Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from http://docs.scipy.org/doc/numpy/reference/generated/numpy.rec.fromfile.html below:

numpy.rec.fromfile — NumPy v2.3 Manual

rec.fromfile(fd, dtype=None, shape=None, offset=0, formats=None, names=None, titles=None, aligned=False, byteorder=None)[source]#

Create an array from binary file data

Parameters:

fdstr or file type

If file is a string or a path-like object then that file is opened, else it is assumed to be a file object. The file object must support random access (i.e. it must have tell and seek methods).

dtypedata-type, optional

valid dtype for all arrays

shapeint or tuple of ints, optional

shape of each array.

offsetint, optional

Position in the file to start reading from.

formats, names, titles, aligned, byteorder

If dtype is None, these arguments are passed to numpy.format_parser to construct a dtype. See that function for detailed documentation

Returns:

np.recarray

record array consisting of data enclosed in file.

Examples

>>> from tempfile import TemporaryFile
>>> a = np.empty(10,dtype='f8,i4,a5')
>>> a[5] = (0.5,10,'abcde')
>>>
>>> fd=TemporaryFile()
>>> a = a.view(a.dtype.newbyteorder('<'))
>>> a.tofile(fd)
>>>
>>> _ = fd.seek(0)
>>> r=np.rec.fromfile(fd, formats='f8,i4,a5', shape=10,
... byteorder='<')
>>> print(r[5])
(0.5, 10, b'abcde')
>>> r.shape
(10,)

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4