Support user-defined plotly figures

optuna_dashboard/__init__.py

@@ -1,5 +1,6 @@
 from ._app import run_server  # noqa
 from ._app import wsgi  # noqa
+from ._custom_plot_data import save_plotly_graph_object  # noqa
 from ._form_widget import ChoiceWidget  # noqa
 from ._form_widget import dict_to_form_widget  # noqa
 from ._form_widget import ObjectiveChoiceWidget  # noqa

optuna_dashboard/_app.py

@@ -25,6 +25,7 @@ from . import _note as note
 from ._bottle_util import BottleViewReturn
 from ._bottle_util import json_api_view
 from ._cached_extra_study_property import get_cached_extra_study_property
+from ._custom_plot_data import get_plotly_graph_objects
 from ._importance import get_param_importance_from_trials_cache
 from ._pareto_front import get_pareto_front_trials
 from ._preferential_history import NewHistory
@@ -214,6 +215,8 @@ def create_app(
             union_user_attrs,
             has_intermediate_values,
         ) = get_cached_extra_study_property(study_id, trials)
+
+        plotly_graph_objects = get_plotly_graph_objects(system_attrs)
         return serialize_study_detail(
             summary,
             best_trials,
@@ -222,6 +225,7 @@ def create_app(
             union,
             union_user_attrs,
             has_intermediate_values,
+            plotly_graph_objects,
         )
 
     @app.get("/api/studies/<study_id:int>/param_importances")

optuna_dashboard/_custom_plot_data.py

@@ -0,0 +1,115 @@
+from __future__ import annotations
+
+import math
+from typing import TYPE_CHECKING
+import uuid
+
+from optuna import Study
+
+
+if TYPE_CHECKING:
+    from typing import Any
+
+    from optuna.storages import BaseStorage
+    import plotly.graph_objs as go
+
+
+SYSTEM_ATTR_PLOT_DATA = "dashboard:plot_data:"
+SYSTEM_ATTR_MAX_LENGTH = 2045
+
+
+def save_plotly_graph_object(
+    study: Study, figure: go.Figure, *, graph_object_id: str | None = None
+) -> str:
+    """Save the user-defined plotly's graph object to the study.
+
+    Example:
+
+       .. code-block:: python
+
+          import optuna
+          from optuna_dashboard import save_plotly_graph_object
+
+          def objective(trial):
+              x = trial.suggest_float("x", -100, 100)
+              y = trial.suggest_categorical("y", [-1, 0, 1])
+              return x**2 + y
+
+          study = optuna.create_study()
+          study.optimize(objective, n_trials=100)
+
+          figure = optuna.visualization.plot_optimization_history(study)
+          save_plotly_graph_object(study, figure)
+
+    Args:
+        study:
+            Target study object.
+        plot_data:
+            The plotly's graph object to save.
+        graph_object_id:
+            Unique identifier of the graph object. If specified, the graph object is overwritten.
+
+    Returns:
+        The graph object ID.
+    """
+    storage = study._storage
+    study_id = study._study_id
+
+    graph_object_id = graph_object_id or str(uuid.uuid4())
+    key = SYSTEM_ATTR_PLOT_DATA + graph_object_id + ":"
+    plot_data_json_str = figure.to_json()
+    save_graph_object_json(storage, study_id, key, plot_data_json_str)
+    return graph_object_id
+
+
+def save_graph_object_json(
+    storage: BaseStorage, study_id: int, key_prefix: str, plot_data_json_str: str
+) -> None:
+    plot_data_system_attrs = split_plot_data(plot_data_json_str, key_prefix)
+    for k, v in plot_data_system_attrs.items():
+        storage.set_study_system_attr(study_id, k, v)
+
+    # Clear previous graph object attributes
+    study_system_attrs = storage.get_study_system_attrs(study_id)
+    all_plot_data_system_attrs = [k for k in study_system_attrs if k.startswith(key_prefix)]
+    if len(all_plot_data_system_attrs) > len(plot_data_system_attrs):
+        for i in range(len(plot_data_system_attrs), len(all_plot_data_system_attrs)):
+            storage.set_study_system_attr(study_id, f"{key_prefix}{i}", "")
+
+
+def list_graph_object_ids(system_attrs: dict[str, Any]) -> list[str]:
+    titles = set()
+    for key in system_attrs:
+        if not key.startswith(SYSTEM_ATTR_PLOT_DATA):
+            continue
+
+        s = key.split(":", maxsplit=2)  # e.g. ["dashboard", "plot_data", "Optimization History:1"]
+        if len(s) != 3:
+            continue
+        # Please note that title may contain ":".
+        title = s[2].rsplit(":", maxsplit=1)[0]
+        titles.add(title)
+    return list(titles)
+
+
+def get_plotly_graph_objects(system_attrs: dict[str, Any]) -> dict[str, str]:
+    graph_objects = {}
+    for title in list_graph_object_ids(system_attrs):
+        key_prefix = SYSTEM_ATTR_PLOT_DATA + title + ":"
+        plot_data_attrs = {k: v for k, v in system_attrs.items() if k.startswith(key_prefix)}
+        graph_objects[title] = concat_plot_data(plot_data_attrs, key_prefix)
+    return graph_objects
+
+
+def split_plot_data(plot_data_str: str, key_prefix: str) -> dict[str, str]:
+    plot_data_len = len(plot_data_str)
+    attrs = {}
+    for i in range(math.ceil(plot_data_len / SYSTEM_ATTR_MAX_LENGTH)):
+        start = i * SYSTEM_ATTR_MAX_LENGTH
+        end = min((i + 1) * SYSTEM_ATTR_MAX_LENGTH, plot_data_len)
+        attrs[f"{key_prefix}{i}"] = plot_data_str[start:end]
+    return attrs
+
+
+def concat_plot_data(plot_data_attrs: dict[str, str], key_prefix: str) -> str:
+    return "".join(plot_data_attrs[f"{key_prefix}{i}"] for i in range(len(plot_data_attrs)))

