为什么HERE API中的routingApi.matrix()方法有时找不到两点之间的开销？

Question

我正在使用Here API和Python (herepy)，我在使用routingApi.matrix()方法时遇到了问题，因为多次运行代码会抛出以下错误。特别是，对于同一组起点和终点，有时它会设法创建距离矩阵，但有时它会向我抛出错误。我知道当函数要查找JSON变量的值时，它找不到我所请求的字典。但我不明白为什么在一次迭代中我没有问题，而在另一次迭代中，它给了我这个错误。

distMatrixComp()和distMatrix()函数是没有问题的任意函数

Start Points:  [[-36.62871, -72.07365], [-36.59533, -72.0858], [-36.8972043, -72.028369], [-36.62639, -72.09149], [-36.6089, -72.10252], [-35.96823, -72.33622], [-36.42341, -71.96235], [-36.41848, -71.97017], [-36.61557, -72.11887], [-36.14303, -71.8106], [-36.1414329, -71.827859], [-35.96311, -72.31443], [-36.61005, -72.1025], [-36.61525, -72.07426], [-36.6163286, -72.1227685]]
 End Points:  [[-36.5874, -72.11869], [-36.56707, -72.07326], [-36.2867395, -72.5440474], [-36.60889, -72.10185], [-36.74158, -72.46435], [-35.9665601, -72.3123652], [-36.60703, -72.10427], [-36.6094, -72.0999], [-36.5874, -72.11869], [-36.61266, -72.10245], [-36.46084, -71.72261], [-35.95813, -72.33583], [-36.60979, -72.14558], [-35.9686549, -72.3149309], [-36.623144, -72.124962]] 

    Traceback (most recent call last):

      File "<ipython-input-27-1bccda51e23d>", line 1, in <module>
        runfile('C:/Users/bacheleonb/Dropbox/Python/Project Carterizacion/updateMatrixDistances.py')

      File "C:\Users\bacheleonb\AppData\Local\Continuum\anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
        execfile(filename, namespace)

      File "C:\Users\bacheleonb\AppData\Local\Continuum\anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
        exec(compile(f.read(), filename, 'exec'), namespace)

      File "C:/Users/bacheleonb/Dropbox/Python/Project Carterizacion/updateMatrixDistances.py", line 166, in <module>
        matrix = distMatrix(listCoordenadas)

      File "C:/Users/bacheleonb/Dropbox/Python/Project Carterizacion/updateMatrixDistances.py", line 96, in distMatrix
        solution = distMatrixComp(startPoints, endPoints)

      File "C:/Users/bacheleonb/Dropbox/Python/Project Carterizacion/updateMatrixDistances.py", line 27, in distMatrixComp
        modes=[herepy.RouteMode.fastest, herepy.RouteMode.car],summary_attributes=["distance"])

      File "C:\Users\bacheleonb\AppData\Local\Continuum\anaconda3\lib\site-packages\herepy\routing_api.py", line 295, in matrix
        response = self.__get(self.URL_CALCULATE_MATRIX, data, RoutingMatrixResponse)

      File "C:\Users\bacheleonb\AppData\Local\Continuum\anaconda3\lib\site-packages\herepy\routing_api.py", line 40, in __get
        json_data = json.loads(response.content.decode('utf8'))

      File "C:\Users\bacheleonb\AppData\Local\Continuum\anaconda3\lib\json\__init__.py", line 348, in loads
        return _default_decoder.decode(s)

      File "C:\Users\bacheleonb\AppData\Local\Continuum\anaconda3\lib\json\decoder.py", line 337, in decode
        obj, end = self.raw_decode(s, idx=_w(s, 0).end())

      File "C:\Users\bacheleonb\AppData\Local\Continuum\anaconda3\lib\json\decoder.py", line 355, in raw_decode
        raise JSONDecodeError("Expecting value", s, err.value) from None

    JSONDecodeError: Expecting value

def distMatrix(listCoordenadas):

    # Función Auxiliar
    def distMatrixComp(startPoints, endPoints): 

        response = routingApi.matrix(
            start_waypoints=startPoints,
            destination_waypoints=endPoints,
            departure='2018-07-04T17:00:00+02',
            modes=[herepy.RouteMode.fastest, herepy.RouteMode.car],summary_attributes=["distance"])
        return response

    # Función Auxiliar
    def grouped(iterable, n): 
        return list(zip(*[iter(iterable)]*n))

    if len(listCoordenadas) > 15:

        restData = len(listCoordenadas)%15

        if restData != 0:

            restData = tuple(listCoordenadas[-restData:])

        nColumnsGroup = len(grouped(listCoordenadas, 15))

        columnsMatrix = ["Group %s"%i for i in range(1,nColumnsGroup+1)]

        if restData != 0:

            columnsMatrix.append("Group %s"%(nColumnsGroup+1))

        matrix = pd.DataFrame(columns = columnsMatrix)

        for x in grouped(listCoordenadas, 15):

           comb = {}

           for y, c in zip(grouped(listCoordenadas, 15),
                           columnsMatrix):

