numpy.frombuffer
- numpy. 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
-
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.New in version 1.20.0.
- Returns
-
- out ndarray
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)
The data of the resulting array will not be byteswapped, but will be interpreted correctly.
Examples
>>> 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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https://numpy.org/doc/1.22/reference/generated/numpy.frombuffer.html