bindata {cooltools}

Bin two-dimensional data in one dimension

Description

Divides a vector of values x into finite intervals; returns the counts and other statistics in each interval.

Usage

bindata(x, y = NULL, bins = 20, method = "regular", xlim = NULL)

Arguments

x

N-element vector of x-coordinates

y

optional N-element vector of values associated with the different points in x

bins

If method is 'regular' or 'equal', this is a scalar specifying the number of bins. If method is 'custom' this is a vector of (n+1) x-values delimiting the n bins.

method

Character string. Choose 'regular' for regularly space bins, 'equal' for bins containing an equal number of points (+-1), or 'custom' for bins with custom edges.

xlim

optional 2-element vector specifying the data range (data cropped if necessary). If not given, xlim is set to the full range of x.

Value

Returns a list of items

n

number of bins

xlim

considered range of x-coordinates, same as input argument xlim, if given

xleft

n-element vector containing the x-coordinates of the left bin edges

xmid

n-element vector containing the x-coordinates of the bin centres

xright

n-element vector containing the x-coordinates of the right bin edges

dx

n-element vector containing the widths of the bins

count

n-element vector containing the number of points in each bin

x

n-element vector containg the mean x-values in each bin

y

n-element vector containg the mean y-values in each bin

xmedian

n-element vector containg the median of the x-values in each bin

ymedian

n-element vector containg the median of the y-values in each bin

yerr

n-element vector giving the uncertainty on the mean

ysd

n-element vector giving the standard deviations of the y-values

y16

n-element vector giving the 15.86-percentile of the y-values

y84

n-element vector giving the 84.13-percentile of the y-values

Author(s)

Danail Obreschkow

See Also

griddata

Examples

# make and plot 100 random (x,y)-points
set.seed(1)
x = runif(200)
y = x+rnorm(200)
plot(x,y,pch=16,cex=0.5)

# bin the data into 10 bins of 20 points each
bin = bindata(x,y,10,'equal')
segments(bin$xleft,bin$y,bin$xright,bin$y,col='red')
segments(bin$x,bin$y16,bin$x,bin$y84,col='red')
segments(bin$x,bin$y-bin$yerr,bin$x,bin$y+bin$yerr,col='red',lwd=3)
points(bin$x,bin$y,pch=16,col='red')