Enhance converging triangle analysis with boundary utilization scoring and detailed chart mode
- Introduced a new boundary utilization score to measure price proximity to triangle boundaries, improving the accuracy of strength assessments. - Updated scoring weights to incorporate boundary utilization, adjusting the contributions of convergence, volume, and fitting scores. - Added detailed chart mode in the stock viewer, allowing users to toggle between standard and detailed views with additional metrics displayed. - Enhanced documentation to reflect new features, including usage instructions for the boundary utilization score and detailed chart mode. - Improved error handling in the stock viewer for better user experience.
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@ -79,3 +79,89 @@ result = detect_converging_triangle(high, low, close, volume, params)
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- 分位数回归: `fit_boundary_quantile()`
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- 锚点拟合: `fit_boundary_anchor()`
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- 分发函数: `fit_pivot_line_dispatch()`
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# 拟合度分数低，强度分却整体偏高
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---
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## 已实现：边界利用率分数（2026-01-27）
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### 问题分析
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观察图中 SZ002748 世龙实业：
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- 宽度比：0.12（非常收敛）
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- 强度分：0.177（排名第三）
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- 但肉眼观察：价格走势与三角形边界之间有**大量空白**
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**原因**：
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- 原权重：收敛分 20%、拟合贴合度 15%
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- 当宽度比 0.12 时，收敛分 = 1 - 0.12 = 0.88
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- 收敛分贡献 = 0.20 × 0.88 = 0.176 ≈ 全部强度分
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- **收敛分只衡量"形状收窄"，不衡量"价格是否贴近边界"**
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### 解决方案
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新增**边界利用率**分数，衡量价格走势对三角形通道空间的利用程度。
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### 新增函数
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```python
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def calc_boundary_utilization(
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high, low,
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upper_slope, upper_intercept,
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lower_slope, lower_intercept,
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start, end,
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) -> float:
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"""
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计算边界利用率 (0~1)
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对窗口内每一天：
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1. 计算价格到上下边界的距离
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2. 空白比例 = (到上沿距离 + 到下沿距离) / 通道宽度
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3. 当日利用率 = 1 - 空白比例
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返回平均利用率
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"""
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```
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### 新权重配置
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| 分量 | 原权重 | 新权重 | 说明 |
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|------|--------|--------|------|
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| 突破幅度 | 50% | **50%** | 不变 |
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| 收敛分 | 20% | **15%** | 降低 |
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| 成交量分 | 15% | **10%** | 降低 |
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| 拟合贴合度 | 15% | **10%** | 降低 |
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| **边界利用率** | - | **15%** | 新增 |
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### 空白惩罚（新增）
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为避免“通道很宽但价格很空”的误判，加入空白惩罚：
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```
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UTILIZATION_FLOOR = 0.20
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惩罚系数 = min(1, boundary_utilization / UTILIZATION_FLOOR)
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最终强度分 = 原强度分 × 惩罚系数
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```
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当边界利用率明显偏低时，总分会被进一步压制。
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### 结果字段
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`ConvergingTriangleResult` 新增字段：
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```python
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boundary_utilization: float = 0.0 # 边界利用率分数
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```
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### 效果
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- 价格贴近边界（空白少）→ 利用率高 → 强度分高
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- 价格远离边界（空白多）→ 利用率低 → 强度分被惩罚
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- 当边界利用率 < 0.20 时，强度分按比例衰减（空白惩罚）
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- 解决"形状收敛但空白多"的误判问题
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# 上/下沿线，有些点没有碰到线的边缘
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@ -68,6 +68,7 @@ def load_stock_data(csv_path: str, target_date: int = None, all_stocks_mode: boo
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'touchesUpper': int(row.get('touches_upper', '0')),
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'touchesLower': int(row.get('touches_lower', '0')),
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'volumeConfirmed': row.get('volume_confirmed', ''),
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'boundaryUtilization': float(row.get('boundary_utilization', '0')),
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'date': date,
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'hasTriangle': True # 标记为有三角形形态
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}
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@ -77,6 +78,7 @@ def load_stock_data(csv_path: str, target_date: int = None, all_stocks_mode: boo
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# 清理文件名中的非法字符
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clean_name = stock['name'].replace('*', '').replace('?', '').replace('"', '').replace('<', '').replace('>', '').replace('|', '').replace(':', '').replace('/', '').replace('\\', '')
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stock['chartPath'] = f"charts/{date}_{stock_code}_{clean_name}.png"
