Move PlotEdf to tslib/react

2026-09-09 11:28:14 +08:00 · 2024-06-12 17:28:54 +09:00
parent a5c633a37b
commit 92c32d877e
1 changed files with 124 additions and 0 deletions
@@ -0,0 +1,124 @@
+import { Box, Typography, useTheme } from "@mui/material"
+import * as Optuna from "@optuna/types"
+import * as plotly from "plotly.js-dist-min"
+import { FC, useEffect, useMemo } from "react"
+import { useGraphComponentState } from "../hooks/useGraphComponentState"
+import { Target, useFilteredTrialsFromStudies } from "../utils/trialFilter"
+import { GraphContainer } from "./GraphContainer"
+import { plotlyDarkTemplate } from "./PlotlyDarkMode"
+
+export type EdfPlotInfo = {
+  study_name: string
+  trials: Optuna.Trial[]
+}
+
+export const getPlotDomId = (objectiveId: number) => `graph-edf-${objectiveId}`
+
+export const PlotEdf: FC<{
+  studies: Optuna.Study[]
+  objectiveId: number
+}> = ({ studies, objectiveId }) => {
+  const { graphComponentState, notifyGraphDidRender } = useGraphComponentState()
+
+  const theme = useTheme()
+
+  const domId = getPlotDomId(objectiveId)
+  const target = useMemo<Target>(
+    () => new Target("objective", objectiveId),
+    [objectiveId]
+  )
+  const trials = useFilteredTrialsFromStudies(studies, [target], false)
+  const edfPlotInfos = studies.map((study, index) => {
+    const e: EdfPlotInfo = {
+      study_name: study?.name,
+      trials: trials[index],
+    }
+    return e
+  })
+
+  // biome-ignore lint/correctness/useExhaustiveDependencies: <explanation>
+  useEffect(() => {
+    if (graphComponentState !== "componentWillMount") {
+      plotEdf(edfPlotInfos, target, domId, theme.palette.mode)?.then(
+        notifyGraphDidRender
+      )
+    }
+  }, [studies, target, theme.palette.mode, graphComponentState])
+
+  return (
+    <Box component="div">
+      <Typography
+        variant="h6"
+        sx={{ margin: "1em 0", fontWeight: theme.typography.fontWeightBold }}
+      >
+        {`EDF for ${target.toLabel(studies[0].metric_names)}`}
+      </Typography>
+      <GraphContainer
+        plotDomId={domId}
+        graphComponentState={graphComponentState}
+      />
+    </Box>
+  )
+}
+
+const plotEdf = (
+  edfPlotInfos: EdfPlotInfo[],
+  target: Target,
+  domId: string,
+  mode: string
+) => {
+  if (document.getElementById(domId) === null) {
+    return
+  }
+  if (edfPlotInfos.length === 0) {
+    return plotly.react(domId, [], {
+      template: mode === "dark" ? plotlyDarkTemplate : {},
+    })
+  }
+
+  const target_name = "Objective Value"
+  const layout: Partial<plotly.Layout> = {
+    xaxis: {
+      title: target_name,
+    },
+    yaxis: {
+      title: "Cumulative Probability",
+    },
+    margin: {
+      l: 50,
+      t: 0,
+      r: 50,
+      b: 50,
+    },
+    template: mode === "dark" ? plotlyDarkTemplate : {},
+    legend: {
+      x: 1.0,
+      y: 0.95,
+    },
+  }
+
+  const plotData: Partial<plotly.PlotData>[] = edfPlotInfos.map((h) => {
+    const values = h.trials.map((t) => target.getTargetValue(t) as number)
+    const numValues = values.length
+    const minX = Math.min(...values)
+    const maxX = Math.max(...values)
+    const numStep = 100
+    const _step = (maxX - minX) / (numStep - 1)
+
+    const xValues = []
+    const yValues = []
+    for (let i = 0; i < numStep; i++) {
+      const boundary_right = minX + _step * i
+      xValues.push(boundary_right)
+      yValues.push(values.filter((v) => v <= boundary_right).length / numValues)
+    }
+
+    return {
+      type: "scatter",
+      name: `${h.study_name}`,
+      x: xValues,
+      y: yValues,
+    }
+  })
+  return plotly.react(domId, plotData, layout)
+}