新增.hintrc配置文件，更新多个h5ad文件的大小和哈希值，修改FakeEmbryo.py中的细胞层参数，调整前端页面中细胞位置和大小的计算，优化TemporalAnalysis.tsx中的数据连接逻辑以确保细胞类型流动的平衡性。

.hintrc

@@ -0,0 +1,8 @@
+{
+  "extends": [
+    "development"
+  ],
+  "hints": {
+    "no-inline-styles": "off"
+  }
+}

embryo-backend/Data/FakeEmbryo.py

@@ -6,12 +6,12 @@ import os
 np.random.seed(42)
 
 # 参数配置
-stages = [("CS7", 500), ("CS8", 1000), ("CS9", 1500)]
+stages = [("CS7", 500), ("CS7.5", 750), ("CS8", 1000), ("CS9", 1500)]
 genes = ["SOX2", "NANOG", "T", "POU5F1", "OTX2", "ZIC2", "FOXA2", "LEFTY1"]
 layers = {
-    "Ectoderm": 1.0,     # 外层
+    "Ectoderm": 0.1,     # 外层
-    "Mesoderm": 0.85,    # 中层
+    "Mesoderm": 0.085,    # 中层
-    "Endoderm": 0.7,     # 内层
+    "Endoderm": 0.07,     # 内层
 }
 notochord_ratio = 0.05  # 脊索/原条占总细胞数的比例
 
@@ -21,17 +21,23 @@ script_path = os.path.dirname(os.path.realpath(__file__))
 for stage, total_cells in stages:
     n_noto = int(total_cells * notochord_ratio)
     n_layer = total_cells - n_noto
-    n_per_layer = n_layer // len(layers)
+    num_layers = len(layers)
+    # 使用 Dirichlet 生成随机且不相等的概率，再用多项分布采样；若计数仍相等则重采样
+    for _ in range(100):
+        probs = np.random.dirichlet(np.ones(num_layers))
+        n_per_layer = np.random.multinomial(n_layer, probs)
+        if len(set(n_per_layer)) == num_layers:
+            break
 
     positions = []
     cell_types = []
     ids = []
 
     # 椭球比例参数
-    a, b, c = 10, 8, 5
+    a, b, c = 1, 0.8, 0.5
 
     for i, (layer_name, scale) in enumerate(layers.items()):
-        N = n_per_layer
+        N = n_per_layer[i]
         phi = np.random.uniform(0, np.pi, N)
         theta = np.random.uniform(0, 2*np.pi, N)
         r = scale  # 层的半径比例
@@ -46,9 +52,9 @@ for stage, total_cells in stages:
             ids.append(f"{stage}_{layer_name}_{len(ids)}")
 
     # 添加脊索/原条样结构（Z轴中间偏下的细胞）
-    x = np.random.normal(0, 0.5, n_noto)
+    x = np.random.normal(0, 0.01, n_noto)
-    y = np.random.normal(0, 0.5, n_noto)
+    y = np.random.normal(0, 0.01, n_noto)
-    z = np.linspace(-3, 3, n_noto)
+    z = np.linspace(-0.1, 0.1, n_noto)
 
     for xi, yi, zi in zip(x, y, z):
         positions.append([xi, yi, zi])

embryo-frontend/src/pages/EmbryoGeneration.tsx

@@ -258,10 +258,10 @@ const UnifiedEmbryoAnimation: React.FC<UnifiedEmbryoAnimationProps> = ({ cs7Data
 
