samplingcurve: Make a basic sampling curve from a vector of partner ids

In jefferis/emsampling: Experimental functions to analyse EM connectomics data

Description

plot.samplingcurve plots a standard sampling curve

lines.samplingcurve adds a line for a sampling curve to an existing plot. It can also add a specified number of re-randomised versions of the curve, optionally producing a smoothed mean.

hist.samplingcurve plots a histogram of connections per partner neuron. strictly speaking this is a bar plot for a table object rather than an R histogram

Usage

samplingcurve(partners, N = NULL, m = NULL)

## S3 method for class 'samplingcurve'
plot(x, col = "red", ...)

## S3 method for class 'samplingcurve'
lines(x, rand = 0, mean = FALSE, lty = 3,
  col = NULL, ..., colpal = "grey")

## S3 method for class 'samplingcurve'
hist(x, decreasing = TRUE, plot = TRUE, ...)

Arguments

partners	A vector or partner neuron identifiers (typically numeric such as CATMAID skeleton ids)
N, m	optional parameters describing the total number of connections and the total number of partners (if known).
x	A samplingcurve object
col	line colour (see lines)
...	Additional arguments to plotting functions
rand	number of randomised versions of curve to plot
mean	whether to plot the mean of specified number of random curves rather than each individual curve.
lty	line type (see par)
colpal	A colour palette. Either a function (see rainbow) or a vector of colour names. Only used when col=NULL)
decreasing	Whether to plot the strongest connections closest to the y axis (default TRUE)
plot	Whether to show the histogram

Value

An object of class samplingcurve, currently implemented as a data.frame.

hist.samplingcurve returns the table of connections per partner used for the plot.

Examples

scuniform=samplingcurve(sample(1:20, size=200, replace=TRUE))
plot(scuniform)
# add 20 random realisations
lines(scuniform, rand=20)
# add a smooth mean
lines(scuniform, rand=1000, mean=TRUE, col='black')

# use real sample data for inputs to a lateral horn neuron
plot(pd2a1.1.sc)
lines(pd2a1.1.sc, rand=20)
scuniform=samplingcurve(sample(1:20, size=200, replace=TRUE))
hist(scuniform, main='20 neurons with equal connection probability')

hist(pd2a1.1.sc, main='Inputs to a lateral horn neuron')

jefferis/emsampling documentation built on July 21, 2019, 2:20 a.m.