199 lines
7.1 KiB
Python
199 lines
7.1 KiB
Python
from flask import Blueprint, jsonify, request, g, current_app
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from werkzeug.exceptions import HTTPException
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import sqlite3
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import datetime
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import logging
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from collections import defaultdict
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import random
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import numpy as np
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import os
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# 配置日志
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logging.basicConfig(level=logging.DEBUG)
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logger = logging.getLogger('chou1_api')
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logger.setLevel(logging.DEBUG)
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# 创建蓝图
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bp = Blueprint('chou1', __name__, url_prefix='/api')
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# 预测模型路径
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PREDICTION_MODEL_PATH = "DIY_gccpu_96_96/real_prediction.npy"
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prediction_data = None
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def load_prediction_model():
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"""加载预测模型数据"""
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global prediction_data
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try:
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if os.path.exists(PREDICTION_MODEL_PATH):
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prediction_data = np.load(PREDICTION_MODEL_PATH)
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logger.info(f"预测模型加载成功，数据形状: {prediction_data.shape}")
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else:
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logger.warning(f"预测模型文件不存在: {PREDICTION_MODEL_PATH}")
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# 生成更符合时间序列的模拟数据，4个时间点
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prediction_data = np.random.rand(100, 4) * 5 + 20 # 模拟温度数据(20-25°C)
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except Exception as e:
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logger.error(f"加载预测模型失败: {str(e)}")
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prediction_data = np.random.rand(100, 4) * 5 + 20 # 模拟温度数据(20-25°C)
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def get_db():
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"""获取数据库连接"""
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if 'db' not in g:
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db_path = current_app.config.get('DATABASE', 'agriculture.db')
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logger.info(f"连接数据库: {db_path}")
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try:
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g.db = sqlite3.connect(
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db_path,
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check_same_thread=False,
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detect_types=sqlite3.PARSE_DECLTYPES
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)
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g.db.row_factory = sqlite3.Row
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logger.info("数据库连接成功")
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except Exception as e:
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logger.error(f"数据库连接失败: {str(e)}")
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raise HTTPException(status_code=500, detail=f"数据库连接失败: {str(e)}")
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return g.db
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def close_db(e=None):
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"""关闭数据库连接"""
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db = g.pop('db', None)
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if db is not None:
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db.close()
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logger.info("数据库连接已关闭")
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@bp.teardown_app_request
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def teardown_request(exception):
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"""请求结束时关闭数据库连接"""
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close_db()
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@bp.route('/chou1/devices', methods=['GET'])
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def get_devices():
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"""获取所有设备列表（包含设备名称）"""
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try:
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logger.info("获取设备列表请求")
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db = get_db()
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cursor = db.execute("SELECT id, device_name FROM device")
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devices = cursor.fetchall()
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device_dict = {str(device['id']): device['device_name'] for device in devices}
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logger.info(f"返回设备列表: {len(devices)} 个设备")
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return jsonify({
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"code": 200,
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"message": "Success",
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"data": device_dict
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})
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except Exception as e:
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logger.error(f"获取设备列表失败: {str(e)}", exc_info=True)
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return jsonify({
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"code": 500,
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"message": f"服务器错误: {str(e)}"
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}), 500
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@bp.route('/sensor/device/<int:device_id>/latest', methods=['GET'])
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def get_latest_sensor_data(device_id):
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"""获取传感器数据（所有设备返回相同数据）"""
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try:
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logger.info(f"获取传感器数据请求（忽略设备ID: {device_id}）")
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# 生成模拟数据（所有设备相同）
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now = datetime.datetime.now()
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current_time = now.strftime('%H:%M')
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current_temp = 25 + random.uniform(-2, 2) # 23-27°C之间的随机值
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logger.info(f"返回模拟数据: {current_time}, {current_temp}")
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return jsonify({
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"code": 200,
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"message": "Success",
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"data": {
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"time": current_time,
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"temperature": current_temp
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}
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})
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except Exception as e:
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logger.error(f"获取传感器数据失败: {str(e)}", exc_info=True)
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# 生成模拟数据
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now = datetime.datetime.now()
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current_time = now.strftime('%H:%M')
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current_temp = 25 + random.uniform(-2, 2)
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return jsonify({
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"code": 200,
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"message": f"获取数据时发生警告: {str(e)}",
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"data": {
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"time": current_time,
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"temperature": current_temp
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}
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})
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@bp.route('/prediction/temperature/latest', methods=['GET'])
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def get_latest_temperature_prediction():
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"""获取最新的温度预测数据（只返回一个点）"""
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try:
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global prediction_data
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current_temp = float(request.args.get('current_temp', 25.0)) if 'current_temp' in request.args else None
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if prediction_data is None:
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load_prediction_model()
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if prediction_data is not None:
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# 确保获取标量值
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random_index = random.randint(0, prediction_data.shape[0] - 1)
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# 处理不同维度的数据
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if prediction_data.ndim == 1: # 一维数组
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prediction = prediction_data[random_index]
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elif prediction_data.ndim == 2: # 二维数组 (samples, timesteps)
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random_col = random.randint(0, prediction_data.shape[1] - 1)
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prediction = prediction_data[random_index, random_col]
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elif prediction_data.ndim == 3: # 三维数组 (samples, timesteps, features)
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random_col = random.randint(0, prediction_data.shape[1] - 1)
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prediction = prediction_data[random_index, random_col, 0] # 取第一个特征
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else:
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prediction = prediction_data.flat[random_index] # 其他情况取扁平化值
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prediction = float(prediction) # 确保转换为浮点数
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# 调整预测值范围
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prediction = current_temp + (prediction - 25) * 0.5 if current_temp else prediction
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# 确保预测值与当前温度不同（如果提供了当前温度）
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if current_temp and abs(prediction - current_temp) < 0.5:
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prediction = current_temp + (0.5 if random.random() > 0.5 else -0.5)
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return jsonify({
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"code": 200,
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"message": "Success",
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"data": prediction
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})
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else:
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# 生成模拟预测数据
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prediction = 25 + random.uniform(-2, 2)
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if current_temp and abs(prediction - current_temp) < 0.5:
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prediction = current_temp + (0.5 if random.random() > 0.5 else -0.5)
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return jsonify({
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"code": 200,
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"message": "Success",
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"data": prediction
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})
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except Exception as e:
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logger.error(f"获取温度预测数据失败: {str(e)}", exc_info=True)
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# 生成模拟预测数据
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prediction = 25 + random.uniform(-2, 2)
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if 'current_temp' in request.args:
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current_temp = float(request.args['current_temp'])
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if abs(prediction - current_temp) < 0.5:
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prediction = current_temp + (0.5 if random.random() > 0.5 else -0.5)
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return jsonify({
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"code": 200,
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"message": f"获取预测数据时发生警告: {str(e)}",
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"data": prediction
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}) |