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Cleaned up release tools directory....
Cleaned up release tools directory. Converted almost all to python scripts and made toollib to collect common functions and avoid repetition. Properly commented and documented what each script does. The run_ipy_in_profiler one seems broken, I'm not sure what to do with it. We need to either fix it or remove it later, but it's not critical for 0.10.

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parallel_pylab.ipy
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Brian E Granger
Adding examples from ipython1-dev to docs/examples/kernel. These ...
r1337 """Example of how to use pylab to plot parallel data.
The idea here is to run matplotlib is the same IPython session
as an ipython RemoteController client. That way matplotlib
can be used to plot parallel data that is gathered using
RemoteController.
To run this example, first start the IPython controller and 4
engines::
ipcluster -n 4
Then start ipython in pylab mode::
ipython -pylab
Then a simple "run parallel_pylab.ipy" in IPython will run the
example.
"""
import numpy as N
from pylab import *
Brian E Granger
Fixed most of the examples. A few still don't work, but this is a start.
r1338 from IPython.kernel import client
Brian E Granger
Adding examples from ipython1-dev to docs/examples/kernel. These ...
r1337
# Get an IPython1 client
rc = client.MultiEngineClient()
rc.get_ids()
rc.activate()
# Create random arrays on the engines
# This is to simulate arrays that you have calculated in parallel
# on the engines.
# Anymore that length 10000 arrays, matplotlib starts to be slow
%px import numpy as N
%px x = N.random.standard_normal(10000)
%px y = N.random.standard_normal(10000)
%px print x[0:10]
%px print y[0:10]
# Bring back the data
x_local = rc.gather('x')
y_local = rc.gather('y')
# Make a scatter plot of the gathered data
plot(x_local, y_local,'ro')