Revision: 5262
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5262&view=rev
Author: jdh2358
Date: 2008-05-25 09:07:58 -0700 (Sun, 25 May 2008)
Log Message:
-----------
added logo2
Added Paths:
-----------
trunk/matplotlib/examples/pylab/logo2.py
Added: trunk/matplotlib/examples/pylab/logo2.py
===================================================================
--- trunk/matplotlib/examples/pylab/logo2.py (rev 0)
+++ trunk/matplotlib/examples/pylab/logo2.py 2008-05-25 16:07:58 UTC (rev
5262)
@@ -0,0 +1,65 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.cm as cm
+import matplotlib.mlab as mlab
+
+axalpha = 0.05
+fig = plt.figure(figsize=(8, 2),dpi=80)
+fig.figurePatch.set_edgecolor('#FFFFCC')
+fig.figurePatch.set_facecolor('#FFFFCC')
+
+# the polar bar plot
+ax = fig.add_axes([0.05, 0.05, 0.2, 01], polar=True)
+ax.axesPatch.set_alpha(axalpha)
+N = 20
+theta = np.arange(0.0, 2*np.pi, 2*np.pi/N)
+radii = 10*np.random.rand(N)
+width = np.pi/4*np.random.rand(N)
+bars = ax.bar(theta, radii, width=width, bottom=0.0)
+for r,bar in zip(radii, bars):
+ bar.set_facecolor( cm.jet(r/10.))
+ bar.set_alpha(0.5)
+
+for label in ax.get_xticklabels() + ax.get_yticklabels():
+ label.set_visible(False)
+
+
+# the histogram
+axhist = fig.add_axes([0.275, 0.075, 0.2, 0.4])
+axhist.axesPatch.set_alpha(axalpha)
+mu, sigma = 100, 15
+x = mu + sigma*np.random.randn(10000)
+
+# the histogram of the data
+n, bins, patches = axhist.hist(x, 50, normed=1, facecolor='green',
edgecolor='green', alpha=0.75)
+
+
+y = mlab.normpdf( bins, mu, sigma)
+l = axhist.plot(bins, y, 'r', lw=1)
+
+axhist.set_title('Density of IQ',fontsize=6)
+axhist.set_xlabel('IQ', fontsize=6)
+axhist.set_ylabel('P(IQ)', fontsize=6)
+ax.set_xlim(-2*sigma, 2*sigma)
+for label in axhist.get_xticklabels() + axhist.get_yticklabels():
+ label.set_visible(False)
+
+
+axback = fig.add_axes([0., 0., 1., 1.])
+
+#the math background
+tex = r"$W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = U^{3\beta}_{\delta_1 \rho_1}
+ \frac{1}{8 \pi 2} \int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 \left[\frac{
U^{2\beta}_{\delta_1 \rho_1} - \alpha^\prime_2U^{1\beta}_{\rho_1 \sigma_2}
}{U^{0\beta}_{\rho_1 \sigma_2}}\right]$"
+axback.text(0.5, 0.5, tex,
+ transform=axback.transAxes, color="0.5", alpha=0.5, fontsize=40,
+ ha='center', va='center')
+axback.set_axis_off()
+
+# the matplotlib title
+axback.text(0.3, 0.95, 'matplotlib', color='black', fontsize=75,
+ ha='left', va='top', alpha=1.0,
+ transform=axback.transAxes)
+
+
+
+plt.show()
+
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