def profileTM(tmClass, tmDim, nRuns):
  """
  profiling performance of TemporalMemory (TM)
  using the python cProfile module and ordered by cumulative time,
  see how to run on command-line above.

  @param tmClass implementation of TM (cpp, py, ..)
  @param tmDim number of columns in TM
  @param nRuns number of calls of the profiled code (epochs)
  """

  # create TM instance to measure
  tm = tmClass(numberOfCols=tmDim)

  # generate input data
  data = numpy.random.randint(0, 2, [tmDim, nRuns]).astype('float32')

  for i in xrange(nRuns):
    # new data every time, this is the worst case performance
    # real performance would be better, as the input data would not be completely random
    d = data[:,i]

    # the actual function to profile!
    tm.compute(d, True)
def profileTM(tmClass, tmDim, nRuns):
  """
  profiling performance of TemporalMemory (TM)
  using the python cProfile module and ordered by cumulative time,
  see how to run on command-line above.

  @param tmClass implementation of TM (cpp, py, ..)
  @param tmDim number of columns in TM
  @param nRuns number of calls of the profiled code (epochs)
  """

  # create TM instance to measure
  tm = tmClass(numberOfCols=tmDim)

  # generate input data
  data = numpy.random.randint(0, 2, [tmDim, nRuns]).astype('float32')

  for i in xrange(nRuns):
    # new data every time, this is the worst case performance
    # real performance would be better, as the input data would not be completely random
    d = data[:,i]

    # the actual function to profile!
    tm.compute(d, True)
def profileTM ( tmClass , tmDim , nRuns ) : # create TM instance to measure tm = tmClass ( numberOfCols = tmDim ) # generate input data data = numpy . random . randint ( 0 , 2 , [ tmDim , nRuns ] ) . astype ( 'float32' ) for i in xrange ( nRuns ) : # new data every time, this is the worst case performance # real performance would be better, as the input data would not be completely random d = data [ : , i ] # the actual function to profile! tm . compute ( d , True )
profiling performance of TemporalMemory (TM)
  using the python cProfile module and ordered by cumulative time,
  see how to run on command-line above.

  @param tmClass implementation of TM (cpp, py, ..)
  @param tmDim number of columns in TM
  @param nRuns number of calls of the profiled code (epochs)
profiling performance of TemporalMemory ( TM ) using the python cProfile module and ordered by cumulative time see how to run on command - line above .