New dial_dataclass that allows for heteroscedastic noise and multiple outputs#36
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add statistics_y to encode the output and error model
- prepare the new way how to set yerr through statistics_y - unify and fix the output scaling
- fix gpax stddev, untested
- manual_client: adapt to new payload structure - sinusoidal_growth_client: handle std.dev. vs variance and configure length_scale
- there appears to be an interaction between pydantic validation and type comparisons that makes them not be stable. Use a str with name instead.
- test with different backend and tweak hyperparameters
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Everything else apart from the Distribution classes looks fine to me, and tests + the scripts seemed to run fine for me locally. If you think my suggested fix looks correct then I can probably apply the changes and immediately rebase the changes myself.
Signed-off-by: Lance-Drane <Lance-Drane@users.noreply.github.com>
Signed-off-by: Lance-Drane <Lance-Drane@users.noreply.github.com>
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OK, synchronized I'm getting a few errors from the various scripts, but the unit tests run fine; if we can figure out why these aren't working, we should go ahead and merge. I think all of these might be related to an inconsistent 1d_sable_client1d_sinusoidal_growth_client2d_rosenbrock_client(this error happens several times for some reason) |
I can not reproduce any of the errors above with your recent changes. The "user's callback function" seems to indicate that they are happening on the client side. For 1d_sable_client it is probably a ".reshape((self.meshgrid_size,)" in handle_surrogate_values, for 1d_sinusoidal_growth_client it is probably the same place. That would indicate that one of these |
- clean up return values, now that the distinction between stddevs, and transformed stddevs is no longer necesssary
- fix sign mistake in EI and UncertaintyBound
- increase number of greedy restarts for get_next_point, and add debug
- test using different acquisition strategies for rosenbrock in different iterations
- if the repeat arguments bounds, y_is_good, extra_args are not None, they will replace the stored values in the initial workflow initialization
Lance-Drane
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LGTM, I'm not getting the errors any more
Adds the following features:
Fixes the following bugs: