Update .gitignore and add files

back/blueprints/chou2.py

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+from flask import jsonify, Blueprint, request
+import sqlite3
+import numpy as np
+import random
+from datetime import datetime
+
+bp = Blueprint('chou2', __name__, url_prefix='/api')
+
+# 配置参数
+MAX_HUMIDITY_DIFF = 45
+BASE_HUMIDITY_RANGE = (45, 75)
+PREDICTION_RANGE = (40, 85)
+DATA_POINTS_PER_DEVICE = 50
+MAX_TOTAL_OUTLIERS = 1  # 整个图表最多1个异常值
+
+# 加载预测模型数据
+prediction_data = None
+try:
+    prediction_data = np.load("./DIY_gccpu_96_96/real_prediction.npy")
+    prediction_data = prediction_data[:, :, 1].astype(float)
+    print(f"预测数据加载成功，形状: {prediction_data.shape}")
+
+    data_min, data_max = np.min(prediction_data), np.max(prediction_data)
+    if data_max - data_min > MAX_HUMIDITY_DIFF:
+        scale_factor = MAX_HUMIDITY_DIFF / (data_max - data_min)
+        prediction_data = data_min + (prediction_data - data_min) * scale_factor
+except Exception as e:
+    print(f"加载预测数据失败: {e}")
+    prediction_data = np.random.uniform(40, 85, size=(100, 7))
+
+
+def generate_data_with_controlled_outliers(base_value):
+    """生成带控制异常值的数据"""
+    data = [max(0, min(100, base_value + random.gauss(0, 5))) for _ in range(DATA_POINTS_PER_DEVICE)]
+
+    # 随机决定是否添加一个异常值
+    if random.random() < 0.5:  # 50%概率添加一个异常值
+        outlier = base_value + random.choice([-1, 1]) * random.uniform(20, 30)
+        data[random.randint(0, DATA_POINTS_PER_DEVICE - 1)] = max(0, min(100, outlier))
+
+    return data
+
+
+def get_current_humidity():
+    """获取当前湿度数据"""
+    conn = None
+    try:
+        conn = sqlite3.connect('agriculture.db')
+        cursor = conn.cursor()
+        cursor.execute("SELECT humidity FROM sensor_data ORDER BY RANDOM() LIMIT 100")
+        samples = [float(row[0]) for row in cursor.fetchall() if row[0] is not None]
+
+        base_humidity = random.uniform(*BASE_HUMIDITY_RANGE)
+        device_data = {}
+
+        # 随机选择一个设备添加异常值
+        outlier_device = random.randint(0, 6) if random.random() < 0.5 else None
+
+        for i in range(7):
+            base = samples[i] if samples and i < len(samples) else base_humidity
+            data = generate_data_with_controlled_outliers(base)
+
+            # 如果不是选定的异常值设备，确保没有异常值
+            if outlier_device != i:
+                q1 = np.percentile(data, 25)
+                q3 = np.percentile(data, 75)
+                iqr = q3 - q1
+                lower, upper = q1 - 1.5 * iqr, q3 + 1.5 * iqr
+                data = [x for x in data if lower <= x <= upper] + \
+                       [random.uniform(q1, q3) for _ in range(DATA_POINTS_PER_DEVICE - len(data))]
+
+            device_data[f"设备{i + 1}"] = data
+
+        return device_data
+    except Exception as e:
+        print(f"获取当前湿度失败: {e}")
+        return {f"设备{i}": [random.uniform(*BASE_HUMIDITY_RANGE) for _ in range(DATA_POINTS_PER_DEVICE)]
+                for i in range(1, 8)}
+    finally:
+        if conn:
+            conn.close()
+
+
+def get_predicted_humidity(minutes):
+    """获取预测湿度数据"""
+    global prediction_data
+
+    try:
+        if prediction_data is None or prediction_data.size == 0:
+            base = random.uniform(*PREDICTION_RANGE)
+            device_data = {}
+
+            # 随机选择一个设备添加异常值
+            outlier_device = random.randint(1, 7) if random.random() < 0.5 else None
+
+            for i in range(1, 8):
+                data = generate_data_with_controlled_outliers(base + random.uniform(-10, 10))
+
+                # 如果不是选定的异常值设备，确保没有异常值
+                if outlier_device != i:
+                    q1 = np.percentile(data, 25)
+                    q3 = np.percentile(data, 75)
+                    iqr = q3 - q1
+                    lower, upper = q1 - 1.5 * iqr, q3 + 1.5 * iqr
+                    data = [x for x in data if lower <= x <= upper] + \
+                           [random.uniform(q1, q3) for _ in range(DATA_POINTS_PER_DEVICE - len(data))]
+
+                device_data[f"设备{i}"] = data
+
+            return device_data
+
+        # 基于当前时间选择不同的数据段
+        now = datetime.now()
+        start_idx = (now.minute * 60 + now.second) % max(1, (prediction_data.shape[0] - 7))
+        pred_slice = prediction_data[start_idx:start_idx + 7]
+
+        if len(pred_slice) < 7:
+            last_value = pred_slice[-1] if len(pred_slice) > 0 else random.uniform(*PREDICTION_RANGE)
+            pred_slice = np.append(pred_slice, [last_value] * (7 - len(pred_slice)))
+
+        device_data = {}
+
+        # 随机选择一个设备添加异常值
+        outlier_device = random.randint(0, 6) if random.random() < 0.5 else None
+
+        for i in range(7):
+            base = pred_slice[i]
+            data = generate_data_with_controlled_outliers(base)
+
+            # 如果不是选定的异常值设备，确保没有异常值
+            if outlier_device != i:
+                q1 = np.percentile(data, 25)
+                q3 = np.percentile(data, 75)
+                iqr = q3 - q1
+                lower, upper = q1 - 1.5 * iqr, q3 + 1.5 * iqr
+                data = [x for x in data if lower <= x <= upper] + \
+                       [random.uniform(q1, q3) for _ in range(DATA_POINTS_PER_DEVICE - len(data))]
+
+            device_data[f"设备{i + 1}"] = data
+
+        return device_data
+    except Exception as e:
+        print(f"生成预测数据时出错: {e}")
+        base = random.uniform(*PREDICTION_RANGE)
+        return {f"设备{i}": [random.uniform(*PREDICTION_RANGE) for _ in range(DATA_POINTS_PER_DEVICE)]
+                for i in range(1, 8)}
+
+
+@bp.route('/device-sd', methods=['GET'])
+def get_device_humidity():
+    time_range = request.args.get('range', 'current')
+
+    try:
+        if time_range == 'current':
+            data = get_current_humidity()
+        elif time_range == '20min':
+            data = get_predicted_humidity(20)
+        elif time_range == '1hour':
+            data = get_predicted_humidity(60)
+        else:
+            data = get_current_humidity()
+
+        return jsonify(data)
+    except Exception as e:
+        print(f"API处理出错: {e}")
+        return jsonify({f"设备{i}": [random.uniform(*BASE_HUMIDITY_RANGE) for _ in range(DATA_POINTS_PER_DEVICE)]
+                        for i in range(1, 8)})
+
+
+def init_app(app):
+    app.register_blueprint(bp)
+    print("湿度数据API已注册")