Woops, accidentally hit send. Here is the corrected code to run the patched sp
from nupic.encoders import ScalarEncoder > > from nupic.research.spatial_pooler import SpatialPooler > > import numpy > > from patcher import Patcher > > >> #create an encoder > > encoder = ScalarEncoder(n=22, w=3, minval=2.5, maxval=97.5, >> clipInput=True, forced=True) > > >> #create a spatial pooler > > sp = SpatialPooler(inputDimensions=(22), > > columnDimensions=(4,), potentialRadius=22, numActiveColumnsPerInhArea=1, > > globalInhibition=True, synPermActiveInc=0.03, potentialPct=1.0) > > >> Patcher().patchSP(sp) >> > >> #make sp learn input 20 times > > output = numpy.zeros((4,), dtype='int') > > for _ in xrange(20): > > sp.compute(encoder.encode(1), learn=True, activeArray=output) > > > > > >> > > > > On Mon, Oct 27, 2014 at 5:35 PM, Matthew Taylor <[email protected]> wrote: > Mika, did Chetan's tip to patch the SP before running Cerebro fix your > problem? > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Mon, Oct 20, 2014 at 9:15 PM, Chetan Surpur <[email protected]> > wrote: > > Ah, so you have to patch the SP > > before > > you run it. > > > > > > > > On Sun, Oct 19, 2014 at 4:12 PM, Mika Schiller <[email protected]> > > wrote: > >> > >> I'm trying to make the sp learn an input 20 times as you can see in the > >> code below. First I go into nupic.cerebro2.server directory and run > python > >> server.py 9090. Then I go into nupic.cerebro2 directory, then /static > and > >> then run python -m SimpleHTTPServer 8000. When I go to > >> http://localhost:8000/ I see the display, but no cells or anything. > I've > >> attached a screenshot of what I'm seeing. Any idea what might be going > on > >> here? Did I patch the sp correctly? Thanks! > >> > >>>> > >>>> from nupic.encoders import ScalarEncoder > >>>> > >>>> from nupic.research.spatial_pooler import SpatialPooler > >>>> > >>>> import numpy > >>>> > >>>> from patcher import Patcher > >>>> > >>>> > >>>> #create an encoder > >>>> > >>>> encoder = ScalarEncoder(n=22, w=3, minval=2.5, maxval=97.5, > >>>> clipInput=True, forced=True) > >>>> > >>>> > >>>> #create a spatial pooler > >>>> > >>>> sp = SpatialPooler(inputDimensions=(22), > >>>> > >>>> columnDimensions=(4,), potentialRadius=22, > numActiveColumnsPerInhArea=1, > >>>> > >>>> globalInhibition=True, synPermActiveInc=0.03, potentialPct=1.0) > >>>> > >>>> > >>>> > >>>> > >>>> #make sp learn input 20 times > >>>> > >>>> output = numpy.zeros((4,), dtype='int') > >>>> > >>>> for _ in xrange(20): > >>>> > >>>> sp.compute(encoder.encode(1), learn=True, activeArray=output) > >> > >> > >>>> > >>>> > >>>> > >>>> if __name__ == "__main__": > >>>> > >>>> > >>>> > >>>> Patcher().patchSP(sp) > >> > >> > >> <Screen Shot 2014-10-19 at 7.08.50 PM.png> > > > > > >
