of neuronal clusters in Drosophila brain images. Frontiers in Neuroinformatics 6 (00021). doi: 10.3389/fninf.2012.00021