optuna_dashboard/_serializer.py

@@ -132,6 +132,7 @@ def serialize_study_detail(
     union: list[tuple[str, BaseDistribution]],
     union_user_attrs: list[tuple[str, bool]],
     has_intermediate_values: bool,
+    plotly_graph_objects: dict[str, str],
 ) -> dict[str, Any]:
     serialized: dict[str, Any] = {
         "name": summary.study_name,
@@ -162,6 +163,10 @@ def serialize_study_detail(
         serialized["form_widgets"] = form_widgets
     if serialized["is_preferential"]:
         serialized["preference_history"] = serialize_preference_history(system_attrs)
+    serialized["plotly_graph_objects"] = [
+        {"id": id_, "graph_object": graph_object}
+        for id_, graph_object in plotly_graph_objects.items()
+    ]
     return serialized
 
 

optuna_dashboard/ts/apiClient.ts

@@ -93,6 +93,7 @@ interface StudyDetailResponse {
   objective_names?: string[]
   form_widgets?: FormWidgets
   preference_history?: PreferenceHistoryResponce[]
+  plotly_graph_objects: PlotlyGraphObject[]
 }
 
 export const getStudyDetailAPI = (
@@ -131,6 +132,7 @@ export const getStudyDetailAPI = (
         preference_history: res.data.preference_history?.map(
           convertPreferenceHistory
         ),
+        plotly_graph_objects: res.data.plotly_graph_objects,
       }
     })
 }

optuna_dashboard/ts/components/StudyHistory.tsx

@@ -15,6 +15,7 @@ import { GraphIntermediateValues } from "./GraphIntermediateValues"
 import Grid2 from "@mui/material/Unstable_Grid2"
 import { DataGrid, DataGridColumn } from "./DataGrid"
 import { GraphHyperparameterImportance } from "./GraphHyperparameterImportances"
+import { UserDefinedPlot } from "./UserDefinedPlot"
 import { BestTrialsCard } from "./BestTrialsCard"
 import {
   useStudyDetailValue,
@@ -102,6 +103,17 @@ export const StudyHistory: FC<{ studyId: number }> = ({ studyId }) => {
           />
         </CardContent>
       </Card>
+      {studyDetail !== null &&
+        studyDetail.plotly_graph_objects.map((go) => (
+          <Card
+            key={go.id}
+            sx={{
+              margin: theme.spacing(2),
+            }}
+          >
+            <UserDefinedPlot graphObject={go} />
+          </Card>
+        ))}
       <Grid2 container spacing={2} sx={{ padding: theme.spacing(0, 2) }}>
         {studyDetail !== null &&
         studyDetail.directions.length == 1 &&

optuna_dashboard/ts/components/UserDefinedPlot.tsx

@@ -0,0 +1,16 @@
+import * as plotly from "plotly.js-dist-min"
+import React, { FC, useEffect } from "react"
+import { Box } from "@mui/material"
+
+export const UserDefinedPlot: FC<{
+  graphObject: PlotlyGraphObject
+}> = ({ graphObject }) => {
+  const plotDomId = `user-defined-plot:${graphObject.id}`
+
+  useEffect(() => {
+    const parsed = JSON.parse(graphObject.graph_object)
+    plotly.react(plotDomId, parsed.data, parsed.layout)
+  }, [graphObject])
+
+  return <Box id={plotDomId} sx={{ height: "450px" }} />
+}

optuna_dashboard/ts/types/index.d.ts

@@ -182,6 +182,11 @@ type FormWidgets =
       widgets: UserAttrFormWidget[]
     }
 
