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src/n/e/NeuroTools-0.2.0/examples/retina/test_parallel.py   NeuroTools(Download)
 
    import NeuroTools.plotting as plotting
    pylab = plotting.get_display(True)
    pylab.rcParams.update(plotting.pylab_params())
    print rates, neuron_rates

src/n/e/NeuroTools-0.2.0/examples/parameter_search/parameter_search_example.py   NeuroTools(Download)
                                      and (r['weight'] == weights[w_i])][0]
    import NeuroTools.plotting as plotting
    pylab = plotting.get_display(True)
    pylab.rcParams.update(plotting.pylab_params())
    subplot = pylab.imshow(neuron_rates, 

src/n/e/NeuroTools-0.2.0/src/signals/spikes.py   NeuroTools(Download)
 
from NeuroTools.io import *
from NeuroTools.plotting import get_display, set_axis_limits, set_labels, SimpleMultiplot, progress_bar
from pairs import *
from intervals import *
 
        spikes  = interval.slice_times(self.spike_times)
        subplot = get_display(display)
        if not subplot or not HAVE_PYLAB:
            print PYLAB_ERROR
 
        spk_hist = self.time_histogram(time_bin)
        subplot  = get_display(display)
        count    = 0
        t_min_l  = numpy.floor(t_min/time_bin)
        else:
            values, xaxis = numpy.histogram(isis, bins=bins, new=True)
        subplot       = get_display(display)
        values = values/float(values.sum())
        if not subplot or not HAVE_PYLAB:
        else:
            values, xaxis = numpy.histogram(cvs, bins=bins, new=True)
        subplot       = get_display(display)
        values = values/float(values.sum())                
        if not subplot or not HAVE_PYLAB:

src/n/e/NeuroTools-0.2.0/src/signals/analogs.py   NeuroTools(Download)
from NeuroTools import check_dependency, check_numpy_version
from NeuroTools.io import *
from NeuroTools.plotting import get_display, set_axis_limits, set_labels, SimpleMultiplot
 
HAVE_MATPLOTLIB = check_dependency('matplotlib')
            >> signal.plot(ylabel="Vm", display=z, kwargs={'color':'r'})
        """
        subplot   = get_display(display)
        time_axis = self.time_axis()
        if not subplot or not HAVE_PYLAB:
        N         = len(time_axis)
        Nspikes   = 0.
        subplot   = get_display(display)
        if average:
            result = numpy.zeros(N, float)
        if isinstance(eventdict, SpikeList):
            eventdict = eventdict.spiketrains
        figure   = get_display(display)
        subplotcount = 1
 
            elif mode is 'all':
                if first_done:
                    figure   = get_display(display)
                first_done = True
                subplotcount_all = 1

src/n/e/NeuroTools-0.2.0/src/analysis.py   NeuroTools(Download)
    return iFxy / varxy
 
from NeuroTools.plotting import get_display, set_labels
 
HAVE_PYLAB = check_dependency('pylab')
    # Plot the results if display=True
    if display:
        subplot = get_display(display)
        if not subplot or not HAVE_PYLAB:
            return differences, pred, norm

src/n/e/NeuroTools-0.2.0/test/test_plotting.py   NeuroTools(Download)
    def runTest(self):
 
        a = plotting.get_display(True)
        assert a != None
        a = plotting.get_display(False)
        assert a == None
        a = plotting.get_display(1234)
    def runTest(self):
 
        f = plotting.get_display(True)
        x = range(10)
        p = pylab.plot(x)
    def runTest(self):
 
        f = plotting.get_display(True)
        x = range(10)
        pylab.plot(x)