On 5 April 2013 03:54, Sudheer Joseph <sudheer.jos...@yahoo.com> wrote: > Some how I am not getting the trick of the > rect = [0.1, 0.1, 0.8, 0.8] > > I tried > rect1= [0.1,0.1,.4,.4] > and rect2=[.4,.4,.8,.8] > but did not work
You don't say exactly what you did, and how it didn't work... If you read http://matplotlib.org/api/figure_api.html?highlight=add_axes#matplotlib.figure.Figure.add_axes it says "Add an axes at position rect [left, bottom, width, height]...". So you need to specify sensible values in rect1 and rect2. The following works fine for me: import matplotlib.pyplot as plt fig = plt.figure() rect1 = [0.1, 0.1, 0.4, 0.4] rect2 = [0.55, 0.1, 0.4, 0.4] ax1 = fig.add_axes(rect1) ax2 = fig.add_axes(rect2) ax1.plot(range(3)) ax2.plot(range(4, 8)) plt.show() So I would expect that you can adapt your original code to something like the following (untested): from windrose import WindroseAxes from matplotlib import pyplot as plt from numpy.random import random def new_axes(fig, rect): ax = WindroseAxes(fig, rect, axisbg='w') fig.add_axes(ax) return ax def set_legend(ax): l = ax.legend(axespad=-0.10) plt.setp(l.get_texts(), fontsize=8) #Create wind speed and direction variables ws = random(500)*6 wd = random(500)*360 ws1 = random(500)*6 wd1 = random(500)*360 rect1 = [0.1, 0.1, 0.4, 0.4] rect2 = [0.55, 0.1, 0.4, 0.4] fig = plt.figure(figsize=(8, 8), dpi=80, facecolor='w', edgecolor='w') ax1 = new_axes(fig, rect1) ax2 = new_axes(fig, rect2) #windrose like a stacked histogram with normed (displayed in percent) results ax1.bar(wd, ws, normed=True, opening=0.8, edgecolor='white') set_legend(ax1) #windrose like a stacked histogram with normed (displayed in percent) results ax2.bar(wd1, ws1, normed=True, opening=0.8, edgecolor='white') set_legend(ax2) plt.show() Cheers, Scott ------------------------------------------------------------------------------ Minimize network downtime and maximize team effectiveness. Reduce network management and security costs.Learn how to hire the most talented Cisco Certified professionals. Visit the Employer Resources Portal http://www.cisco.com/web/learning/employer_resources/index.html _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
