Releases · strongio/torchcast · GitHub

10000 Releases · strongio/torchcast · GitHub

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29 Apr 15:22

jwdink

v0.6.0 Latest

Latest

v0.6.0 (2025-04-25)

Updated default `fit()` behavior

The fit() method of torchcast.state_space.StateSpaceModel has been updated:

The default LBFGS settings have been updated to avoid the unnecessary inner loop (see here).
The default convergence settings have been updated to increase patience to 2 (instead of 1) and increase max_iter to 300 (instead of 200).
To restore the old behavior, pass optimizer=lambda p: torch.optim.LBFGS(p, max_eval=8, line_search_fn='strong_wolfe'), stopping={'patience' : 1, 'max_iter' : 200}.
Convergence is now controlled by a torch.utils.Stopping instance (or kwargs for one). This means passing tol, patience, and max_iter directly to fit is deprecated; instead call fit(stopping={'patience' : ... etc}).

Updated default `Covariance` behavior

The 'low_rank' method is never chosen by default; if desired it must be selected manually using the 'method' kwarg (previously would automatically be chosen if rank was >= 10). This was based on poor performance empirically.
The starting values for the covariance diagonal have been increased.
Added initial_covariance kwarg to KalmanFilter and subclasses.

Updates to `BinomialFilter`

Added the observed_counts argument, allowing the user to specify whether observations are counts or proportions. If num_obs==1 then this argument is not required (since they are the same).
Fix bug in BinomialStep's kalman-gain calculation when num_obs > 1
Fix issues with BinomialFilter on the GPU.
Fix __getitem__() for BinomialPredictions.
Fix monte-carlo BinomialPredictions.log_prob() to properly marginalize over samples.

Other Fixes

Fix get_durations() on GPU.
Remove redundant matmul in KalmanStep._update()
ss_step is no longer a property but is instead an attribute, avoids unnecessary re-instantiation on each timestep

Assets 2

10 Jan 04:02

jwdink

v0.5.1

v0.5.1 (2025-01-09)

Documentation

New Using NN’s for Long-Range Forecasts: Electricity Data example
Documentation/README cleanup

Trainers

Add torchcast.utils.training module with...

SimpleTrainer for training simple nn.Modules
SeasonalEmbeddingsTrainer for training nn.Modules to embed seasonal patterns.
StateSpaceTrainer for training torchcast's StateSpaceModels (when data are too big for the fit() method)

Baseline

Add make_baseline helper to generate baseline forecasts using a simple n-back method 3641e7c

Fixes

Ensure consistent column-ordering and default RangeIndex in output of Predictions.to_dataframe() 0a0fc81, f33c638
Fix default behavior in how TimeSeriesDataLoader forward-fills nans for the X tensor 0a0fc81
Fix seasonal initial values when passing initial_value to forward cae2879
Fix behavior of StateSpaceModel.simulate() when num_sims > 1 cae2879
Fix extra arg in ExpSmoother._generate_predictions() b553248
Make TimeSeriesDataset.split_measures() usable by removing which argument 8f1001b

Assets 2

09 Oct 20:28

strongio-machine

v0.4.1

v0.4.1 (2024-10-09)

Continuous Integration

ci: Update actions/checkout version (ed64632)
ci: Clone repo using PAT (d0adaca)
ci: Enable repo push (f565d2a)
ci: Use SSH Key (469d531)
ci: Fix docs job permissions (e6e2e34)
ci: Pick python version form pyproject.toml (2a9eef7)
ci: Setup auto-release (9df4f26)

Documentation

docs: Fix examples (6f5a2dc)
docs: AirQuality datasets [skip ci] (c675f04)
docs: Self-hosted docs and fixtures (baca184)

Fixes

fix: AQ Dataset (9b6e23e)

Refactoring

refactor: Switch to pyproject.toml (6de2f27)

Assets 2

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