| 1 | from brian import * |
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| 2 | import numpy |
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| 3 | import scipy.ndimage as im |
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| 4 | |
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| 5 | __all__ = ['bar','StimulusArrayGroup'] |
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| 6 | |
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| 7 | def bar(width, height, thickness, angle): |
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| 8 | ''' |
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| 9 | An array of given dimensions with a bar of given thickness and angle |
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| 10 | ''' |
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| 11 | stimulus = numpy.zeros((width, height)) |
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| 12 | stimulus[:,int(height/2.-thickness/2.):int(height/2.+thickness/2.)] = 1. |
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| 13 | stimulus = im.rotate(stimulus, angle, reshape=False) |
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| 14 | return stimulus |
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| 15 | |
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| 16 | class StimulusArrayGroup(PoissonGroup): |
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| 17 | ''' |
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| 18 | A group of neurons which fire with a given stimulus at a given rate |
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| 19 | |
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| 20 | The argument ``stimulus`` should be a 2D array with values between 0 and 1. |
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| 21 | The point in the stimulus array at position (y,x) will correspond to the |
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| 22 | neuron with index i=y*width+x. This neuron will fire Poisson spikes at |
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| 23 | ``rate*stimulus[y,x]`` Hz. The stimulus will start at time ``onset`` |
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| 24 | for ``duration``. |
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| 25 | ''' |
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| 26 | def __init__(self, stimulus, rate, onset, duration): |
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| 27 | height, width = stimulus.shape |
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| 28 | stim = stimulus.ravel()*rate |
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| 29 | self.stimulus = stim |
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| 30 | def stimfunc(t): |
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| 31 | if onset<t<(onset+duration): |
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| 32 | return stim |
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| 33 | else: |
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| 34 | return 0.*Hz |
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| 35 | PoissonGroup.__init__(self, width*height, stimfunc) |
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| 36 | |
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| 37 | if __name__=='__main__': |
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| 38 | import pylab |
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| 39 | subplot(121) |
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| 40 | stim = bar(100,100,10,90)*0.9+0.1 |
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| 41 | pylab.imshow(stim, origin='lower') |
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| 42 | pylab.gray() |
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| 43 | G = StimulusArrayGroup(stim, 50*Hz, 100*ms, 100*ms) |
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| 44 | M = SpikeMonitor(G) |
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| 45 | run(300*ms) |
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| 46 | subplot(122) |
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| 47 | raster_plot(M) |
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| 48 | axis(xmin=0,xmax=300) |
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| 49 | show() |
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