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stock['chartPathDetail'] = f"charts/{date}_{stock_code}_{clean_name}_detail.png"
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if stock_code not in stocks_map or stocks_map[stock_code]['strength'] < stock['strength']:
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stocks_map[stock_code] = stock
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@ -103,8 +105,10 @@ def load_stock_data(csv_path: str, target_date: int = None, all_stocks_mode: boo
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'touchesUpper': 0,
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'touchesLower': 0,
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'volumeConfirmed': '',
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'boundaryUtilization': 0.0,
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'date': use_date,
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'chartPath': f"charts/{use_date}_{code}_{clean_name}.png",
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'chartPathDetail': f"charts/{use_date}_{code}_{clean_name}_detail.png",
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'hasTriangle': False # 标记为无三角形形态
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}
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@ -873,6 +877,33 @@ def generate_html(stocks: list, date: int, output_path: str):
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color: var(--accent-warm);
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}
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/* Detail Toggle */
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.detail-toggle {
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padding: 10px 18px;
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background: var(--bg-card);
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border: 1px solid var(--border-subtle);
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border-radius: 10px;
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color: var(--text-secondary);
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font-size: 14px;
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font-family: 'Noto Sans SC', sans-serif;
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cursor: pointer;
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transition: all var(--transition-fast);
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display: flex;
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align-items: center;
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gap: 6px;
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}
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.detail-toggle:hover {
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border-color: var(--accent-primary);
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color: var(--accent-primary);
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}
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.detail-toggle.active {
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background: rgba(0, 212, 170, 0.1);
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border-color: var(--accent-primary);
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color: var(--accent-primary);
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}
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/* Filter Chips */
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.filter-chips {
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display: flex;
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@ -1033,6 +1064,16 @@ def generate_html(stocks: list, date: int, output_path: str):
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background: var(--accent-cool);
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}
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</style>
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<script>
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// 工具函数（需要在页面加载前定义，因为HTML元素的onerror会直接调用）
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function handleModalImageError(img) {
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const fallbackSrc = img.dataset.fallbackSrc;
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if (fallbackSrc && img.src !== fallbackSrc && img.dataset.fallbackTried !== 'true') {
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img.dataset.fallbackTried = 'true';
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img.src = fallbackSrc;
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}
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}
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</script>
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</head>
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<body>
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<div class="app-container">
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@ -1062,6 +1103,9 @@ def generate_html(stocks: list, date: int, output_path: str):
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</select>
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<button class="sort-toggle active" id="sortOrder" title="切换排序顺序">↓</button>
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</div>
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<button class="detail-toggle" id="detailToggle" title="切换详细图">
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详细图: 关
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</button>
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<button class="reset-btn" id="resetBtn">
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<span>↺</span> 重置筛选
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</button>
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@ -1136,13 +1180,14 @@ def generate_html(stocks: list, date: int, output_path: str):
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<div id="imageModal" class="modal">
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<div class="modal-content">
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<button class="close-modal" onclick="closeModal()">×</button>
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<img id="modalImage" src="" alt="股票图表">
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<img id="modalImage" src="" alt="股票图表" onerror="handleModalImageError(this)">
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</div>
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</div>
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<script>
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// 内嵌数据
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const allStocks = STOCK_DATA;
