You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Created new DataModel class as interface/superclass for all data-driven models. Data-driven models are interchangeable in use (e.g., simulation, use with prog_algs) with physics-based models. DataModels can be trained using data (.from_data), or an existing model (.from_model)
Introduced new LSTM State Transition DataModel. See lstm_model, full_lstm_model, and custom_model for examples of use
DMD model updated to new data-driven model interface. Can now be created from data as well as an existing model
Added ability to integrate training noise to data for DMD Model
New Model: Single-Phase DC Motor
Added the ability to select integration method when simulation. Current options are Euler and RK4
New feature allowing serialization of model parameters as JSON. See serialization example
Added automatic step size feature in simulation. When enabled, step size will adapt to meet the exact save_pts and save_freq. Step size range can also be bounded
New Example Model: Simple Paris' Law
Added ability to set bounds when estimating parameters (See PrognosticsModel.estimate_params())
Initialize method is now optional
Various bug fixes and performance improvements
Acknowledgements
Thank you to our intern Henry Lembo (@hlembo) for his contributions to this release.
This release includes contributions from NASA's Autonomous Spacecraft Operations (ASO), Data and Reasoning Fabric (DRF), System Wide Safety (SWS), and Transformative Tools & Technologies (TTT) projects. Thank you for your support!
reacted with thumbs up emoji reacted with thumbs down emoji reacted with laugh emoji reacted with hooray emoji reacted with confused emoji reacted with heart emoji reacted with rocket emoji reacted with eyes emoji
-
Release v1.4
Acknowledgements
Thank you to our intern Henry Lembo (@hlembo) for his contributions to this release.
This release includes contributions from NASA's Autonomous Spacecraft Operations (ASO), Data and Reasoning Fabric (DRF), System Wide Safety (SWS), and Transformative Tools & Technologies (TTT) projects. Thank you for your support!
This discussion was created from the release prog_models v1.4.
Beta Was this translation helpful? Give feedback.
All reactions