Here is full trace:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/home/wakatana/experiments_today/v3/run_nupic.py in <module>()
239 SWARM_CFG["PREDICTION_STEP"],
# PREDICTION STEP
240 Verbose=True,
# VERBOSE
--> 241 VeryVerbose=False
# VERY VERBOSE
242 )
243 RUNMODEL_STOP_TIME = SCRIPT_STOP_TIME =
calendar.timegm(time.gmtime())
/home/wakatana/experiments_today/v3/experiments/hot_gym_anomaly/run_model/run_model.py
in runModel(model, inputFile, outputFile, predictionSteps, Verbose,
VeryVerbose)
67
68 # Compute the Anomaly Likelihood
---> 69 likelihood = anomalyLikelihood.anomalyProbability(col2,
tmp, col1)
70 logLikelihood =
anomalyLikelihood.computeLogLikelihood(likelihood)
71
/home/wakatana/.local/lib/python2.7/site-packages/nupic-0.3.0.dev0-py2.7-linux-x86_64.egg/nupic/algorithms/anomaly_likelihood.pyc
in anomalyProbability(self, value, anomalyScore, timestamp)
140 estimateAnomalyLikelihoods(
141 self._historicalScores,
--> 142 skipRecords = self._claLearningPeriod)
143 )
144
/home/wakatana/.local/lib/python2.7/site-packages/nupic-0.3.0.dev0-py2.7-linux-x86_64.egg/nupic/algorithms/anomaly_likelihood.pyc
in estimateAnomalyLikelihoods(anomalyScores, averagingWindow,
skipRecords, verbosity)
297 metricValues = numpy.array(s)
298 metricDistribution = estimateNormal(metricValues[skipRecords:],
--> 299
performLowerBoundCheck=False)
300
301 if metricDistribution["variance"] < 1.5e-5:
/home/wakatana/.local/lib/python2.7/site-packages/nupic-0.3.0.dev0-py2.7-linux-x86_64.egg/nupic/algorithms/anomaly_likelihood.pyc
in estimateNormal(sampleData, performLowerBoundCheck)
511 params = {
512 "name": "normal",
--> 513 "mean": numpy.mean(sampleData),
514 "variance": numpy.var(sampleData),
515 }
/usr/lib/python2.7/dist-packages/numpy/core/fromnumeric.pyc in mean(a,
axis, dtype, out, keepdims)
2714
2715 return _methods._mean(a, axis=axis, dtype=dtype,
-> 2716 out=out, keepdims=keepdims)
2717
2718 def std(a, axis=None, dtype=None, out=None, ddof=0,
keepdims=False):
/usr/lib/python2.7/dist-packages/numpy/core/_methods.pyc in _mean(a,
axis, dtype, out, keepdims)
60 dtype = mu.dtype('f8')
61
---> 62 ret = um.add.reduce(arr, axis=axis, dtype=dtype, out=out,
keepdims=keepdims)
63 if isinstance(ret, mu.ndarray):
64 ret = um.true_divide(
TypeError: cannot perform reduce with flexible type
