* Implemented unit tests for the new features in AnomalyLikelihood class.
* Convert AnomalyLikelihood._historicalScores to a user-configurable sliding window, instead of accumulating all of the incoming data points. This improved performance a ton! Added AnomalyLikelihood.forceModelRefresh() method.
* Update nupic.core to include backwards compatibility fix for RandomImpl.
* Uninstall pycapnp to avoid running tests that utilize the functionality and currently fail with Duplicate ID error.
* Makes pycapnp and corresponding serialization optional. If pycapnp is not installed then the corresponding serialization tests will be skipped.
* Add Multiple Prediction Test for NegLL Metric
* Add test for NegLL Error Metric
* Fix Orphan Decay Bug in temporal memory test
* Change decreasing overlaps test for coordinate encoder to not require a strict decrease (staying the same is ok).
* Allow specifying MonitoredTemporalMemory as TM implementation through OPF
* include bucket likelihood and classifier input in clamodel
* update metrics managers to pass model results to metrics
* introducting a computeFlag to prevent double-computation. * The flag is used to prevent double computation in the event that customCompute() is called at the same time as compute()
* Added `numRecords` param for consitency with the newly added `infer` method in FastCLACLassifier
* checking if classifier has a `maxCategoryCount` attribute. If not, set it to solve backward compatibilities issues
* renaming numCategories to maxCategoryCount to be constistent between KNN and CLA classifier
* made new experimentutils file containing InferenceElement, InferenceType, and ModelResult duplicates which we will want to change in the future