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let currentThreshold = 0;
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let showDetailCharts = false;
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// 筛选和排序状态
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let filters = {
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@ -1209,6 +1254,15 @@ def generate_html(stocks: list, date: int, output_path: str):
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filterAndDisplayStocks();
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});
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// 详细图切换
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const detailToggle = document.getElementById('detailToggle');
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detailToggle.addEventListener('click', function() {
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showDetailCharts = !showDetailCharts;
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this.textContent = showDetailCharts ? '详细图: 开' : '详细图: 关';
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this.classList.toggle('active', showDetailCharts);
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filterAndDisplayStocks();
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});
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// 方向筛选芯片
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const directionFilter = document.getElementById('directionFilter');
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directionFilter.addEventListener('click', function(e) {
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@ -1350,9 +1404,11 @@ def generate_html(stocks: list, date: int, output_path: str):
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stock.direction === 'down' ? 'direction-down' : '';
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const volumeText = stock.volumeConfirmed === 'True' ? '✓' :
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stock.volumeConfirmed === 'False' ? '✗' : '—';
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const chartPath = showDetailCharts ? stock.chartPathDetail : stock.chartPath;
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const fallbackPath = showDetailCharts ? stock.chartPath : stock.chartPathDetail;
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return `
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<div class="stock-card" onclick="openModal('${stock.chartPath}')">
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<div class="stock-card" onclick="openModal('${stock.chartPath}', '${stock.chartPathDetail}')">
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<div class="card-header">
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<div class="stock-identity">
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<div class="stock-name">${stock.name}</div>
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@ -1381,11 +1437,16 @@ def generate_html(stocks: list, date: int, output_path: str):
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<span class="metric-label">放量确认</span>
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<span class="metric-value">${volumeText}</span>
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</div>
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<div class="metric-item">
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<span class="metric-label">边界利用率</span>
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<span class="metric-value">${(stock.boundaryUtilization || 0).toFixed(2)}</span>
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</div>
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</div>
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<div class="chart-container">
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<img src="${stock.chartPath}"
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<img src="${chartPath}"
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alt="${stock.name}"
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class="stock-chart"
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data-fallback-src="${fallbackPath}"
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onerror="handleImageError(this)">
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</div>
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</div>
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@ -1394,6 +1455,12 @@ def generate_html(stocks: list, date: int, output_path: str):
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}
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function handleImageError(img) {
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const fallbackSrc = img.dataset.fallbackSrc;
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if (fallbackSrc && img.src !== fallbackSrc && img.dataset.fallbackTried !== 'true') {
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img.dataset.fallbackTried = 'true';
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img.src = fallbackSrc;
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return;
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}
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if (img.dataset.errorHandled) return;
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img.dataset.errorHandled = 'true';
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img.style.display = 'none';
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@ -1403,9 +1470,14 @@ def generate_html(stocks: list, date: int, output_path: str):
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img.parentElement.appendChild(noChart);
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}
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function openModal(imagePath) {
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function openModal(defaultPath, detailPath) {
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event.stopPropagation();
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document.getElementById('modalImage').src = imagePath;
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const modalImage = document.getElementById('modalImage');
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const targetPath = showDetailCharts ? detailPath : defaultPath;
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const fallbackPath = showDetailCharts ? defaultPath : detailPath;
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modalImage.dataset.fallbackTried = 'false';
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modalImage.dataset.fallbackSrc = fallbackPath;
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modalImage.src = targetPath;
