v1.2
Closed Nov 17, 2021
100% complete
Release v1.2
Note for existing users
This release includes changes to the return format of the MonteCarlo Predictor's predict
method. These changes were necessary to support non-sample based predictors. The non backwards-compatible changes are listed below:
- times:
- previous
List[List[float]]
where times[n][m] corresponds to timepoint m of sample n. - new
L…
- previous
Release v1.2
Note for existing users
This release includes changes to the return format of the MonteCarlo Predictor's predict
method. These changes were necessary to support non-sample based predictors. The non backwards-compatible changes are listed below:
- times:
- previous
List[List[float]]
where times[n][m] corresponds to timepoint m of sample n. - new
List[float]
where times[m] corresponds to timepoint m for all samples
- previous
- End of Life (EOL)/ Time of Event (ToE) estimates:
- previous
List[float]
where the values correspond to the time that the first event occurs. - new
UnweightedSamples
where keys correspond to the individual events predicted.
- previous
- State at time of event (ToE)
- previous: element in states
- new: member of toe event (e.g., toe.final_state['event1'])
General Improvements
- Added new visualization capabilities, including:
- Updates to UncertainData
- Metrics functions can now accept UncertainData or Predictions, and operate on multiple states/events [#92]
- Added additional examples demonstrating
prog_algs
features - Add support for Python 3.9
- Added support for prog_models v1.1
- General Bugfixes
State Estimator Improvements
- Particle Filter Sample Vectorization - significantly improves runtime for vectorized models [#76]
- Particle Filter now calculates weights in log-domain (improves numerical stability) [#76]
- Added ability to set initial time in state estimators using the
t0
parameter - Fixed bug where states were being reordered in UKF
- Fixed bug where t wasn't being set each step of PF
Predictor Changes
- New Unscented Transform Predictor [#40, #74]
- Predictors can now predict multiple events. [#81]
- New
Prediction
class to represent predicted future values (e.g., states). Returned from thePredictor.predict
method [#60, #25] - New
ToEPredictionProfile
class to represent and operate on the result of multiple predictions at different times of prediction [#91]
Notes
The changes in this release were produced in part by Northrop Grumman under a contributor license agreement. Thank you NGC!