import ast
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import sys
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import numpy as np
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import json
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import time
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import redis
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radiusLen = None
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# 将字符串转换为浮点型数组
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def convert_to_float_array(str_array):
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if isinstance(str_array, str):
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return np.array(ast.literal_eval(str_array), dtype=float)
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return str_array
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def getWaveScopeByCode(x, y):
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code = codeMatrix[x, y]
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includeList = []
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existNodes = set()
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spreadWaveNode({"x": x, "y": y}, {"x": x, "y": y}, existNodes, includeList)
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return includeList
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def spreadWaveNode(originNode, currNode, existNodes, includeList):
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x, y = currNode['x'], currNode['y']
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neighbors = [(x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)]
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for neighbor in neighbors:
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extendNeighborNodes(originNode, {"x": neighbor[0], "y": neighbor[1]}, existNodes, includeList)
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def extendNeighborNodes(originNode, nextNode, existNodes, includeList):
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x, y = nextNode['x'], nextNode['y']
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if (x < 0 or x >= codeMatrix.shape[0] or y < 0 or y >= codeMatrix.shape[1]):
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return
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if (x, y) in existNodes:
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return
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existNodes.add((x, y))
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nextNodeCodeData = codeMatrix[x, y]
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if nextNodeCodeData == 'NONE':
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spreadWaveNode(originNode, nextNode, existNodes, includeList)
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else:
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o1Cda = convert_to_float_array(cdaMatrix[originNode['x'], originNode['y']])
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o2Cda = convert_to_float_array(cdaMatrix[x, y])
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num1 = (o1Cda[0] - o2Cda[0]) ** 2
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num2 = (o1Cda[1] - o2Cda[1]) ** 2
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if num1 + num2 <= radiusLen ** 2:
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includeList.append({"x": int(x), "y": int(y), "code": str(codeMatrix[x, y])})
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spreadWaveNode(originNode, nextNode, existNodes, includeList)
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# 找到某个值对应的 x, y 下标
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def find_value_in_matrix(value):
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indices = np.where(codeMatrix == value)
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return list(zip(indices[0], indices[1]))
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def initWaveMatrix():
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lev = 1
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waveMatrix = np.empty_like(codeMatrix, dtype=object)
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for x in range(codeMatrix.shape[0]):
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for y in range(codeMatrix.shape[1]):
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if codeMatrix[x][y] == 'NONE':
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waveMatrix[x][y] = "-"
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else:
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waveMatrix[x][y] = '[]'
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return waveMatrix
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# 优化版本：使用集合来提高性能
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def mergeWave(originWave, vehicle):
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# 将字符串解析为集合
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set_data = set(ast.literal_eval(originWave))
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# 如果 vehicle 不在集合中，则添加
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set_data.add(vehicle)
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# 返回序列化后的字符串
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return json.dumps(list(set_data))
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# 将 dynamicMatrix 转换为 numpy 结构化数组
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def convert_to_structured_array(dynamicMatrix):
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# 定义结构化数组的 dtype
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dtype = [('serial', int), ('vehicle', 'U2')]
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# 将嵌套的列表转换为结构化数组
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structured_array = np.array([tuple(d.values()) for row in dynamicMatrix for d in row], dtype=dtype)
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# 重塑为原始的二维形状
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return structured_array.reshape(len(dynamicMatrix), -1)
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# 使用 numpy 加速的代码
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def process_dynamic_matrix(dynamicMatrix, codeMatrix):
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# 将 dynamicMatrix 转换为结构化数组
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dynamicMatrix = convert_to_structured_array(dynamicMatrix)
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# 获取 dynamicMatrix 的形状
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rows, cols = dynamicMatrix.shape
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# 创建一个布尔掩码，用于筛选出 vehicle 不为 '0' 和 '-1' 的元素
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mask = (dynamicMatrix['vehicle'] != '0') & (dynamicMatrix['vehicle'] != '-1')
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# 获取满足条件的 x 和 y 坐标
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x_indices, y_indices = np.where(mask)
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# 遍历满足条件的坐标
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for x, y in zip(x_indices, y_indices):
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# print(code)
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data = dynamicMatrix[x][y]
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vehicle = data['vehicle']
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includeList = getWaveScopeByCode(x,y)
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for include in includeList:
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originWave = waveMatrix[include['x']][include['y']]
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waveMatrix[include['x']][include['y']] = mergeWave(originWave, vehicle)
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radiusLenStr = sys.argv[1]
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radiusLen = float(radiusLenStr)
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redisHost = sys.argv[2]
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redisPwd = sys.argv[3]
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redisPort = sys.argv[4]
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redisIdx = sys.argv[5]
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startTime = time.perf_counter()
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# 创建一个连接池
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pool = redis.ConnectionPool(host=redisHost, port=int(redisPort), password=redisPwd, db=int(redisIdx))
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r = redis.Redis(connection_pool=pool)
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codeMatrixStr = r.get('KV.AGV_MAP_ASTAR_CODE_FLAG.1')
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codeMatrix = np.array(json.loads(codeMatrixStr))
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cdaMatrixStr = r.get('KV.AGV_MAP_ASTAR_CDA_FLAG.1')
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cdaMatrix = np.array(json.loads(cdaMatrixStr))
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dynamicMatrixStr = r.get('KV.AGV_MAP_ASTAR_DYNAMIC_FLAG.1')
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dynamicMatrix = np.array(json.loads(dynamicMatrixStr))
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waveMatrix = initWaveMatrix()
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# # 使用 numpy 加速的代码
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process_dynamic_matrix(dynamicMatrix, codeMatrix)
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# for x in range(dynamicMatrix.shape[0]):
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# for y in range(dynamicMatrix.shape[1]):
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# data = dynamicMatrix[x, y]
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# vehicle = data['vehicle']
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# if vehicle != '0' and vehicle != '-1':
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# getWaveScopeByCode(x, y)
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# 将 numpy.ndarray 转换为嵌套列表
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waveMatrixList = waveMatrix.tolist()
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# 将嵌套列表转换为 JSON 字符串
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waveMatrixJsonStr = json.dumps(waveMatrixList)
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r.set("KV.AGV_MAP_ASTAR_WAVE_FLAG.1",waveMatrixJsonStr)
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end = time.perf_counter()
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# print('程序运行时间为: %s Seconds' % (end - startTime))
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print("1")
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