[FIXED] Contour plots for multivariate gaussian

Issue

I'm trying to use a contour plot to visualize a multivariate normal distribution.

import numpy as np
from scipy.stats import multivariate_normal

mean = (0, 0)
cov = [[1, 0.75], 
       [0.75, 1]]
data = np.random.multivariate_normal(mean, cov,size=1000)
var = multivariate_normal(mean=mean, cov=cov)
z = var.pdf(data)
plt.contour(data,z)

>>>
ValueError: Contour levels must be increasing

My goal is simply a contour plot of the multivariate distribution, much like a 2D histogram. However, I seem to be misunderstanding the function's intent.

Is there a better way to accomplish this effect?

Solution

You can use seaborn kde plot:

import seaborn as sns
sns.kdeplot(data, bw=.15)
plt.show()

as described here https://seaborn.pydata.org/generated/seaborn.kdeplot.html for easy plotting.

I know it is not the exact answer to your problem but it might be sufficient answer for you if you are willing to install the seaborn library.

Answered By - Vladimír Kunc