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document.getElementById('imageModal').classList.add('show');
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}
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@ -285,6 +285,30 @@ def plot_triangle(
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# 详细模式：显示拟合点（仅在 show_details=True 且有三角形时）
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# ========================================================================
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if show_details and has_triangle and has_enough_data:
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# 标注所有枢轴点（用于查看拐点分布）
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if len(ph_display_idx) > 0:
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ax1.scatter(
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ph_display_idx,
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high_win[ph_idx],
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marker='x',
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s=60,
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color='red',
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alpha=0.6,
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zorder=4,
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label=f'上沿枢轴点({len(ph_idx)})',
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)
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if len(pl_display_idx) > 0:
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ax1.scatter(
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pl_display_idx,
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low_win[pl_idx],
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marker='x',
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s=60,
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color='green',
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alpha=0.6,
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zorder=4,
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label=f'下沿枢轴点({len(pl_idx)})',
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)
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# 标注选中的枢轴点（用于拟合线的关键点）
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if len(selected_ph_display) >= 2:
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ax1.scatter(
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@ -324,6 +348,14 @@ def plot_triangle(
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strength = max(result.breakout_strength_up, result.breakout_strength_down)
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price_score = max(result.price_score_up, result.price_score_down)
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# 获取边界利用率与惩罚系数（兼容旧数据）
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boundary_util = getattr(result, 'boundary_utilization', 0.0)
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utilization_floor = 0.20
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if utilization_floor > 0:
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utilization_penalty = min(1.0, boundary_util / utilization_floor)
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else:
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utilization_penalty = 1.0
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ax1.set_title(
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f"{stock_code} {stock_name} - 收敛三角形 (检测窗口: {detect_dates[0]} ~ {detect_dates[-1]})\n"
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f"显示范围: {display_dates[0]} ~ {display_dates[-1]} ({len(display_dates)}个交易日) "
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@ -331,8 +363,9 @@ def plot_triangle(
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f"枢轴点: 高{len(ph_idx)}/低{len(pl_idx)} 触碰: 上{result.touches_upper}/下{result.touches_lower} "
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f"放量确认: {'是' if result.volume_confirmed else '否' if result.volume_confirmed is False else '-'}\n"
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f"强度分: {strength:.3f} "
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f"(价格: {price_score:.3f}×50% + 收敛: {result.convergence_score:.3f}×20% + "
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f"成交量: {result.volume_score:.3f}×15% + 拟合贴合度: {result.fitting_score:.3f}×15%)",
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f"(价格: {price_score:.3f}×50% + 收敛: {result.convergence_score:.3f}×15% + "
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f"成交量: {result.volume_score:.3f}×10% + 拟合贴合度: {result.fitting_score:.3f}×10% + "
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f"边界利用率: {boundary_util:.3f}×15%) × 利用率惩罚: {utilization_penalty:.2f}",
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fontsize=11, pad=10
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)
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else:
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@ -396,6 +429,11 @@ def main() -> None:
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action="store_true",
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help="为所有108只股票生成图表（包括不满足收敛三角形条件的）",
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)
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parser.add_argument(
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"--clear",
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action="store_true",
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help="清空当前模式的旧图片（默认不清空）",
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)
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args = parser.parse_args()
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# 确定是否显示详细信息（命令行参数优先）
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@ -467,22 +505,24 @@ def main() -> None:
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print("当日无满足条件的股票")
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return
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# 4. 创建输出目录并清空对应模式的旧图片
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# 4. 创建输出目录，并按需清空对应模式的旧图片
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os.makedirs(args.output_dir, exist_ok=True)
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# 只清空当前模式的图片（简洁模式或详细模式）
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print(f"\n[4] 清空当前模式的旧图片...")
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suffix = "_detail.png" if show_details else ".png"
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# 找出当前模式的文件：简洁模式是不含_detail的.png，详细模式是_detail.png
|
||||
if show_details:
|
||||
old_files = [f for f in os.listdir(args.output_dir) if f.endswith('_detail.png')]
|
||||
if args.clear:
|
||||
# 只清空当前模式的图片（简洁模式或详细模式）
|
||||
print(f"\n[4] 清空当前模式的旧图片...")
