environment/share/doc/ipython/examples/parallel/phistogram.py
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
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
def phistogram ( view , a , bins = 10 , rng = None , normed = False ) : 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
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
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