I have generated some data in Python using matplotlib.hist2d. An example of the data is seen below.
As you can see this data has some contours in it found by tracing the same color throughout the plot. I see a gamma distribution centered around 0.015. I would like to take this data and gather these contours so I can see a line trace through each color level. I tried playing around with the contour function as here
counts, xedges, yedges, Image = hist2d(x, y, bins=bins, norm=LogNorm(), range=[[0, 1], [0, 400]])
contour(counts)
but that didn't seem to produce anything.
Does anyone know the best way to get these contours? Ideally I'd like to take these contours and fit a function (like a gamma function) to them and then get the function parameters.
Thanks
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
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