     // 计算所有点的包围盒，自动居中和缩放
     let allPositions: number[] = [];
-    cs7Data.forEach(p => { allPositions.push(p.x - 40, p.y, p.z); });
+    cs7Data.forEach(p => { allPositions.push(p.x - 0.5, p.y, p.z); });
-    cs8Data.forEach(p => { allPositions.push(p.x + 40, p.y, p.z); });
+    cs8Data.forEach(p => { allPositions.push(p.x + 0.5,p.y, p.z); });
     cs75Data.forEach((p, i) => {
-      const fromX = i % 2 === 0 ? p.x - 40 : p.x + 40;
+      const fromX = i % 2 === 0 ? p.x - 0.5 : p.x + 0.5;
       allPositions.push(fromX, p.y, p.z);
       allPositions.push(p.x, p.y, p.z);
     });
@@ -285,7 +285,7 @@ const UnifiedEmbryoAnimation: React.FC<UnifiedEmbryoAnimationProps> = ({ cs7Data
       const positions: number[] = [];
       const colors: number[] = [];
       cs7Data.forEach((p) => {
-        positions.push(p.x - 40, p.y, p.z);
+        positions.push(p.x - 0.5, p.y, p.z);
         const c = colorMap.get(p.value as string) || new THREE.Color('#CCCCCC');
         colors.push(c.r, c.g, c.b);
       });
@@ -293,7 +293,7 @@ const UnifiedEmbryoAnimation: React.FC<UnifiedEmbryoAnimationProps> = ({ cs7Data
       geometry.setAttribute("color", new THREE.Float32BufferAttribute(colors, 3));
       const material = new THREE.PointsMaterial({
         vertexColors: true,
-        size: 0.8,
+        size: 0.4,
         sizeAttenuation: true,
         transparent: true,
         alphaTest: 0.5,
@@ -327,7 +327,7 @@ const UnifiedEmbryoAnimation: React.FC<UnifiedEmbryoAnimationProps> = ({ cs7Data
       const positions: number[] = [];
       const colors: number[] = [];
       cs8Data.forEach((p) => {
-        positions.push(p.x + 40, p.y, p.z);
+        positions.push(p.x + 0.5, p.y, p.z);
         const c = colorMap.get(p.value as string) || new THREE.Color('#CCCCCC');
         colors.push(c.r, c.g, c.b);
       });
@@ -335,7 +335,7 @@ const UnifiedEmbryoAnimation: React.FC<UnifiedEmbryoAnimationProps> = ({ cs7Data
       geometry.setAttribute("color", new THREE.Float32BufferAttribute(colors, 3));
       const material = new THREE.PointsMaterial({
         vertexColors: true,
-        size: 0.8,
+        size: 0.4,
         sizeAttenuation: true,
         transparent: true,
         alphaTest: 0.5,
@@ -408,7 +408,7 @@ const UnifiedEmbryoAnimation: React.FC<UnifiedEmbryoAnimationProps> = ({ cs7Data
           const sourcePoint = cs7PointsOfType.length > 0
             ? cs7PointsOfType[sourceIndex]
             : cs7Data[i % cs7Data.length];
-          fromX = sourcePoint.x - 40;
+          fromX = sourcePoint.x - 0.5;
           fromY = sourcePoint.y;
           fromZ = sourcePoint.z;
         } else {
@@ -418,7 +418,7 @@ const UnifiedEmbryoAnimation: React.FC<UnifiedEmbryoAnimationProps> = ({ cs7Data
           const sourcePoint = cs8PointsOfType.length > 0
             ? cs8PointsOfType[sourceIndex]
             : cs8Data[i % cs8Data.length];
-          fromX = sourcePoint.x + 40;
+            fromX = sourcePoint.x + 0.5;
           fromY = sourcePoint.y;
           fromZ = sourcePoint.z;
         }
@@ -466,7 +466,7 @@ const UnifiedEmbryoAnimation: React.FC<UnifiedEmbryoAnimationProps> = ({ cs7Data
           vAlpha = alpha;
           vColor = color;
           gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0);
-          gl_PointSize = 10.0;
+          gl_PointSize = 5.0;
         }
       `;
 

embryo-frontend/src/pages/TemporalAnalysis.tsx

@@ -68,7 +68,7 @@ const TemporalAnalysis: React.FC = () => {
       // 转换数据为线图格式
       const stagesData = response.data.stages_data;
       const allCellTypes = new Set<string>();
-      
+
       // 收集所有细胞类型
       stagesData.forEach((stageData: any) => {
         Object.keys(stageData.cell_types).forEach(cellType => {
@@ -78,7 +78,7 @@ const TemporalAnalysis: React.FC = () => {
 
       const cellTypesArray = Array.from(allCellTypes).sort();
       const colorMap = generateCellTypeColors(cellTypesArray);
-      
+
       // 构建线图数据 - 每个细胞类型一条线
       const lineData = cellTypesArray.map(cellType => {
         const linePoints = stagesData.map((stageData: any) => {
@@ -112,7 +112,7 @@ const TemporalAnalysis: React.FC = () => {
   // 构建桑基图数据
   const buildSankeyData = (dataCS7: any[], dataCS8: any[], dataCS9: any[]) => {
     setSankeyLoading(true);
-    
+
     try {
       // 统计各阶段的细胞类型数量
       const countCellTypes = (data: any[]) => {
@@ -152,7 +152,7 @@ const TemporalAnalysis: React.FC = () => {
       const nodes: any[] = [];
       cellTypeArray.forEach(cellType => {
         const color = colorMap.get(cellType) || '#CCCCCC';
-        
+
         // CS7 节点
         if (countsCS7[cellType]) {
           const percentage = ((countsCS7[cellType] / totalCS7) * 100).toFixed(1);
@@ -184,39 +184,79 @@ const TemporalAnalysis: React.FC = () => {
         }
       });
 
