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import matplotlib.mlab as mlab
from matplotlib.pyplot import figure, show
import numpy as np

## Copy of fill_between.py but using fill_betweenx() instead.

x = np.arange(0.0, 2, 0.01)
y1 = np.sin(2*np.pi*x)
y2 = 1.2*np.sin(4*np.pi*x)

fig = figure()
ax1 = fig.add_subplot(311)
ax2 = fig.add_subplot(312, sharex=ax1)
ax3 = fig.add_subplot(313, sharex=ax1)

ax1.fill_betweenx(x, 0, y1)
ax1.set_ylabel('between y1 and 0')

ax2.fill_betweenx(x, y1, 1)
ax2.set_ylabel('between y1 and 1')

ax3.fill_betweenx(x, y1, y2)
ax3.set_ylabel('between y1 and y2')

# now fill between y1 and y2 where a logical condition is met.  Note
# this is different than calling
#   fill_between(x[where], y1[where],y2[where]
# because of edge effects over multiple contiguous regions.
fig = figure()
ax = fig.add_subplot(211)
ax.plot(y1, x, y2, x, color='black')
ax.fill_betweenx(x, y1, y2, where=y2>=y1, facecolor='green')
ax.fill_betweenx(x, y1, y2, where=y2<=y1, facecolor='red')
ax.set_title('fill between where')

# Test support for masked arrays.
y2 = np.ma.masked_greater(y2, 1.0)
ax1 = fig.add_subplot(212, sharex=ax)
ax1.plot(y1, x, y2, x, color='black')
ax1.fill_betweenx(x, y1, y2, where=y2>=y1, facecolor='green')
ax1.fill_betweenx(x, y1, y2, where=y2<=y1, facecolor='red')
ax1.set_title('Now regions with y2 > 1 are masked')

# This example illustrates a problem; because of the data
# gridding, there are undesired unfilled triangles at the crossover
# points.  A brute-force solution would be to interpolate all
# arrays to a very fine grid before plotting.


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