拆分SPC直方图和正态曲线页面

spc-vue/README.md

@@ -16,11 +16,13 @@ npm run dev
 
 - `/overview`：SPC 总览和关键指标
 - `/run-chart`：基本趋势图，显示原始序列、均值线、中位线、规格限和移动平均线
+- `/histogram`：频数直方图，只显示分箱频数和规格限，不叠加正态曲线
+- `/normal-curve`：正态曲线，单独显示拟合分布和规格限
 - `/xbar-r`：Xbar 控制图，控制限来自 XR 结果
 - `/r-chart`：R 极差控制图
 - `/xbar-s`：Xbar 控制图，控制限来自 XS 结果
 - `/s-chart`：S 标准差控制图
-- `/cpk`：过程能力与直方图
+- `/cpk`：过程能力指标
 
 ## 接口校验重点
 

spc-vue/src/router.ts

@@ -6,11 +6,15 @@ import XBarSView from "./views/XBarSView.vue";
 import SChartView from "./views/SChartView.vue";
 import CpkView from "./views/CpkView.vue";
 import RunChartView from "./views/RunChartView.vue";
+import HistogramView from "./views/HistogramView.vue";
+import NormalCurveView from "./views/NormalCurveView.vue";
 
 export const routes = [
   { path: "/", redirect: "/overview" },
   { path: "/overview", component: OverviewView, meta: { title: "总览" } },
   { path: "/run-chart", component: RunChartView, meta: { title: "趋势图" } },
+  { path: "/histogram", component: HistogramView, meta: { title: "直方图" } },
+  { path: "/normal-curve", component: NormalCurveView, meta: { title: "正态曲线" } },
   { path: "/xbar-r", component: XBarRView, meta: { title: "Xbar-R" } },
   { path: "/r-chart", component: RChartView, meta: { title: "R 图" } },
   { path: "/xbar-s", component: XBarSView, meta: { title: "Xbar-S" } },

spc-vue/src/utils/chartOptions.ts

@@ -287,12 +287,12 @@ export function createCapabilityBarOption(cpk: CpkResult): EChartsOption {
   };
 }
 
-// 创建直方图和正态曲线配置，用来核对分布和规格限位置。
-export function createHistogramOption(cpk: CpkResult): EChartsOption {
+// 创建单独直方图配置，只展示频数分布和规格限，不叠加正态曲线。
+export function createFrequencyHistogramOption(cpk: CpkResult): EChartsOption {
   const xRange = calculateHistogramXAxisRange(cpk);
 
   return {
-    color: ["#0f766e", "#b45309"],
+    color: ["#0f766e"],
     tooltip: { trigger: "axis" },
     legend: { top: 0, right: 0 },
     grid: { left: 52, right: 48, top: 46, bottom: 42 },
@@ -303,44 +303,73 @@ export function createHistogramOption(cpk: CpkResult): EChartsOption {
       max: xRange.max,
       axisLabel: { color: "#667085" }
     },
-    yAxis: [
-      {
+    yAxis: {
       type: "value",
       name: "频数",
+      minInterval: 1,
       axisLabel: { color: "#667085" },
       splitLine: { lineStyle: { color: "#e5e7eb" } }
     },
-      {
-        type: "value",
-        name: "正态曲线",
-        axisLabel: { color: "#667085" },
-        splitLine: { show: false }
-      }
-    ],
     series: [
       {
         name: "频数",
         type: "bar",
         data: cpk.Xk.map((value, index) => [value, cpk.YkCount[index]]),
-        barMaxWidth: 28,
+        barMaxWidth: 34,
         markLine: {
           symbol: "none",
           data: [
             { xAxis: cpk.LSL, name: "LSL" },
             { xAxis: cpk.USL, name: "USL" },
-            { xAxis: cpk.SL, name: "SL" }
+            { xAxis: cpk.SL, name: "目标值" }
+          ],
+          label: { color: "#667085" },
+          lineStyle: { color: "#991b1b", type: "dashed" }
+        }
+      }
+    ]
+  };
+}
+
+// 创建正态曲线配置，单独查看拟合曲线与规格限关系。
+export function createNormalCurveOption(cpk: CpkResult): EChartsOption {
+  const xRange = calculateHistogramXAxisRange(cpk);
+
+  return {
+    color: ["#b45309"],
+    tooltip: { trigger: "axis" },
+    legend: { top: 0, right: 0 },
+    grid: { left: 52, right: 48, top: 46, bottom: 42 },
+    xAxis: {
+      type: "value",
+      name: "测量值",
+      min: xRange.min,
+      max: xRange.max,
+      axisLabel: { color: "#667085" }
+    },
+    yAxis: {
+      type: "value",
+      name: "概率密度",
+      axisLabel: { color: "#667085" },
+      splitLine: { lineStyle: { color: "#e5e7eb" } }
+    },
+    series: [
+      {
+        name: "正态曲线",
+        type: "line",
+        smooth: true,
+        symbolSize: 4,
+        data: cpk.NormalDistributionX.map((value, index) => [value, cpk.NormalDistributionY[index]]),
+        markLine: {
+          symbol: "none",
+          data: [
+            { xAxis: cpk.LSL, name: "LSL" },
+            { xAxis: cpk.USL, name: "USL" },
+            { xAxis: cpk.SL, name: "目标值" }
           ],
           label: { color: "#667085" },
           lineStyle: { color: "#991b1b", type: "dashed" }
         }
-      },
-      {
-        name: "正态曲线",
-        type: "line",
-        yAxisIndex: 1,
-        smooth: true,
-        symbolSize: 4,
-        data: cpk.NormalDistributionX.map((value, index) => [value, cpk.NormalDistributionY[index]])
       }
     ]
   };

