Create a 2-d gaussian distribution

In this example we are going to create a bidimensional gaussian distribution with parameters .

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)

create the distribution, no correlation

distribution = ot.Normal([0.0, 2.0], [1.0, 0.6], ot.CorrelationMatrix(2))
print(distribution)

Out:

Normal(mu = [0,2], sigma = [1,0.6], R = [[ 1 0 ]
 [ 0 1 ]])

draw a sample

sample = distribution.getSample(10)
print(sample)

Out:

    [ X0        X1        ]
0 : [ -0.533767  2.50205  ]
1 : [  0.637214  2.74318  ]
2 : [ -0.330867  1.94233  ]
3 : [  1.90132   2.92378  ]
4 : [  0.210666  2.00093  ]
5 : [ -2.17162   2.16491  ]
6 : [  0.670238  1.76749  ]
7 : [  0.429259  3.81131  ]
8 : [ -1.69802   2.44749  ]
9 : [ -0.238387  2.08961  ]

draw PDF

graph = distribution.drawPDF()
view = viewer.View(graph)
plt.show()