Problem: self.inputMin, inputMax are equal on some dataset

[breznak]

A possible bug, the self.inputMin, inputMax is provided by the NAB API.

• one some dataset (I don't know which) the values are all the same (ie the dataset is just a flat line)

57: Results have been written to /mnt/store/devel/HTM/NAB/results/htmcore/realTweets/htmcore_Twitter_volume_UPS.csv multiprocessing.pool.RemoteTraceback: """ Traceback (most recent call last): File "/usr/lib/python3.6/multiprocessing/pool.py", line 119, in worker result = (True, func(*args, *kwds)) File "/usr/lib/python3.6/multiprocessing/pool.py", line 44, in mapstar return list(map(args)) File "/mnt/store/devel/HTM/NAB/nab/detectors/base.py", line 147, in detectDataSet detectorInstance.initialize() File "/mnt/store/devel/HTM/NAB/nab/detectors/htmcore/htmcore_detector.py", line 284, in initialize assert self.inputMin < self.inputMax, "FAILED "+str(self.inputMin)+" "+str(self.inputMax) AssertionError: FAILED 45.0 45.0 """ The above exception was the direct cause of the following exception: Traceback (most recent call last): File "run.py", line 247, in main(args) File "run.py", line 96, in main runner.detect(detectorConstructors) File "/mnt/store/devel/HTM/NAB/nab/runner.py", line 134, in detect self.pool.map_async(detectDataSet, args).get(99999999) File "/usr/lib/python3.6/multiprocessing/pool.py", line 644, in get raise self._value AssertionError: FAILED 45.0 45.0

• our c++ ScalarEncoder has a check that min < max

  • which is reasonable, for otherwise the encoder would use 0 for some internal sizes.

• I don't know if the problem is a bug in how this NAB implementation computes/deals with setting the min.max,

• or if we have to workaround that in c++ ScalarEncoder?

[ctrl-z-9000-times]

I think that this is a bug in NAB, or maybe the data set is a flat line at 45.0?

[markNZed]

One of the timeseries https://github.com/htm-community/NAB/blob/master/data/artificialNoAnomaly/art_flatline.csv is a flat line - I guess to check that the detector does not create false positives.