* now alpha long
* fix
* rename param
* thought i did this
* debug
* debug
* more
* more
* moar
* Revert "moar"
This reverts commit e347106246583982e1be206485ad4d8eb944f817.
* Revert "more"
This reverts commit 0746e6d2e400ce1715614c62af84a9680c4d65c1.
* Revert "more"
This reverts commit 0db5a8792c01bb2d687f9152e6ba37fb76d4a453.
* Revert "debug"
This reverts commit 72f235b13727980e4331ff487998ddc7c7f7fb63.
* Revert "debug"
This reverts commit 7871b69f8c1bdffed386c2baac99542fcc50f7eb.
* Online lateral lag learning (#34974)
This reverts commit b4cc9e68d1.
* pad to the best size for fft
* Fix static analysis
* Add typing
* Fix typing
* MAX_LAG
* Calculate cross correlation regardless if the points are valid
* Back to lagd
* Add lagd to process_config
* Lagd in test onroad
* Move lag estimator for lagd
* Remove duplicate entry from test_onroad
* Update process replay
* pre-fill the data
* Update cpu usage
* 25sec window
* Change the meaning of lateralDelayEstimate
* No newline
* Fix typing
* Prefill
* Update ref commit
* Add a unit test
* Fix static issues
* Time limit
* Or timeout
* Use mocker
* Update estimate every time
* empty test
* DT const
* enable RIVIAN again
* Update ref commit
* Update that again
* Improve the tests
* Fix static
* Add masking test
* Increase timeout
* Add liveDelay to selfdrived
* Add liveDelay to selfdrived in process_replay
* Fix block_avg restore after num_blocks
* regen most
* Update bolt
* Update ref commit
* Change the key name
* Add assert
* True weighted average
* Add volt and bolt param migration
* Remove mazda due to invalid sensor timings
* Fix the import
* Add mazda to excluded
* Bring back mazda, but add todo
* New segment for TOYOTA3
* Fix
* Update ref commit
* LiveParametersV2 key
* Param key
* Fix tests
* Remove old params if error
* Update exception message
* Update the test
* Add test for corrupted byte format in v1
* Rename params_reader => params
* Add struct and services
* Proof of concept
* Use vego
* Process replay support
* Fix issues
* Max not min
* Remove print
* Make lag positive
* Points and updates
* Sliding cross corr
* Stuff
* Remove redundant param
* Move to lagd
* Update alert
* Something that works
* Report isEstimated
* Corr field
* Use skimage masked corr
* Fixes
* Move to lat_accel_loc
* Use the delay it in the model
* Mark as executable
* Add 0.2 to initial
* add install line
* Back to 5m window
* Move the import up
* corr window 120
* Show is estimated
* Sort messages
* New impl
* Fix
* Params
* Set initial_lag elsewhere
* Add param
* Rename Param
* Fix type isues
* More blocks
* Masked fft NCC implementation
* Remove package installation
* Use 20hz data and interp the correlation peak
* Move ncc code to separate function
* steering_saturated support
* Constants
* Add recovery buffer
* Fix static
* min_valid_block_count nad liveDelay
* lateralDelayEstimate
* Fix comm issues. Do estimations at 4hz
* Fix
* Display the estimate
* Increase the block size
* Cache every minute
* DEBUG flag
* Add progress to the alert
* Fix crash
* points only in debug
* Fix BlockAverage restoration
* Comment
* Move estimators into estimator directory
* Remove lagd
* Feed only relevant messages
* Rewrite as a set literal
* np.diag with P_initial
* Fix static
* Struct renames
* Update ref commit
* Make it nicer
* Some renames
* Refactor ParamsLearner
* Make it VehicleParamsLearner
* Fix
* Use capnp serialization instead of json
* Fix speed
* Remove redundant comments
* Monitor observed_roll
* Just use init_state
* Comment
* Improve reset
* Set globals api
* Typing for return value
* Redo reset messaging
* Remove usages of math
* Fix process_replay custom_params
* Type ignores for rednose fields
* Remove import
* Reset previous values too
* Update ref_commit
* Revert it
* Bring it back
* Remove more
* Add migration for cached params
* reset curvature while disabled
* comment
* duplicate line
* fix possible iso violation because it was unlimited while disengaged
* rename so you can't accidentally use
* update refs
* Update max_lat_accel.py
The error you're encountering is due to the fact that the code is trying to calculate the 90th percentile of lateral acceleration values that are less than 0, but there are no such values in the dataset. This results in an empty list, which causes the np.percentile function to fail with an IndexError
* fix
* simpler
---------
Co-authored-by: Shane Smiskol <shane@smiskol.com>
Harald Schäfer