备份与迷雾的差异分析、合并执行，附属数据改挂坐标键

备份（.rondbackup）与迷雾（.fwss）各加一层「先看差异再动手」： - 迷雾：上传先出差异页，说清叠加能补多少、整体替换会丢多少，并在真实底图上用绿/灰/红标出会新增 / 不变 / 会丢的区域 - 备份：与当前数据集按 UUID 逐条比对（rond 每次导出都会重排 Z_PK，编号认不出人），新增合入、冲突逐条选、仅站内有逐条勾选删除，全在一个事务里执行；合入的行写回 entity_raw，保证再传同一份备份时差异归零 - 地点按坐标对齐：站点的「补全地址」会把地点改名，拿名称当键会让一整个地点的到访全变成假冲突 - 附属数据（备注/结论/访客票/图片）从 dataset_id+src_pk 换成坐标键，换数据集不再失联；访客票没有 dataset_id，回填按活跃数据集认领 - 修正 contentHash 拿 Z_PK 当指纹的隐患，以及两处「src_pk 跨快照稳定」的错误注释导出格式（.rondbackup / .fwss）保持原样，往返测试通过。
2026-09-19 16:04:00 +08:00
parent 9e01923244
commit 30c502ce7b
43 changed files with 5968 additions and 170 deletions
@@ -0,0 +1,114 @@
+package fog
+
+import (
+	"image"
+	"math"
+	"testing"
+)
+
+func bmOf(cells ...[2]int) []byte {
+	bm := make([]byte, bitmapSize)
+	for _, c := range cells {
+		bm[c[1]*8+c[0]/8] |= 0x80 >> (c[0] % 8)
+	}
+	return bm
+}
+
+func pixAt(img *image.NRGBA, px, py int) [4]byte {
+	i := (py*256 + px) * 4
+	return [4]byte{img.Pix[i], img.Pix[i+1], img.Pix[i+2], img.Pix[i+3]}
+}
+
+// z=18 时一格正好 16 像素，块 (100,200) 完整落在瓦片 (400,800) 里，
+// 格 (col,row) 的中心像素是 (col*16+8, row*16+8)。
+func TestRenderDiffTilePerCell(t *testing.T) {
+	key := [2]int{100, 200}
+	cur := map[[2]int][]byte{key: bmOf([2]int{0, 0}, [2]int{4, 0})}
+	inc := map[[2]int][]byte{key: bmOf([2]int{0, 0}, [2]int{1, 0})}
+	img := RenderDiffTile(cur, inc, 18, 400, 800, "wgs84")
+	if img == nil {
+		t.Fatal("瓦片不该为空")
+	}
+	if got := pixAt(img, 8, 8); got != DiffBothColor {
+		t.Errorf("两边都有的格应为灰色，实际 %v", got)
+	}
+	if got := pixAt(img, 24, 8); got != DiffGainColor {
+		t.Errorf("只有快照有的格应为绿色，实际 %v", got)
+	}
+	if got := pixAt(img, 72, 8); got != DiffLostColor {
+		t.Errorf("只有库里有、整体替换会丢的格应为红色，实际 %v", got)
+	}
+	if got := pixAt(img, 200, 200); got[3] != 0 {
+		t.Errorf("没被探索的格应保持透明，实际 %v", got)
+	}
+}
+
+func TestRenderDiffTileSingleSided(t *testing.T) {
+	key := [2]int{100, 200}
+	onlyCur := RenderDiffTile(map[[2]int][]byte{key: bmOf([2]int{3, 3})}, nil, 18, 400, 800, "wgs84")
+	if got := pixAt(onlyCur, 56, 56); got != DiffLostColor {
+		t.Errorf("快照里完全没有的块应整块为红，实际 %v", got)
+	}
+	onlyInc := RenderDiffTile(nil, map[[2]int][]byte{key: bmOf([2]int{3, 3})}, 18, 400, 800, "wgs84")
+	if got := pixAt(onlyInc, 56, 56); got != DiffGainColor {
+		t.Errorf("库里完全没有的块应整块为绿，实际 %v", got)
+	}
+}
+
+// z=10 时一格不足一像素，块只占 4x4 像素，按块内多数类涂色。
+func TestRenderDiffTileCoarseZoomUsesDominantKind(t *testing.T) {
+	key := [2]int{100, 200}
+	cur := map[[2]int][]byte{key: bmOf([2]int{0, 0})}
+	inc := map[[2]int][]byte{key: bmOf([2]int{1, 1}, [2]int{2, 2}, [2]int{3, 3})}
+	img := RenderDiffTile(cur, inc, 10, 1, 3, "wgs84")
+
+	const step, scale = WorldCells >> 10, 256.0 / (WorldCells >> 10)
+	bx, by := float64(key[0]*BlockCells), float64(key[1]*BlockCells)
+	px := int(math.Floor((bx - 1*step) * scale))
+	py := int(math.Floor((by - 3*step) * scale))
+	if got := pixAt(img, px+1, py+1); got != DiffGainColor {
+		t.Errorf("三格新增、一格不变的块应以绿色为主，实际 %v", got)
+	}
+	if w := int(math.Ceil(float64(BlockCells) * scale)); w != 4 {
+		t.Fatalf("z=10 下块应占 4 像素，实际 %d", w)
+	}
+}
+
+func TestRenderDiffTileEdgeCases(t *testing.T) {
+	if RenderDiffTile(nil, nil, 18, 400, 800, "wgs84") == nil {
+		t.Error("两边都空也应返回一张空瓦片")
+	}
+	if RenderDiffTile(nil, nil, 23, 0, 0, "wgs84") != nil {
+		t.Error("超出缩放范围应返回 nil")
+	}
+}
+
+func TestDominantKind(t *testing.T) {
+	cases := []struct {
+		both, gain, lost int
+		want             uint8
+	}{
+		{0, 0, 0, diffNone},
+		{5, 1, 0, diffBoth},
+		{1, 5, 0, diffGain},
+		{1, 0, 5, diffLost},
+		{2, 2, 0, diffGain}, // 平局让「会新增」胜出
+		{3, 1, 1, diffBoth},
+	}
+	for _, c := range cases {
+		if got := dominantKind(c.both, c.gain, c.lost); got != c.want {
+			t.Errorf("dominantKind(%d,%d,%d)=%d，期望 %d", c.both, c.gain, c.lost, got, c.want)
+		}
+	}
+}
+
+func TestBlockDiffCounts(t *testing.T) {
+	both, gain, lost := blockDiffCounts(bmOf([2]int{0, 0}, [2]int{1, 0}), bmOf([2]int{0, 0}, [2]int{2, 0}))
+	if both != 1 || gain != 1 || lost != 1 {
+		t.Errorf("一块里应各有一格：both=%d gain=%d lost=%d", both, gain, lost)
+	}
+	both, gain, lost = blockDiffCounts(nil, bmOf([2]int{5, 5}))
+	if both != 0 || gain != 1 || lost != 0 {
+		t.Errorf("只有快照有该块：both=%d gain=%d lost=%d", both, gain, lost)
+	}
+}