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"""Example of how to use matplotlib to plot parallel data.
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The idea here is to run matplotlib is the same IPython session
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as an ipython parallel Client. That way matplotlib
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can be used to plot parallel data that is gathered using
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a DirectView.
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To run this example, first start the IPython controller and 4
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engines::
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ipcluster -n 4
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Then start ipython with matplotlib integration mode::
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ipython --matplotlib
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Then a simple "%run parallel_plot.ipy" in IPython will run the
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example.
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"""
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import matplotlib.pyplot as plt
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from IPython.parallel import Client
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# Get an IPython Client
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rc = Client()
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v = rc[:]
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# Create random arrays on the engines
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# This is to simulate arrays that you have calculated in parallel
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# on the engines.
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# Anymore that length 10000 arrays, matplotlib starts to be slow
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%px import numpy as np
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%px x = np.random.standard_normal(10000)
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%px y = np.random.standard_normal(10000)
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print v.apply_async(lambda : x[0:10]).get_dict()
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print v.apply_async(lambda : y[0:10]).get_dict()
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# Bring back the data
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x_local = v.gather('x', block=True)
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y_local = v.gather('y', block=True)
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# Make a scatter plot of the gathered data
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plt.plot(x_local, y_local,'ro')
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