1.0.0 (2026-04-27) Features add common code for training (4aca0a9) add deactivate method (4483ffb) add empty methods to be implemented in dt (599195d) add getter for active local dts (ecdb7d1) add handler for training (a91fe65) add last training time in inference event payload (c5419e1) add learning config file (be51454) add minimal main with patients activation scheduling (cfbf73b) add patient deactivation event scheduling (0049063) add scheduling of training and inferences for experiment TrainAfterTime (1a514a9) add seed to dt aggregate (6aa0ef8) add simulator start (b40f2df) add support for monitors (409ddd3) add training metrics export to csv (99f916c) better charts (0ae7c0b) DTAggregate: implement new data notification and train (a437ee6) export F1score, precision and recall (326e7e8) export more metrics on time when using adaptive policy (c0ac54e) implement DT aggregate skeleton (2fda026) implement DT skeleton (e23d63a) implement handler for inference on local dts (b79ca3f) implement handler for patient deactivation (7dd78a5) implement handler for training (eb4f631) implement inference for test on local DTs (5bd01aa) implement labelling (a52da1f) implement learning utils (58e935c) implement method to notify new model to local dts (1b9aefa) implement methods to register/unregister local dts (90f38f6) implement monitor for retraining on enough dts activated (f32a981) implement monitor for retraining on enough dts activated (87f76f4) implement monitor for retraining on performance degradation (e7544d9) implement notification of patient series to dt aggregate (c0f99fc) implement script to split dataset by patient (75f4984) implement simulator skeleton (8d0ec7f) implement timeseries forecasting on all data (a1fba5e) init dt aggregate for each dt (2385091) more learning configs (3ed8fc9) now using classification (7bb5ce3) passing last traing time to dt (417c91c) setup simulator to be a DES (09e7224) Dependency updates deps: add codecarbon (f74335a) deps: add matplotlib (7a5a5e4) deps: add pandas (3deb2f6) deps: add seaborn (d4405d8) deps: add torch (0c755d5) Bug Fixes add data export folder creation in main (920c292) adding timestamp column to DT data (a650857) comment out redudant monitor (aeb8a46) exporting test into one global csv (e158343) fix bootstrap months parameter (a634cb0) fix data updating from DT to DTAggregate (c19cf4f) fix events name (fe78c5b) fix inference scheduling (e3b1a86) fix last train time (087a96e) fix model setter to load fresh model from new weights (9c5fcc6) fix model setting (0b68bd6) fix patient_series type (1ee7876) fix test event timing (27dda2b) fix test set start and end indexes (2d01a7e) fix test set when there are not enough points (5580028) fix time horizon of the prediction and time interval for plotting (b8e6559) getting current mean and std for patients that becomes active before retraining (9018cfe) import create loaders function (4c5e3ac) init first model in dtaggregate as a LSTM and not None (aaac46f) init optimizer after the model (e24f117) moving also the model to the right device (6ec458e) moving also the model to the right device (2e9e115) passing also the seed to DT (74c302b) remove DTAggregate type to avoid circular dependencies (b67476e) remove useless init dts code (8510f23) remove val ratio (e11b1fe) removing deploy on dockerhub (a0d4531) safely ignoring patients with not enough data (5b05187) update project name (33a238f) using model state_dict and not model itself (fd2ca69) using normalized series also in testing (b6462f2) using weighted loss to handle class imbalance (b363e27) General maintenance adding log prints (5d693e4) remove useless todo comment (c8dd3e0) updating some hyperparameters (a8e6d97)