|
||||
# 找出当前模式的文件：简洁模式是不含_detail的.png，详细模式是_detail.png
|
||||
if show_details:
|
||||
old_files = [f for f in os.listdir(args.output_dir) if f.endswith('_detail.png')]
|
||||
else:
|
||||
old_files = [f for f in os.listdir(args.output_dir)
|
||||
if f.endswith('.png') and not f.endswith('_detail.png')]
|
||||
|
||||
for f in old_files:
|
||||
os.remove(os.path.join(args.output_dir, f))
|
||||
print(f" 已删除 {len(old_files)} 个旧图片 ({'详细模式' if show_details else '简洁模式'})")
|
||||
else:
|
||||
old_files = [f for f in os.listdir(args.output_dir)
|
||||
if f.endswith('.png') and not f.endswith('_detail.png')]
|
||||
|
||||
for f in old_files:
|
||||
os.remove(os.path.join(args.output_dir, f))
|
||||
print(f" 已删除 {len(old_files)} 个旧图片 ({'详细模式' if show_details else '简洁模式'})")
|
||||
print(f"\n[4] 跳过清空旧图片（使用 --clear 可手动清空）")
|
||||
|
||||
# 5. 检测参数（从统一配置导入）
|
||||
params = DETECTION_PARAMS
|
||||
|
||||
Binary file not shown.
@ -80,6 +80,7 @@ class ConvergingTriangleResult:
|
||||
convergence_score: float = 0.0 # 收敛分数
|
||||
volume_score: float = 0.0 # 成交量分数
|
||||
fitting_score: float = 0.0 # 拟合贴合度分数
|
||||
boundary_utilization: float = 0.0 # 边界利用率分数
|
||||
|
||||
# 几何属性
|
||||
upper_slope: float = 0.0
|
||||
@ -811,6 +812,72 @@ def calc_fitting_adherence(
|
||||
return min(1.0, max(0.0, adherence_score))
|
||||
|
||||
|
||||
def calc_boundary_utilization(
|
||||
high: np.ndarray,
|
||||
low: np.ndarray,
|
||||
upper_slope: float,
|
||||
upper_intercept: float,
|
||||
lower_slope: float,
|
||||
lower_intercept: float,
|
||||
start: int,
|
||||
end: int,
|
||||
) -> float:
|
||||
"""
|
||||
计算边界利用率 (0~1)
|
||||
|
||||
衡量价格走势对三角形通道空间的利用程度。
|
||||
如果价格总是远离边界线（大量空白），利用率低。
|
||||
如果价格频繁接近或触碰边界线，利用率高。
|
||||
|
||||
计算方法：
|
||||
1. 对窗口内每一天，计算价格到上下边界的相对距离
|
||||
2. 利用率 = 1 - 平均相对空白比例
|
||||
|
||||
归一化映射：
|
||||
- 空白 0% → 利用率 1.00 (价格完全贴合边界)
|
||||
- 空白 25% → 利用率 0.75 (良好)
|
||||
- 空白 50% → 利用率 0.50 (一般)
|
||||
- 空白 75% → 利用率 0.25 (较差，大量空白)
|
||||
|
||||
Args:
|
||||
high, low: 价格数据
|
||||
upper_slope, upper_intercept: 上沿线参数
|
||||
lower_slope, lower_intercept: 下沿线参数
|
||||
start, end: 窗口范围
|
||||
|
||||
Returns:
|
||||
utilization: 0~1，越大表示利用率越高
|
||||
"""
|
||||
total_utilization = 0.0
|
||||
valid_days = 0
|
||||
|
||||
for i in range(start, end + 1):
|
||||
upper_line = upper_slope * i + upper_intercept
|
||||
lower_line = lower_slope * i + lower_intercept
|
||||
channel_width = upper_line - lower_line
|
||||
|
||||
if channel_width <= 0:
|
||||
continue
|
||||
|
||||
# 计算价格到边界的距离（价格应在通道内，所以距离 >= 0）
|
||||
dist_to_upper = max(0.0, upper_line - high[i])
|
||||
dist_to_lower = max(0.0, low[i] - lower_line)
|
||||
|
||||
