Draw the empirical CDF¶
In this example we are going to draw the empirical CDF of an unidimensional sample.
from __future__ import print_function import openturns as ot import openturns.viewer as viewer from matplotlib import pylab as plt ot.Log.Show(ot.Log.NONE)
Then create a sample from a gaussian distribution.
size = 100 normal = ot.Normal(1) sample = normal.getSample(size)
We draw the empirical CDF based on the UserDefined distribution. By default, the drawCDF method requires no input argument.
distribution = ot.UserDefined(sample) graph = distribution.drawCDF() view = viewer.View(graph)
If required, we can specify the interval that we want to draw. In the following example, these bounds are computed from the minimum and the maximum of the sample.
xmin = sample.getMin() - 2.0 xmax = sample.getMax() + 2.0 graph = ot.UserDefined(sample).drawCDF(xmin, xmax) view = viewer.View(graph) plt.show()
Total running time of the script: ( 0 minutes 0.137 seconds)