Turn hist2d output into contours in matplotlib

So the problem is that the image created by hist2d is plotted in data coordinates, but the contours you are trying to create are in pixel coordinates. The simple way around this is to specify the extent of the contours (i.e. rescale/reposition them in the x and y axes).

For example:

from matplotlib.colors import LogNorm
from matplotlib.pyplot import *

x = np.random.normal(5,10,100000)
y = np.random.normal(5,10,100000)
counts,ybins,xbins,image = hist2d(x,y,bins=100,norm=LogNorm())
contour(counts,extent=[xbins.min(),xbins.max(),ybins.min(),ybins.max()],linewidths=3)

Will produce:

Would prefer to post this as a comment, but don't have the reputation, so ...

@ebarr has a nice solution with one small correction: the xbins and ybins coming from the 2d plot should be reversed (see matplotlib documentation, https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.hist2d
)

Also, only mildly annoying, but the contour lines colors won't line up with the colors in the 2d histogram since the histogram colorscale has been log transformed. To fix this you can manually specify levels for the contour plot.

Making these changes, and separating the plots for clarity yields:

from matplotlib.colors import LogNorm
import matplotlib.pyplot as plt

x = np.random.normal(5,10,100000)
y = np.random.normal(5,10,100000)
plt.subplot(121)
counts,xbins,ybins,image = plt.hist2d(x,y,bins=100
                                      ,norm=LogNorm()
                                      , cmap = plt.cm.rainbow)
plt.colorbar()
plt.subplot(122)
plt.contour(counts.transpose(),extent=[xbins[0],xbins[-1],ybins[0],ybins[-1]],
    linewidths=3, cmap = plt.cm.rainbow, levels = [1,5,10,25,50,70,80,100])

This produces: Histogram and contour map