+type PlotlyGraphObject = {
+  id: string
+  graph_object: string
+}
+
 type StudyDetail = {
   id: number
   name: string
@@ -199,6 +204,7 @@ type StudyDetail = {
   objective_names?: string[]
   form_widgets?: FormWidgets
   preference_history?: PreferenceHistory[]
+  plotly_graph_objects: PlotlyGraphObject[]
 }
 
 type StudyDetails = {

pyproject.toml

@@ -43,6 +43,7 @@ docs = [
 
 test = [
     "coverage",
+    "plotly",
     "pytest",
     "moto[s3]",
 ]

python_tests/test_custom_plot_data.py

@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+from unittest.mock import patch
+
+import optuna
+from optuna_dashboard import _custom_plot_data as custom_plot_data
+from optuna_dashboard import save_plotly_graph_object
+
+
+def get_dummy_study() -> optuna.Study:
+    def objective(trial: optuna.Trial) -> float:
+        x = trial.suggest_float("x", -100, 100)
+        y = trial.suggest_categorical("y", [-1, 0, 1])
+        return x**2 + y
+
+    study = optuna.create_study()
+    optuna.logging.set_verbosity(optuna.logging.ERROR)
+    study.optimize(objective, n_trials=100)
+    return study
+
+
+def test_save_plotly_graph_object() -> None:
+    # Save history plot
+    dummy_study = get_dummy_study()
+    plot_data = optuna.visualization.plot_optimization_history(dummy_study)
+    graph_object_id = save_plotly_graph_object(dummy_study, plot_data)
+
+    study_system_attrs = dummy_study._storage.get_study_system_attrs(dummy_study._study_id)
+    plot_data_dict = custom_plot_data.get_plotly_graph_objects(study_system_attrs)
+    assert len(plot_data_dict) == 1
+    assert plot_data_dict[graph_object_id] == plot_data.to_json()
+
+    # Save parallel coordinate plot
+    plot_data = optuna.visualization.plot_parallel_coordinate(dummy_study)
+    graph_object_id = save_plotly_graph_object(dummy_study, plot_data)
+
+    study_system_attrs = dummy_study._storage.get_study_system_attrs(dummy_study._study_id)
+    plot_data_dict = custom_plot_data.get_plotly_graph_objects(study_system_attrs)
+    assert len(plot_data_dict) == 2
+    assert plot_data_dict[graph_object_id] == plot_data.to_json()
+
+
+def test_update_plotly_graph_object() -> None:
+    # Save history plot
+    dummy_study = get_dummy_study()
+    plot_data = optuna.visualization.plot_optimization_history(dummy_study)
+    graph_object_id = save_plotly_graph_object(dummy_study, plot_data)
+
+    study_system_attrs = dummy_study._storage.get_study_system_attrs(dummy_study._study_id)
+    plot_data_dict = custom_plot_data.get_plotly_graph_objects(study_system_attrs)
+    assert len(plot_data_dict) == 1
+    assert plot_data_dict[graph_object_id] == plot_data.to_json()
+
+    # Save parallel coordinate plot
+    plot_data = optuna.visualization.plot_parallel_coordinate(dummy_study)
+    graph_object_id = save_plotly_graph_object(
+        dummy_study, plot_data, graph_object_id=graph_object_id
+    )
+
+    study_system_attrs = dummy_study._storage.get_study_system_attrs(dummy_study._study_id)
+    plot_data_dict = custom_plot_data.get_plotly_graph_objects(study_system_attrs)
+    assert len(plot_data_dict) == 1
+    assert plot_data_dict[graph_object_id] == plot_data.to_json()

python_tests/test_serializers.py

@@ -29,7 +29,7 @@ def test_get_study_detail_is_preferential() -> None:
     assert len(study_summaries) == 1
 
     study_summary = study_summaries[0]
-    study_detail = serialize_study_detail(study_summary, [], study.trials, [], [], [], False)
+    study_detail = serialize_study_detail(study_summary, [], study.trials, [], [], [], False, {})
     assert study_detail["is_preferential"]
 
 
@@ -40,7 +40,7 @@ def test_get_study_detail_is_not_preferential() -> None:
     assert len(study_summaries) == 1
 
     study_summary = study_summaries[0]
-    study_detail = serialize_study_detail(study_summary, [], study.trials, [], [], [], False)
+    study_detail = serialize_study_detail(study_summary, [], study.trials, [], [], [], False, {})
     assert not study_detail["is_preferential"]