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DOC: fix some minor issues with histogram2d docstring formatting.
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rgommers committed Aug 11, 2013
1 parent f62522c commit ed908c7
Showing 1 changed file with 19 additions and 9 deletions.
28 changes: 19 additions & 9 deletions numpy/lib/twodim_base.py
Original file line number Diff line number Diff line change
Expand Up @@ -585,39 +585,48 @@ def histogram2d(x, y, bins=10, range=None, normed=False, weights=None):
Examples
--------
2D-histogram with variable bin width:
>>> import matplotlib as mpl
>>> import matplotlib.pyplot as plt
# First we define the bin edges
Construct a 2D-histogram with variable bin width. First define the bin
edges:
>>> xedges = [0, 1, 1.5, 3, 5]
>>> yedges = [0, 2, 3, 4, 6]
# Next we create a histogram H with random bin content
Next we create a histogram H with random bin content:
>>> x = np.random.normal(3, 1, 100)
>>> y = np.random.normal(1, 1, 100)
>>> H, xedges, yedges = np.histogram2d(y, x, bins=(xedges, yedges))
# Or we fill the histogram H with a determined bin content
Or we fill the histogram H with a determined bin content:
>>> H = np.ones((4, 4)).cumsum().reshape(4, 4)
>>> print H[::-1] # This shows the bin content in the order as plotted
[[ 13. 14. 15. 16.]
[ 9. 10. 11. 12.]
[ 5. 6. 7. 8.]
[ 1. 2. 3. 4.]]
Imshow can only do an equidistant representation of bins:
>>> fig = plt.figure(figsize=(7, 3))
# Imshow can only do an equidistant representation of bins
>>> ax = fig.add_subplot(131)
>>> ax.set_title('imshow:\nequidistant')
>>> im = plt.imshow(H, interpolation='nearest', origin='low',
extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]])
# pcolormesh can displaying exact bin edges
pcolormesh can displaying exact bin edges:
>>> ax = fig.add_subplot(132)
>>> ax.set_title('pcolormesh:\nexact bin edges')
>>> X, Y = np.meshgrid(xedges, yedges)
>>> ax.pcolormesh(X, Y, H)
>>> ax.set_aspect('equal')
# NonUniformImage displays exact bin edges with interpolation
NonUniformImage displays exact bin edges with interpolation:
>>> ax = fig.add_subplot(133)
>>> ax.set_title('NonUniformImage:\ninterpolated')
>>> im = mpl.image.NonUniformImage(ax, interpolation='bilinear')
Expand All @@ -629,6 +638,7 @@ def histogram2d(x, y, bins=10, range=None, normed=False, weights=None):
>>> ax.set_ylim(yedges[0], yedges[-1])
>>> ax.set_aspect('equal')
>>> plt.show()
"""
from numpy import histogramdd

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