               comb[c] = [list(x), list(y)]

           if restData != 0:

               comb["Group %s"%(nColumnsGroup+1)] = [list(x), list(restData)]
               matrix = matrix.append(comb, ignore_index= True)

           else:

               matrix = matrix.append(comb, ignore_index= True)

        if restData != 0:

            comb = {}
            for x, c in zip(grouped(listCoordenadas,15),
                            columnsMatrix):

                comb[c] = [list(restData), list(x)]

            comb["Group %s"%(nColumnsGroup+1)] = [list(restData), list(restData)]

            matrix = matrix.append(comb, ignore_index= True)

        nRowsMatrix = matrix.shape[0]
        nColumnsMatrix = matrix.shape[1]
        print(matrix)
        finalDistanceMatrix = [[0 for i in range(nRowsMatrix)] for j in range(nColumnsMatrix)]
        for i in range(nRowsMatrix):

            for j in range(nColumnsMatrix):

                startPoints = matrix.iloc[i,j][0]
                endPoints = matrix.iloc[i,j][1]
                print("nRow: ", i)
                print("nCol: ", j)
                print("Start Points: ", startPoints)
                print("End Points: ", endPoints, "\n")
                solution = distMatrixComp(startPoints, endPoints)
                #print(solution)
                tempDistMatrix = [[0 for i in range(len(endPoints))] for j in range(len(startPoints))]

                for k in solution.response["matrixEntry"]:

                    tempDistMatrix[k["startIndex"]][k["destinationIndex"]] = k["summary"]["distance"]

                finalDistanceMatrix[i][j] = tempDistMatrix

        distanceMatrix = np.zeros((len(listCoordenadas), len(listCoordenadas)))

        indiceX = 0
        indiceY = 0

        for i in finalDistanceMatrix:
            for j in i:

                tempX = 0

                for k in range(len(j)):
                    tempY = 0

                    for l in j[k]:

                        distanceMatrix[indiceX+tempX,indiceY+tempY] = l

                        tempY += 1
                    tempX += 1    

                indiceY += len(j[0])
            indiceY = 0
            indiceX += len(j)

    else:            

        distanceMatrix = np.zeros((len(listCoordenadas), len(listCoordenadas)))
        solution = distMatrixComp(listCoordenadas, listCoordenadas)
        for i in solution.response["matrixEntry"]:

            distanceMatrix[i["startIndex"]][i["destinationIndex"]] = i["summary"]["distance"]

    matrixRaw = distanceMatrix
    matrix = pd.DataFrame(matrixRaw)
    #matrix = (matrix-matrix.min())/(matrix.max()-matrix.min())

    return matrix

{"response": {"matrixEntry": [{"destinationIndex": 0, "startIndex": 0, "summary": {"costFactor": 2390, "distance": 33519}}, 
                              {"destinationIndex": 1, "startIndex": 0, "summary": {"costFactor": 346, "distance": 1916}}, 
                              {"destinationIndex": 2, "startIndex": 0, "summary": {"costFactor": 2259, "distance": 32941}}, 
                              {"destinationIndex": 3, "startIndex": 0, "summary": {"costFactor": 2090, "distance": 27661}}, 
                              {"destinationIndex": 4, "startIndex": 0, "status": "failed"}, 
                              {"destinationIndex": 5, "startIndex": 0, "summary": {"costFactor": 4485, "distance": 78916}}, 
                              {"destinationIndex": 6, "startIndex": 0, "summary": {"costFactor": 5751, "distance": 111151}}, 

                              {"destinationIndex": 3, "startIndex": 1, "summary": {"costFactor": 873, "distance": 6165}},
                              {"destinationIndex": 4, "startIndex": 1, "status": "failed"}, 
                              {"destinationIndex": 5, "startIndex": 1, "summary": {"costFactor": 2724, "distance": 43621}}, 
                              {"destinationIndex": 6, "startIndex": 1, "summary": {"costFactor": 4168, "distance": 80086}}, 

                              {"destinationIndex": 2, "startIndex": 2, "summary": {"costFactor": 3198, "distance": 62491}},
                              {"destinationIndex": 3, "startIndex": 2, "summary": {"costFactor": 3518, "distance": 69691}}, 
                              {"destinationIndex": 4, "startIndex": 2, "status": "failed"},
                              {"destinationIndex": 5, "startIndex": 2, "summary": {"costFactor": 4952, "distance": 100113}}, 
                              {"destinationIndex": 6, "startIndex": 2, "summary": {"costFactor": 941, "distance": 10104}},
                              {"destinationIndex": 7, "startIndex": 2, "summary": {"costFactor": 795, "distance": 8373}}, 

Answer 1

你是正确的。开始路点“定义矩阵中路线的起始点的路点列表。M:N请求中的开始数限制为15。”15 *15应该可以工作，但herepy不在这里，所以不能确切地说出问题是什么。看起来问题是由于目的地的传播而导致的超时。

您是否可以尝试使用少于15个节点，或者您可以尝试直接使用路由API https://developer.here.com/documentation/routing/dev_guide/topics/example-matrix-use-post-method.html