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

new completer for qtconsole....

new completer for qtconsole. add a completer to the qtconsole that is navigable by arraow keys and tab. One need to call it twice to get it on focus and be able to select completion with Return. looks like zsh completer, not the gui drop down list of --gui-completer. This also try to split the completion logic from console_widget, and try to keep the old completer qui around. The plain completer that never takes focus back, and the QlistWidget completer. to switch between the 3, the --gui-completion flag as been changed to take an argument (plain, droplist, ncurses).

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      """Parallel histogram function"""

      import numpy

      from IPython.parallel import Reference

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

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

          Parameters

          ----------

              view

                  IPython DirectView 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(view.targets)

          # view.push(dict(bins=bins, rng=rng))

          with view.sync_imports():

              import numpy

          rets = view.apply_sync(lambda a, b, rng: numpy.histogram(a,b,rng), Reference(a), bins, rng)

          hists = [ r[0] for r in rets ]

          lower_edges = [ r[1] for r in rets ]

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

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

          hist_array = numpy.array(hists).reshape(nengines, -1)

          # 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
				from IPython.parallel import Reference

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

				Parameters
				----------
				view
				IPython DirectView 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(view.targets)

				# view.push(dict(bins=bins, rng=rng))
				with view.sync_imports():
				import numpy
				rets = view.apply_sync(lambda a, b, rng: numpy.histogram(a,b,rng), Reference(a), bins, rng)
				hists = [ r[0] for r in rets ]
				lower_edges = [ r[1] for r in rets ]
				# view.execute('hist, lower_edges = numpy.histogram(%s, bins, rng)' % a)
				lower_edges = view.pull('lower_edges', targets=0)
				hist_array = numpy.array(hists).reshape(nengines, -1)
				# 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