numpy.fromfile()

numpy.fromfile(file, dtype=float, count=-1, sep='')

Construct an array from data in a text or binary file.

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.

Parameters:

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. 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.

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.

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.

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', '<i4'), ('sec', '<i4')]), ('temp', '<f8')])

Save the raw data to disk:

>>> 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', '<i4'), ('sec', '<i4')]), ('temp', '<f8')])

The recommended way to store and load data:

>>> np.save(fname, x)
>>> np.load(fname + '.npy')
array([((10, 0), 98.25)],
      dtype=[('time', [('min', '<i4'), ('sec', '<i4')]), ('temp', '<f8')])

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.fromfile.html

doc_NumPy

2017-01-10 18:14:08

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