numpy.fromfile(file, dtype=float, count=-1, sep='', offset=0)¶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.
Open file object or filename.
Changed in version 1.17.0: pathlib.Path objects are now accepted.
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. Most builtin numeric types are supported and extension types may be supported.
New in version 1.18.0: Complex dtypes.
Number of items to read. -1 means all items (i.e., the complete
file).
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.
The offset (in bytes) from the file’s current position. Defaults to 0. Only permitted for binary files.
New in version 1.17.0.
Notes
Do not rely on the combination of tofile and fromfile for
data storage, as the binary files generated 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', np.int64), ('sec', np.int64)]),
... ('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', '<i8'), ('sec', '<i8')]), ('temp', '<f8')])
Save the raw data to disk:
>>> import tempfile
>>> fname = tempfile.mkstemp()[1]
>>> x.tofile(fname)
Read the raw data from disk:
>>> np.fromfile(fname, dtype=dt)
array([((10, 0), 98.25)],
dtype=[('time', [('min', '<i8'), ('sec', '<i8')]), ('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', '<i8'), ('sec', '<i8')]), ('temp', '<f8')])