examples/network/network_api_demo.py
def runNetwork(network, writer):
  """Run the network and write output to writer.

  :param network: a Network instance to run
  :param writer: a csv.writer instance to write output to
  """
  sensorRegion = network.regions["sensor"]
  spatialPoolerRegion = network.regions["spatialPoolerRegion"]
  temporalPoolerRegion = network.regions["temporalPoolerRegion"]
  anomalyLikelihoodRegion = network.regions["anomalyLikelihoodRegion"]

  prevPredictedColumns = []

  for i in xrange(_NUM_RECORDS):
    # Run the network for a single iteration
    network.run(1)

    # Write out the anomaly likelihood along with the record number and consumption
    # value.
    consumption = sensorRegion.getOutputData("sourceOut")[0]
    anomalyScore = temporalPoolerRegion.getOutputData("anomalyScore")[0]
    anomalyLikelihood = anomalyLikelihoodRegion.getOutputData("anomalyLikelihood")[0]
    writer.writerow((i, consumption, anomalyScore, anomalyLikelihood))
def runNetwork(network, writer):
  """Run the network and write output to writer.

  :param network: a Network instance to run
  :param writer: a csv.writer instance to write output to
  """
  sensorRegion = network.regions["sensor"]
  spatialPoolerRegion = network.regions["spatialPoolerRegion"]
  temporalPoolerRegion = network.regions["temporalPoolerRegion"]
  anomalyLikelihoodRegion = network.regions["anomalyLikelihoodRegion"]

  prevPredictedColumns = []

  for i in xrange(_NUM_RECORDS):
    # Run the network for a single iteration
    network.run(1)

    # Write out the anomaly likelihood along with the record number and consumption
    # value.
    consumption = sensorRegion.getOutputData("sourceOut")[0]
    anomalyScore = temporalPoolerRegion.getOutputData("anomalyScore")[0]
    anomalyLikelihood = anomalyLikelihoodRegion.getOutputData("anomalyLikelihood")[0]
    writer.writerow((i, consumption, anomalyScore, anomalyLikelihood))
def runNetwork ( network , writer ) : sensorRegion = network . regions [ "sensor" ] spatialPoolerRegion = network . regions [ "spatialPoolerRegion" ] temporalPoolerRegion = network . regions [ "temporalPoolerRegion" ] anomalyLikelihoodRegion = network . regions [ "anomalyLikelihoodRegion" ] prevPredictedColumns = [ ] for i in xrange ( _NUM_RECORDS ) : # Run the network for a single iteration network . run ( 1 ) # Write out the anomaly likelihood along with the record number and consumption # value. consumption = sensorRegion . getOutputData ( "sourceOut" ) [ 0 ] anomalyScore = temporalPoolerRegion . getOutputData ( "anomalyScore" ) [ 0 ] anomalyLikelihood = anomalyLikelihoodRegion . getOutputData ( "anomalyLikelihood" ) [ 0 ] writer . writerow ( ( i , consumption , anomalyScore , anomalyLikelihood ) )
Run the network and write output to writer.

  :param network: a Network instance to run
  :param writer: a csv.writer instance to write output to
Run the network and write output to writer .