张宗平
61 lines
1.7 KiB
Bash
Executable File
61 lines
1.7 KiB
Bash
Executable File
#!/usr/bin/env bash
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# run_compare.sh — 对所有内置数据集跑纵向对比可视化（render-column）
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#
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# 用法:
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# bash scripts/run_compare.sh [数据集目录] [输出目录]
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#
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# 默认:
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# 数据集目录: ../../datasets/builtin
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# 输出目录: render_compare
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#
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# 管道: inject → render-column（自动检测 + 渲染）
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set -uo pipefail
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BUILTIN_DIR="${1:-../../datasets/builtin}"
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OUTPUT="${2:-render_compare}"
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URL="${TS_ANA_TD_URL:-ws://root:taosdata@localhost:6041}"
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# 多列数据集映射: dataset_name → value_col
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declare -A VALUE_COLS=(
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["ecg_002"]="ECG1"
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["sensor_007"]="ankle_horiz_fwd"
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)
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mkdir -p "$OUTPUT"
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total=0
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ok=0
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skip=0
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for dataset_dir in "$BUILTIN_DIR"/*/; do
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name=$(basename "$dataset_dir")
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csv="$dataset_dir/data.csv"
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[[ -f "$csv" ]] || { echo "SKIP $name: no data.csv"; ((skip++)); ((total++)); continue; }
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# 确定 value 列
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value_col="${VALUE_COLS[$name]:-value}"
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echo "=== $name (value_col=$value_col) ==="
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# 1. 注入
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echo " [1/2] inject..."
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uv run python -m ts_anomaly_td inject \
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--csv "$csv" --stable "$name" --value-col "$value_col" --url "$URL" \
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|| { echo " inject FAILED, skipping $name"; ((total++)); continue; }
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# 2. 纵向对比渲染（内部自动检测 6 算法）
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echo " [2/2] render-column..."
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uv run python -m ts_anomaly_td render-column \
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--gt-csv "$csv" --stable "$name" --value-col "$value_col" \
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--output "$OUTPUT/${name}_compare.png" --url "$URL" \
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&& { echo " → $OUTPUT/${name}_compare.png"; ((ok++)); } \
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|| { echo " render-column FAILED"; }
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((total++))
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done
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echo ""
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echo "=== 完成: $ok/$total 成功, $skip 跳过 ==="
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ls -la "$OUTPUT"/*_compare.png 2>/dev/null || echo "(无输出)"
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