Data and histogram do not collide in matplotlib?

Question

I am creating a histogram for my data. Interestingly, when I plot my raw data and their histogram together on one plot, they are a "y-flipped" version of each other as follows:

I failed to find out the reason and fix it. My code snippet is as follows:

import math as mt
import numpy as np
import matplotlib.pylab as plt

x = np.random.randn(50)
y = np.random.randn(50)
w = np.random.randn(50)
leftBound, rightBound, topBound, bottomBound = min(x), max(x), max(y), min(y)
# parameters for histogram
x_edges = np.linspace(int(mt.floor(leftBound)), int(mt.ceil(rightBound)), int(mt.ceil(rightBound))-int(mt.floor(leftBound))+1)
y_edges = np.linspace(int(mt.floor(bottomBound)), int(mt.ceil(topBound)), int(mt.ceil(topBound))-int(mt.floor(bottomBound))+1)
# construct the histogram
wcounts = np.histogram2d(x, y, bins=(x_edges, y_edges), normed=False, weights=w)[0]
# wcounts is a 2D array, with each element representing the weighted count in a bins

# show histogram
extent = x_edges[0], x_edges[-1], y_edges[0], y_edges[-1]
fig = plt.figure()
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # left, bottom, width, height (range 0 to 1)
axes.set_xlabel('x (m)')
axes.set_ylabel('y (m)')
histogram = axes.imshow(np.transpose(wcounts), extent=extent, alpha=1, vmin=0.5, vmax=5, cmap=cm.binary) # alpha controls the transparency
fig.colorbar(histogram)

# show data
axes.plot(x, y, color = '#99ffff')

Since the data here are generated randomly for demonstration, I don't think it helps much, if the problem is with that particular data set. But anyway, if it is something wrong with the code, it still helps.

Answer 1

By default, axes.imshow(z) places array element z[0,0] in the top left corner of the axes (or the extent in this case). You probably want to either add the origin="bottom" argument to your imshow() call or pass a flipped data array, ie, z[:,::-1] .