upstream/ipython Files · docs/examples/kernel/phistogram.py

Initial version of working refactored ipcluster....

Initial version of working refactored ipcluster. This new version uses Twisted's cross platform process management API and provides: * New command line parsing using argparse. This allows for different subcommands (ipcluster local, ipcluster pbs, ipcluster mpirun, etc). * Currently working local and mpirun stating of clusters. * Almost working pbs starting. This has no docs and no tests as of yet and should be considered a tech preview.

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      """Parallel histogram function"""

      import numpy

      def phistogram(rc, a, bins=10, rng=None, normed=False):

          """Compute the histogram of a remote array a.

          :Parameters:

              rc

                  IPython RemoteController instance

              a : str

                  String name of the remote array

              bins : int

                  Number of histogram bins

              rng : (float, float)

                  Tuple of min, max of the range to histogram

              normed : boolean

                  Should the histogram counts be normalized to 1

          """

          nengines = len(rc)

          rc.push(dict(bins=bins, rng=rng))

          rc.execute('import numpy')

          rc.execute('hist, lower_edges = numpy.histogram(%s, bins, rng)' % a)

          lower_edges = rc.pull('lower_edges', targets=0)

          hist_array = rc.gather('hist')

          hist_array.shape = (nengines,-1)

          total_hist = numpy.sum(hist_array, 0)

          if normed:

              total_hist = total_hist/numpy.sum(total_hist,dtype=float)

          return total_hist, lower_edges

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				"""Parallel histogram function"""
				import numpy

				def phistogram(rc, a, bins=10, rng=None, normed=False):
				"""Compute the histogram of a remote array a.

				:Parameters:
				rc
				IPython RemoteController instance
				a : str
				String name of the remote array
				bins : int
				Number of histogram bins
				rng : (float, float)
				Tuple of min, max of the range to histogram
				normed : boolean
				Should the histogram counts be normalized to 1
				"""
				nengines = len(rc)
				rc.push(dict(bins=bins, rng=rng))
				rc.execute('import numpy')
				rc.execute('hist, lower_edges = numpy.histogram(%s, bins, rng)' % a)
				lower_edges = rc.pull('lower_edges', targets=0)
				hist_array = rc.gather('hist')
				hist_array.shape = (nengines,-1)
				total_hist = numpy.sum(hist_array, 0)
				if normed:
				total_hist = total_hist/numpy.sum(total_hist,dtype=float)
				return total_hist, lower_edges