Skip to content

Expose expected minimum in result response #26

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
langdal merged 4 commits into from
Sep 23, 2021
Merged

Expose expected minimum in result response #26

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
3fc295a
Expose expected minimum in result response
langdal Sep 22, 2021
54fb0d5
Fix typo
langdal Sep 22, 2021
7d744ad
Merge branch 'main' into feature/add-expected_minimum-to-response
langdal Sep 22, 2021
a319202
Round expected minimum
langdal Sep 22, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 6 additions & 0 deletions optimizerapi/openapi/specification.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -102,6 +102,12 @@ components:
result:
type: object
properties:
expected_minimum:
type: array
items:
type: array
items:
type: number
pickled:
type: string
next:
Expand Down
9 changes: 6 additions & 3 deletions optimizerapi/optimizer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -135,14 +135,17 @@ def processResult(result, optimizer, dimensions, cfg, extras, data, space):
resultDetails["next"] = round_to_length_scales(next_exp, optimizer.space)

if len(data) >= cfg["initialPoints"]:
# Plotting is only possible if the model has
# processed more that "initialPoints" data points
# Some calculations are only possible if the model has
# processed more than "initialPoints" data points
min = expected_minimum(result)
resultDetails["expected_minimum"] = [round_to_length_scales(min[0], optimizer.space), round(min[1], 2)]

plot_convergence(result)
addPlot(plots, "convergence")

plot_objective(result, dimensions=dimensions, usepartialdependence=False)
addPlot(plots, "objective")

resultDetails["pickled"] = securepickle.pickleToString(result, securepickle.get_crypto())

addVersionInfo(resultDetails["extras"])
Expand Down