# 当日空白比例 = (到上沿距离 + 到下沿距离) / 通道宽度
|
||||
blank_ratio = (dist_to_upper + dist_to_lower) / channel_width
|
||||
|
||||
# 当日利用率 = 1 - 空白比例，限制在 [0, 1]
|
||||
day_utilization = max(0.0, min(1.0, 1.0 - blank_ratio))
|
||||
|
||||
total_utilization += day_utilization
|
||||
valid_days += 1
|
||||
|
||||
if valid_days == 0:
|
||||
return 0.0
|
||||
|
||||
return total_utilization / valid_days
|
||||
|
||||
|
||||
def calc_breakout_strength(
|
||||
close: float,
|
||||
upper_line: float,
|
||||
@ -818,7 +885,8 @@ def calc_breakout_strength(
|
||||
volume_ratio: float,
|
||||
width_ratio: float,
|
||||
fitting_adherence: float,
|
||||
) -> Tuple[float, float, float, float, float, float]:
|
||||
boundary_utilization: float,
|
||||
) -> Tuple[float, float, float, float, float, float, float, float]:
|
||||
"""
|
||||
计算形态强度分 (0~1)
|
||||
|
||||
@ -827,9 +895,13 @@ def calc_breakout_strength(
|
||||
|
||||
使用加权求和，各分量权重：
|
||||
- 突破幅度分 (50%): tanh 非线性归一化，3%突破≈0.42，5%突破≈0.64，10%突破≈0.91
|
||||
- 收敛分 (20%): 1 - width_ratio，收敛越强分数越高
|
||||
- 成交量分 (15%): 放量程度，2倍放量=满分
|
||||
- 拟合贴合度 (15%): 枢轴点到拟合线的贴合程度，形态纯度
|
||||
- 收敛分 (15%): 1 - width_ratio，收敛越强分数越高
|
||||
- 成交量分 (10%): 放量程度，2倍放量=满分
|
||||
- 拟合贴合度 (10%): 枢轴点到拟合线的贴合程度，形态纯度
|
||||
- 边界利用率 (15%): 价格走势对通道空间的利用程度
|
||||
|
||||
额外惩罚项：
|
||||
- 当边界利用率过低时，对总强度进行空白惩罚，避免“通道很宽但价格很空”的误判
|
||||
|
||||
突破幅度分布参考（使用 tanh(pct * 15)）：
|
||||
- 1% 突破 → 0.15
|
||||
@ -846,19 +918,23 @@ def calc_breakout_strength(
|
||||
volume_ratio: 成交量相对均值的倍数
|
||||
width_ratio: 末端宽度/起始宽度
|
||||
fitting_adherence: 拟合贴合度分数 (0~1)
|
||||
boundary_utilization: 边界利用率分数 (0~1)
|
||||
|
||||
Returns:
|
||||
(strength_up, strength_down, price_score_up, price_score_down, convergence_score, vol_score, fitting_score)
|
||||
(strength_up, strength_down, price_score_up, price_score_down,
|
||||
convergence_score, vol_score, fitting_score, boundary_util_score)
|
||||
返回总强度和各分量分数，用于可视化和分析
|
||||
"""
|
||||
import math
|
||||
|
||||
# 权重配置
|
||||
W_PRICE = 0.50 # 突破幅度权重
|
||||
W_CONVERGENCE = 0.20 # 收敛度权重
|
||||
W_VOLUME = 0.15 # 成交量权重
|
||||
W_FITTING = 0.15 # 拟合贴合度权重
|
||||
TANH_SCALE = 15.0 # tanh 缩放因子
|
||||
# 权重配置（调整后，总和 = 100%）
|
||||
W_PRICE = 0.50 # 突破幅度权重
|
||||
W_CONVERGENCE = 0.15 # 收敛度权重（原 20%，降低）
|
||||
W_VOLUME = 0.10 # 成交量权重（原 15%，降低）
|
||||
W_FITTING = 0.10 # 拟合贴合度权重（原 15%，降低）
|
||||
W_UTILIZATION = 0.15 # 边界利用率权重（新增）
|
||||
TANH_SCALE = 15.0 # tanh 缩放因子
|
||||
UTILIZATION_FLOOR = 0.20 # 边界利用率下限（用于空白惩罚）
|
||||
|
||||
# 1. 价格突破分数（tanh 非线性归一化）
|
||||
if upper_line > 0:
|
||||
@ -882,22 +958,36 @@ def calc_breakout_strength(
|
||||
# 4. 拟合贴合度分数（直接使用传入的分数）
|
||||
fitting_score = max(0.0, min(1.0, fitting_adherence))
|
||||
|
||||
