Moved files to a parallelcomputing folder. Added demo code for xmlrpc, matplotlib.

Author: Jonathan Rocher

MPI/hello_world.py ParallelComputing/hello_world.pyMPI/hello_world.py renamed to ParallelComputing/hello_world.py

@@ -0,0 +1,23 @@
+""" Demo of a timer and an animation using matplotlib: crashes on WX but work 
+with the QT backend. 
+""" 
+
+from matplotlib import pyplot as plt
+
+from datetime import datetime
+fig = plt.figure()
+ax = fig.add_subplot(1, 1, 1)
+
+def updateTime(axes):
+    axes.set_title(datetime.now())
+    axes.figure.canvas.draw()
+
+# Specifying interval=100 is enough except for QT backend
+timer = fig.canvas.new_timer(interval=100) 
+# Add a call back to the function above. The callback can also be give a class 
+# with a __call__ method. See animation_demo2.
+timer.add_callback(updateTime, ax)
+timer.interval = 100 # Work around bug in QT timer
+
+timer.start()
+plt.show()

py_open_cl_demo.py ParallelComputing/py_open_cl_demo.pypy_open_cl_demo.py renamed to ParallelComputing/py_open_cl_demo.py

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+""" Demo 2 of a timer and an animation using matplotlib: this time the 
+Note: crashes on WX but works with the QT backend. 
+""" 
+
+fig = plt.figure()
+ax = fig.add_subplot(1, 1, 1)
+x = np.linspace(0, 20)
+y = 0.5 * x * x
+line, = ax.plot(x, y)
+
+# The class only takes a line object as a parameter. All
+# of the needed information is obtained from the object itself.
+class updatingLine(object):
+    def __init__(self, line):
+        self._line = line
+        self._xdata = line.get_xdata()
+        self._ydata = line.get_ydata()
+        self.counter = 0
+        self.canvas = line.figure.canvas
+
+    def __call__(self):
+        self._line.set_data(self._xdata[:self.counter],
+            self._ydata[:self.counter])
+        self.canvas.draw()
+        self.counter = (self.counter + 1) % self._xdata.size
+
+timer = fig.canvas.new_timer(interval=100)
+timer.add_callback(updatingLine(line))
+timer.start()

matplotlib/animation_demo.py

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+import numpy as np
+from matplotlib.animation import FuncAnimation
+import matplotlib.pyplot as plt
+
+t = np.linspace(0, 10, 500)
+x = np.exp(-0.5 * t) * np.sin(2 * np.pi * t)
+fig = plt.figure()
+ax = fig.add_subplot(1, 1, 1)
+line, = plt.plot(t, x)
+
+def update_line(frame, line, t, x):
+    line.set_data(t[:frame], x[:frame])
+
+anim = FuncAnimation(fig, update_line, fargs=(line, t, x), interval=50, 
+                     frames=t.size)
+plt.show()