numpy dtype错误 - （结构化数组创建）(numpy dtype error - (structured array creation))

 我无法理解为什么以下不起作用： 
 
np.dtype(dict(names="10", formats=np.float64))
 
 我一直在努力解决这个问题，因为我recfunctions numpy的recfunctions函数工作，但是由于numpy.dtype问题，我没有成功。 这是我目前收到的错误： 
 
dtype = np.dtype(dict(names=names, formats=formats))
ValueError: all items in the dictionary must have the same length.
 
 我想获得一个数据结构，其中包含一种记录数组，每个指定字段中包含多列数据 - 类似于字典，其中每个值是一个二维数组或几列数据。 通常，数据可能最终为~6列，每个键或记录约2000行，具有约200个记录。 
 
 这是我在一个完整的脚本中尝试过的:(虽然仍然给出相同的错误） 
 
import numpy as np
from numpy.lib import recfunctions


# Just function to make random data
def make_data(i, j):
    # some arbitrary function to show that the number of columns may change, but rows stay the same length
    if i%3==0:
        data = np.array([[i for i in range(0,1150)]*t for t in range(0,3)])
    else:
        data = np.array([[i for i in range(0,1150)]*t for t in range(0,6)])
    return data

def data_struct(low_ij, high_ij):

    """
    Data Structure to contain several columns of data for different combined values between "low ij" and "high ij"

    Key: "(i, j)"
    Value: numpy ndarray (multidimensional)
    """

    for i in range(0,low_ij+1):
        for j in range(0,high_ij+1):
            # Get rid of some of the combinations
            # (unimportant)
            if(i<low_ij and j<low_ij):
                break
            elif(i<j):
                break

            # Combinations of interest to create structure
            else:
                names = str(i)+str(j)
                formats = np.float64
                data = np.array(make_data(i, j))
                try:
                    data_struct = recfunctions.append_fields(base=data_struct, names=names, data=data, dtypes=formats)
                # First loop will assign data_struct using this exception,
                # then proceed to use the try statement to add on the rest of the data
                except UnboundLocalError:
                    dtype = np.dtype(dict(names=names, formats=formats))
                    data_struct = np.array(data, dtype=dtype)

    return data_struct

I am having some trouble understanding why the following does not work:
 
np.dtype(dict(names="10", formats=np.float64))
 
I have been struggling with this because I would like to get the recfunctions function in numpy to work, but due to issues with the numpy.dtype, I haven't been successful. This is the error I am receiving at the moment:
 
dtype = np.dtype(dict(names=names, formats=formats))
ValueError: all items in the dictionary must have the same length.
 
I want to get a data structure that will contain a type of record array with multiple columns of data within each assigned field - similar to a dictionary where each value is a 2d array or several columns of data. Typically the data may end up being ~6 columns, ~2000 rows for each key or record, with ~200 records.
 
Here is what I have tried in a complete script: (although still giving the same error)
 
import numpy as np
from numpy.lib import recfunctions


# Just function to make random data
def make_data(i, j):
    # some arbitrary function to show that the number of columns may change, but rows stay the same length
    if i%3==0:
        data = np.array([[i for i in range(0,1150)]*t for t in range(0,3)])
    else:
        data = np.array([[i for i in range(0,1150)]*t for t in range(0,6)])
    return data

def data_struct(low_ij, high_ij):

    """
    Data Structure to contain several columns of data for different combined values between "low ij" and "high ij"

    Key: "(i, j)"
    Value: numpy ndarray (multidimensional)
    """

    for i in range(0,low_ij+1):
        for j in range(0,high_ij+1):
            # Get rid of some of the combinations
            # (unimportant)
            if(i<low_ij and j<low_ij):
                break
            elif(i<j):
                break

            # Combinations of interest to create structure
            else:
                names = str(i)+str(j)
                formats = np.float64
                data = np.array(make_data(i, j))
                try:
                    data_struct = recfunctions.append_fields(base=data_struct, names=names, data=data, dtypes=formats)
                # First loop will assign data_struct using this exception,
                # then proceed to use the try statement to add on the rest of the data
                except UnboundLocalError:
                    dtype = np.dtype(dict(names=names, formats=formats))
                    data_struct = np.array(data, dtype=dtype)

    return data_struct

原文：https://stackoverflow.com/questions/27947763