-      // 构建连接
+      // 构建连接：使用最小百分比作为同类连线，并将剩余部分匹配到有缺口的目标细胞类型，保证各阶段总量守恒
-      const links: any[] = [];
+      const buildBalancedLinks = (
-      cellTypeArray.forEach(cellType => {
+        sourceCounts: Record<string, number>,
-        const color = colorMap.get(cellType) || '#CCCCCC';
+        sourceTotal: number,
-        
+        targetCounts: Record<string, number>,
-        // CS7 -> CS8 连接
+        targetTotal: number,
-        if (countsCS7[cellType] && countsCS8[cellType]) {
+        sourceStage: string,
-          const cs7Percentage = (countsCS7[cellType] / totalCS7) * 100;
+        targetStage: string
-          const cs8Percentage = (countsCS8[cellType] / totalCS8) * 100;
+      ) => {
-          const avgPercentage = (cs7Percentage + cs8Percentage) / 2;
+        const types = Array.from(
-          
+          new Set([
-          links.push({
+            ...Object.keys(sourceCounts),
-            source: `CS7_${cellType}`,
+            ...Object.keys(targetCounts)
-            target: `CS8_${cellType}`,
+          ])
-            value: Math.max(avgPercentage, 0.1), // 确保有最小值以显示连接
+        );
-            color: color + '80' // 添加透明度
-          });
-        }
 
-        // CS8 -> CS9 连接
+        const sourcePct: Record<string, number> = {};
-        if (countsCS8[cellType] && countsCS9[cellType]) {
+        const targetPct: Record<string, number> = {};
-          const cs8Percentage = (countsCS8[cellType] / totalCS8) * 100;
+        types.forEach((t) => {
-          const cs9Percentage = (countsCS9[cellType] / totalCS9) * 100;
+          sourcePct[t] = ((sourceCounts[t] || 0) / sourceTotal) * 100;
-          const avgPercentage = (cs8Percentage + cs9Percentage) / 2;
+          targetPct[t] = ((targetCounts[t] || 0) / targetTotal) * 100;
-          
+        });
-          links.push({
+
-            source: `CS8_${cellType}`,
+        const flows: any[] = [];
-            target: `CS9_${cellType}`,
+
-            value: Math.max(avgPercentage, 0.1), // 确保有最小值以显示连接
+        // 同类对齐：取最小值
-            color: color + '80' // 添加透明度
+        const sourceResidual: Record<string, number> = {};
+        const targetResidual: Record<string, number> = {};
+        types.forEach((t) => {
+          const direct = Math.min(sourcePct[t], targetPct[t]);
+          if (direct > 0) {
+            const color = (colorMap.get(t) || '#CCCCCC') + '80';
+            flows.push({
+              source: `${sourceStage}_${t}`,
+              target: `${targetStage}_${t}`,
+              value: direct,
+              color
+            });
+          }
+          sourceResidual[t] = sourcePct[t] - direct; // >= 0
+          targetResidual[t] = targetPct[t] - direct; // >= 0
+        });
+
+        // 将源阶段的剩余按目标阶段的缺口比例分配
+        types.forEach((sType) => {
+          let remaining = sourceResidual[sType];
+          if (remaining <= 0) return;
+          // 计算当前目标缺口总和
+          let totalDeficit = types.reduce((sum, t) => sum + Math.max(targetResidual[t], 0), 0);
+          if (totalDeficit <= 0) return;
+          types.forEach((dType) => {
+            if (targetResidual[dType] <= 0) return;
+            const share = (remaining * targetResidual[dType]) / totalDeficit;
+            if (share > 1e-6) {
+              const color = (colorMap.get(sType) || '#CCCCCC') + '80';
+              flows.push({
+                source: `${sourceStage}_${sType}`,
+                target: `${targetStage}_${dType}`,
+                value: share,
+                color
+              });
+              targetResidual[dType] -= share;
+            }
           });
-        }
+        });
-      });
+
+        return flows;
+      };
+
+      const links: any[] = [
+        ...buildBalancedLinks(countsCS7, totalCS7, countsCS8, totalCS8, 'CS7', 'CS8'),
+        ...buildBalancedLinks(countsCS8, totalCS8, countsCS9, totalCS9, 'CS8', 'CS9')
+      ];
 
       setSankeyData({ nodes, links });
     } catch (error) {
@@ -326,7 +366,7 @@ const TemporalAnalysis: React.FC = () => {
             The three 3D views below show cell type distributions for CS7, CS8, and CS9.
             Compare spatial distributions to observe changes over development.
           </p>
-          
+
           <div
             className="three-column-grid visualization-grid"
             style={{
@@ -425,7 +465,7 @@ const TemporalAnalysis: React.FC = () => {
             The Sankey diagram (left) shows cell type flows across stages; the line chart (right)
             shows the proportion changes of the selected gene across cell types.
           </p>
-          
+
           <div
             style={{
               display: "grid",
@@ -663,4 +703,4 @@ const TemporalAnalysis: React.FC = () => {
   );
 };
 
-export default TemporalAnalysis; 
+export default TemporalAnalysis;

embryo-frontend/tsconfig.json

@@ -6,6 +6,7 @@
     "module": "ESNext",
     "lib": ["ES2022", "DOM", "DOM.Iterable"],
     "skipLibCheck": true,
+    "forceConsistentCasingInFileNames": true,
 
     /* Bundler mode */
     "moduleResolution": "bundler",