Пример #1
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import convis
inp = convis.streams.RandomStream((20, 20), level=3.0, mean=10.0)
convis.plot(inp.get(100))
Пример #2
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import convis
from matplotlib.pylab import plot, xlim, gcf
stream = convis.streams.PoissonMNISTStream('../data', rep=20, fr=0.20)
# here we are using a very high firing rate for easy visualization
# (20% of cells are active in each frame)
convis.plot(stream.get(500))
gcf().show()
convis.plot(stream.get(500))
gcf().show()
stream.reset()  # returning to the start
convis.plot(stream.get(500))
gcf().show()
Пример #3
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import convis
n = convis.streams.PseudoNMNIST()
convis.plot(n.get(200)) 
Пример #4
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import convis
model = convis.models.Retina()
inp = convis.streams.RandomStream((20, 20), mean=127, level=100.0)
o = model.run(inp, dt=100, max_t=1000)
convis.plot(o[0])