#!/usr/bin/env python import matplotlib.pyplot as plt import numpy as np 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, (ax1, ax2, ax3) = plt.subplots(3, 1, sharex=True) ax1.fill_between(x, 0, y1) ax1.set_ylabel('between y1 and 0') ax2.fill_between(x, y1, 1) ax2.set_ylabel('between y1 and 1') ax3.fill_between(x, y1, y2) ax3.set_ylabel('between y1 and y2') ax3.set_xlabel('x') # 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, (ax, ax1) = plt.subplots(2, 1, sharex=True) ax.plot(x, y1, x, y2, color='black') ax.fill_between(x, y1, y2, where=y2 >= y1, facecolor='green', interpolate=True) ax.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red', interpolate=True) ax.set_title('fill between where') # Test support for masked arrays. y2 = np.ma.masked_greater(y2, 1.0) ax1.plot(x, y1, x, y2, color='black') ax1.fill_between(x, y1, y2, where=y2 >= y1, facecolor='green', interpolate=True) ax1.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red', interpolate=True) 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. # show how to use transforms to create axes spans where a certain condition is satisfied fig, ax = plt.subplots() y = np.sin(4*np.pi*x) ax.plot(x, y, color='black') # use the data coordinates for the x-axis and the axes coordinates for the y-axis import matplotlib.transforms as mtransforms trans = mtransforms.blended_transform_factory(ax.transData, ax.transAxes) theta = 0.9 ax.axhline(theta, color='green', lw=2, alpha=0.5) ax.axhline(-theta, color='red', lw=2, alpha=0.5) ax.fill_between(x, 0, 1, where=y > theta, facecolor='green', alpha=0.5, transform=trans) ax.fill_between(x, 0, 1, where=y < -theta, facecolor='red', alpha=0.5, transform=trans) plt.show()