Parallel coordinates plot for multivariate data.
nan_parallelcoords(AX,...) plots into the axes with handle AX. nan_parallelcoords(X) nan_parallelcoords(X,group) nan_parallelcoords(X,group,quant) nan_parallelcoords(X,group,quant,labels) nan_parallelcoords(X,group,quant,labels,stdize)
handle
Rows of X correspond to observations, columns to variables
plots the data in different groups with different colors. group is a string matrix.
if not empty the the median and the quant and (1-quant) quantiles of f(t) at each value of t is plotted
labels the coordinate tick marks
do nothing
normalize each column of X (mean = 0, deviation = 1)
instead of X the principal component scores of X is used, in order of decreasing eigenvalue.
uses the standardized principal component scores.
Parallel coordinates is a common way of visualizing high-dimensional geometry and analyzing multivariate data.
To show a set of points in an n-dimensional space, a backdrop is drawn consisting of n parallel lines, typically vertical and equally spaced. A point in n-dimensional space is represented as a polyline with vertices on the parallel axes; the position of the vertex on the ith axis corresponds to the ith coordinate of the point.
nan_parallelcoords treats NaNs in X as missing values,
// make a grouped plot of the raw data loadmatfile("demos/data/iris.mat"); labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; nan_parallelcoords(meas, species, [],labels); // plot only the median and quartiles of each group nan_parallelcoords(meas, species, 0.25,labs);
Andrews, D. F. (1972), Plots of high-dimensional data, Biometrics 28, S.125-136