Accelerated MotionModel that has passed all the testing functions! #17
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…ed absolute sigma in Linear model
…odel error calculations
… Update trans_positions
Update data fitting logic: Compare observed data points with model parameters. If n_obs < n_params, return fill value for the parameters and infinity for the uncertainties; Otherwise, calculate parameters normally. If n_obs = n_params and absolute_sigma=False, return infinity for uncertainties (Same behavior as scipy curve fit).
…motion models. Update fitting logic: Provide multiple motion models, use the available model with the most number of parameters to fit according to the observed data points (i.e., choose the model with n_obs >= n_params). Removed motion_model_input and default_motion_model for clarity.
…atch_pos at_time into model; Renamed get_ functions into calc_ functions
… and get_batch_pos_at_time into model; Replaced MotionModel.fit_motion_model with MotionModel.fit; Rewrote and accelerated StarTable.fit_velocities with StarTable.fit_motion_model
hustonm
reviewed
Jan 14, 2026
| edx = np.arange(n_obs, dtype=int) | ||
| # Precompute All Bootstrap Draws at Once | ||
| # Ensure there are enough unique points in each bootstrap sample | ||
| bdx_unique = np.stack([ |
Contributor
There was a problem hiding this comment.
Why is the size of the bootstrap index arrays 2*n_params now? The previous version used the number of points in the full data set.
hustonm
reviewed
Jan 14, 2026
| fit_param_names = [] | ||
|
|
||
| # Number of fit parameters/required observations in each direction | ||
| n_params = int(np.ceil(len(fit_param_names) / 2)) |
Contributor
There was a problem hiding this comment.
We should confirm that this is adequate for other motion models that we intend to add in the future. It'll work for the current ones.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Major changes are:
n_obs >= n_param. By default,motion_models=[Empty, Fixed, Linear]inStarTable.fit_motion_model. Empty and Fixed are always added.downgradethe given ones if there are not enough observed points, untiln_obs >= n_param. Empty and Fixed are always added.default_motion_modelis now removed, as the actually used motion model is determined by the number of available epochs to fit and the list of provided models inmotion_models.motion_model_dictis now removed, and all the model-related parameters go intofixed_params_dict.t0is now optional and will be calculated as np.average(t, weights=1./np.hypot(xe, ye)) if not provided.get_star_position_at_timeandget_batch_star_positionsintoMotionModel.model, which is now fully vectorized and returns positions and uncertainties in shapes of(N_stars, N_times), or(N_stars,)whenN_times=1, or(N_times,)whenN_stars=1.StarTable.fit_motion_modelsignificantly forn_epochs < 300! Now achieving > 10,000 iterations per second for 5 epochs!Name Changes:
MotionModel.fit_motion_model->MotionModel.fitStarTable.fit_velocities->StarTable.fit_motion_modelMotionModel.get_star_position_at_time / get_batch_star_positions->MotionModel.model