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Module « numpy.matlib »
Signature de la fonction frombuffer
Description
help(numpy.matlib.frombuffer)
frombuffer(buffer, dtype=float, count=-1, offset=0, *, like=None)
Interpret a buffer as a 1-dimensional array.
Parameters
----------
buffer : buffer_like
An object that exposes the buffer interface.
dtype : data-type, optional
Data-type of the returned array; default: float.
count : int, optional
Number of items to read. ``-1`` means all data in the buffer.
offset : int, optional
Start reading the buffer from this offset (in bytes); default: 0.
like : array_like, optional
Reference object to allow the creation of arrays which are not
NumPy arrays. If an array-like passed in as ``like`` supports
the ``__array_function__`` protocol, the result will be defined
by it. In this case, it ensures the creation of an array object
compatible with that passed in via this argument.
.. versionadded:: 1.20.0
Returns
-------
out : ndarray
See also
--------
ndarray.tobytes
Inverse of this operation, construct Python bytes from the raw data
bytes in the array.
Notes
-----
If the buffer has data that is not in machine byte-order, this should
be specified as part of the data-type, e.g.::
>>> dt = np.dtype(int)
>>> dt = dt.newbyteorder('>')
>>> np.frombuffer(buf, dtype=dt) # doctest: +SKIP
The data of the resulting array will not be byteswapped, but will be
interpreted correctly.
This function creates a view into the original object. This should be safe
in general, but it may make sense to copy the result when the original
object is mutable or untrusted.
Examples
--------
>>> import numpy as np
>>> s = b'hello world'
>>> np.frombuffer(s, dtype='S1', count=5, offset=6)
array([b'w', b'o', b'r', b'l', b'd'], dtype='|S1')
>>> np.frombuffer(b'\x01\x02', dtype=np.uint8)
array([1, 2], dtype=uint8)
>>> np.frombuffer(b'\x01\x02\x03\x04\x05', dtype=np.uint8, count=3)
array([1, 2, 3], dtype=uint8)
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