# 5. 加权求和（计算综合强度分）
|
||||
# 5. 边界利用率分数（直接使用传入的分数）
|
||||
boundary_util_score = max(0.0, min(1.0, boundary_utilization))
|
||||
|
||||
# 6. 加权求和（计算综合强度分）
|
||||
# 不再要求必须突破，而是计算形态的综合质量分数
|
||||
strength_up = (
|
||||
W_PRICE * price_score_up +
|
||||
W_CONVERGENCE * convergence_score +
|
||||
W_VOLUME * vol_score +
|
||||
W_FITTING * fitting_score
|
||||
W_FITTING * fitting_score +
|
||||
W_UTILIZATION * boundary_util_score
|
||||
)
|
||||
|
||||
strength_down = (
|
||||
W_PRICE * price_score_down +
|
||||
W_CONVERGENCE * convergence_score +
|
||||
W_VOLUME * vol_score +
|
||||
W_FITTING * fitting_score
|
||||
W_FITTING * fitting_score +
|
||||
W_UTILIZATION * boundary_util_score
|
||||
)
|
||||
|
||||
# 7. 空白惩罚（边界利用率过低时降低总分）
|
||||
if UTILIZATION_FLOOR > 0:
|
||||
utilization_penalty = min(1.0, boundary_util_score / UTILIZATION_FLOOR)
|
||||
else:
|
||||
utilization_penalty = 1.0
|
||||
|
||||
strength_up *= utilization_penalty
|
||||
strength_down *= utilization_penalty
|
||||
|
||||
return (
|
||||
min(1.0, strength_up),
|
||||
min(1.0, strength_down),
|
||||
@ -905,7 +995,8 @@ def calc_breakout_strength(
|
||||
price_score_down,
|
||||
convergence_score,
|
||||
vol_score,
|
||||
fitting_score
|
||||
fitting_score,
|
||||
boundary_util_score
|
||||
)
|
||||
|
||||
|
||||
@ -1123,16 +1214,30 @@ def detect_converging_triangle(
|
||||
# 综合上下沿贴合度（取平均）
|
||||
fitting_adherence = (adherence_upper + adherence_lower) / 2.0
|
||||
|
||||
# 计算边界利用率（价格走势对三角形通道的利用程度）
|
||||
boundary_utilization = calc_boundary_utilization(
|
||||
high=high,
|
||||
low=low,
|
||||
upper_slope=a_u,
|
||||
upper_intercept=b_u,
|
||||
lower_slope=a_l,
|
||||
lower_intercept=b_l,
|
||||
start=start,
|
||||
end=end,
|
||||
)
|
||||
|
||||
# 计算突破强度（返回总强度和各分量分数）
|
||||
(strength_up, strength_down,
|
||||
price_score_up, price_score_down,
|
||||
convergence_score, vol_score, fitting_score) = calc_breakout_strength(
|
||||
convergence_score, vol_score, fitting_score,
|
||||
boundary_util_score) = calc_breakout_strength(
|
||||
close=close[end],
|
||||
upper_line=upper_end,
|
||||
lower_line=lower_end,
|
||||
volume_ratio=volume_ratio,
|
||||
width_ratio=width_ratio,
|
||||
fitting_adherence=fitting_adherence,
|
||||
boundary_utilization=boundary_utilization,
|
||||
)
|
||||
|
||||
return ConvergingTriangleResult(
|
||||
@ -1146,6 +1251,7 @@ def detect_converging_triangle(
|
||||
convergence_score=convergence_score,
|
||||
volume_score=vol_score,
|
||||
fitting_score=fitting_score,
|
||||
boundary_utilization=boundary_util_score,
|
||||
upper_slope=a_u,
|
||||
lower_slope=a_l,
|
||||
width_ratio=width_ratio,
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user