python numpy中fromfile函数的使用

def fromfile(file, dtype=None, count=-1, sep=''): # real signature unknown; restored from __doc__
    """
    fromfile(file, dtype=float, count=-1, sep='')
    
        Construct an array from data in a text or binary file.
        #从文本或二进制文件中的数据构造一个数组。
        A highly efficient way of reading binary data with a known data-type,
        as well as parsing simply formatted text files.  Data written using the
        `tofile` method can be read using this function.
        #一种按二进制格式来读取数据的高效方法，还能解析简单格式化的文本文件。使用`tofile`写入数据的方法可以使用这个函数来读取。
        Parameters
        ----------
        file : file or str
            Open file object or filename.
        dtype : data-type
            Data type of the returned array.
            For binary files, it is used to determine the size and byte-order
            of the items in the file.
            #对于二进制文件，它用于确定文件中项目的大小和字节顺序。
        count : int
            Number of items to read. ``-1`` means all items (i.e., the complete
            file).
        sep : str
            Separator between items if file is a text file.
            Empty ("") separator means the file should be treated as binary.
            Spaces (" ") in the separator match zero or more whitespace characters.
            A separator consisting only of spaces must match at least one
            whitespace.
           # 如果文件是一个文本文件，默认使用空格分隔。
           ("")分隔符意味着文件应被视为二进制文件。分隔符中的空格（""）匹配零个或多个空白字符。仅由空格组成的分隔符必须至少匹配一个""。
        See also
        --------
        load, save
        ndarray.tofile
        loadtxt : More flexible way of loading data from a text file.
    
        Notes
        -----
        Do not rely on the combination of `tofile` and `fromfile` for
        data storage, as the binary files generated are are not platform
        independent.  In particular, no byte-order or data-type information is
        saved.  Data can be stored in the platform independent ``.npy`` format
        using `save` and `load` instead.
    
        Examples
        --------
        Construct an ndarray:
    
        >>> dt = np.dtype([('time', [('min', int), ('sec', int)]),
        ...                ('temp', float)])
        >>> x = np.zeros((1,), dtype=dt)
        >>> x['time']['min'] = 10; x['temp'] = 98.25
        >>> x
        array([((10, 0), 98.25)],
              dtype=[('time', [('min', '>> import os
        >>> fname = os.tmpnam()
        >>> x.tofile(fname)
    
        Read the raw data from disk:
    
        >>> np.fromfile(fname, dtype=dt)
        array([((10, 0), 98.25)],
              dtype=[('time', [('min', '>> np.save(fname, x)
        >>> np.load(fname + '.npy')
        array([((10, 0), 98.25)],
              dtype=[('time', [('min', '

tofile()只能保存为二进制文件，且不能保存当前数据的行列信息，文件后缀不影响保存格式，还是二进制。

tofile()保存方法对数据读取有要求，需要手动指定读出来的数据的的dtype，如果指定的格式与保存时的不一致，则读出来的就是错误的数据。