spc-vue/src/views/CpkView.vue

@@ -3,7 +3,7 @@ import { computed } from "vue";
 import EChartPanel from "../components/EChartPanel.vue";
 import MetricStrip from "../components/MetricStrip.vue";
 import { useSpc } from "../composables/useSpc";
-import { createCapabilityBarOption, createHistogramOption } from "../utils/chartOptions";
+import { createCapabilityBarOption } from "../utils/chartOptions";
 
 const { result } = useSpc();
 
@@ -21,25 +21,16 @@ const metrics = computed(() => {
 });
 
 const capabilityOption = computed(() => (result.value?.Cpk ? createCapabilityBarOption(result.value.Cpk) : null));
-const histogramOption = computed(() => (result.value?.Cpk ? createHistogramOption(result.value.Cpk) : null));
 </script>
 
 <template>
   <article class="page-stack">
     <MetricStrip v-if="metrics.length" :metrics="metrics" />
-    <div class="two-column">
     <EChartPanel
       title="过程能力指标"
       eyebrow="Capability"
-        description="能力柱状图用于快速比较 Cp、Cpk、Pp、Ppk。页面保留 1.00 与 1.33 参考线，方便验证常见能力门槛。"
+      description="能力柱状图用于快速比较 Cp、Cpk、Pp、Ppk。页面保留 1.00 与 1.33 参考线，方便验证常见能力门槛；分布形态请在直方图和正态曲线页面单独查看。"
       :option="capabilityOption"
     />
-      <EChartPanel
-        title="直方图与正态曲线"
-        eyebrow="Distribution"
-        description="直方图展示测量值分布，并叠加正态曲线和规格限，便于判断能力指标是否被偏态或边界数据影响。"
-        :option="histogramOption"
-      />
-    </div>
   </article>
 </template>

spc-vue/src/views/HistogramView.vue

@@ -0,0 +1,38 @@
+<script setup lang="ts">
+import { computed } from "vue";
+import EChartPanel from "../components/EChartPanel.vue";
+import MetricStrip from "../components/MetricStrip.vue";
+import { useSpc } from "../composables/useSpc";
+import { createFrequencyHistogramOption } from "../utils/chartOptions";
+
+const { result } = useSpc();
+
+const option = computed(() => (result.value?.Cpk ? createFrequencyHistogramOption(result.value.Cpk) : null));
+
+const metrics = computed(() => {
+  const cpk = result.value?.Cpk;
+  if (!cpk) return [];
+  const maxCount = Math.max(...cpk.YkCount);
+
+  return [
+    { label: "分箱数", value: cpk.GroupCount },
+    { label: "组距", value: cpk.GroupWidth },
+    { label: "最大频数", value: maxCount },
+    { label: "最小值", value: cpk.ValueMin },
+    { label: "最大值", value: cpk.ValueMax },
+    { label: "规格限", value: `${cpk.LSL} ~ ${cpk.USL}` }
+  ];
+});
+</script>
+
+<template>
+  <article class="page-stack">
+    <MetricStrip v-if="metrics.length" :metrics="metrics" />
+    <EChartPanel
+      title="频数直方图"
+      eyebrow="Histogram"
+      description="直方图只展示各测量区间的频数分布，并标出规格限和目标值。它适合先观察真实分布形态、偏态、双峰、离群区间以及数据是否靠近规格边界。"
+      :option="option"
+    />
+  </article>
+</template>

spc-vue/src/views/NormalCurveView.vue

@@ -0,0 +1,37 @@
+<script setup lang="ts">
+import { computed } from "vue";
+import EChartPanel from "../components/EChartPanel.vue";
+import MetricStrip from "../components/MetricStrip.vue";
+import { useSpc } from "../composables/useSpc";
+import { createNormalCurveOption } from "../utils/chartOptions";
+
+const { result } = useSpc();
+
+const option = computed(() => (result.value?.Cpk ? createNormalCurveOption(result.value.Cpk) : null));
+
+const metrics = computed(() => {
+  const cpk = result.value?.Cpk;
+  if (!cpk) return [];
+
+  return [
+    { label: "Sigma", value: cpk.Singma },
+    { label: "SigmaS", value: cpk.SingmaS },
+    { label: "Ca", value: cpk.Ca },
+    { label: "SL", value: cpk.SL },
+    { label: "USL", value: cpk.USL },
+    { label: "LSL", value: cpk.LSL }
+  ];
+});
+</script>
+
+<template>
+  <article class="page-stack">
+    <MetricStrip v-if="metrics.length" :metrics="metrics" />
+    <EChartPanel
+      title="正态曲线"
+      eyebrow="Normal Curve"
+      description="正态曲线单独展示当前 SPC 结果中的拟合分布，并标出规格限和目标值。它用于辅助判断能力指标解释是否依赖正态分布假设。"
+      :option="option"
+    />
+  </article>
+</template>