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Display two neurons with segments in the query coloured by similarity

Source: R/similarity.r
show_similarity.Rd

By default, the query neuron will be drawn with its segments shaded from red to blue, with red indicating a poor match to the target segments, and blue a good match.

Usage

show_similarity(
  query,
  target,
  smat = NULL,
  cols = colorRampPalette(c("red", "yellow", "cyan", "navy")),
  col = "black",
  AbsoluteScale = FALSE,
  PlotVectors = TRUE,
  ...
)

Arguments

query

a neuron to compare and colour.

target

the neuron to compare against.

smat

a score matrix (if NULL, defaults to smat.fcwb).

cols

the function to use to colour the segments (e.g. heat.colors).

col

the colour with which to draw the target neuron.

AbsoluteScale

logical indicating whether the colours should be calculated based on the minimum and maximum similarities for the neuron (AbsoluteScale = FALSE) or on the minimum and maximum possible for all neurons.

PlotVectors

logical indicating whether the vectors of the dotprops representation should be plotted. If FALSE, only the points are plotted.

...

extra arguments to pass to plot3d.

Value

show_similarity is called for the side effect of drawing the plot; a vector of object IDs is returned.

See also

The low level function WeightedNNBasedLinesetMatching is used to retrieve the scores.

Examples

if (FALSE) { # \dontrun{
library(nat)

# Pull out gamma and alpha-beta neurons
gamma_neurons <- subset(kcs20, type=='gamma')
ab_neurons <- subset(kcs20, type=='ab')

# Compare two alpha-beta neurons with similar branching, but dissimilar arborisation
clear3d()
show_similarity(ab_neurons[[1]], ab_neurons[[2]])

# Compare an alpha-beta and a gamma neuron with some similarities and differences
clear3d()
show_similarity(ab_neurons[[1]], gamma_neurons[[3]])
} # }