import convis inp = convis.streams.RandomStream((20, 20), level=3.0, mean=10.0) convis.plot(inp.get(100))
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()
import convis n = convis.streams.PseudoNMNIST() convis.plot(n.get(200))
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])