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[转载]numpy.frombuffer
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numpy.frombuffer
numpy.frombuffer(buffer, dtype=float, count=-1, offset=0)
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. offset : int, optional Start reading the buffer from this offset (in bytes); default: 0. |
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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 = ‘hello world‘ >>> np.frombuffer(s, dtype=‘S1‘, count=5, offset=6) array([‘w‘, ‘o‘, ‘r‘, ‘l‘, ‘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)
NumPy的ndarray数组对象不能像list一样动态地改变其大小，在做数据采集时很不方便。本文介绍如何通过np.frombuffer()实现动态数组。
【参考】
https://blog.csdn.net/weixin_36670529/article/details/102668346
https://wap.sciencenet.cn/blog-3428464-1247195.html
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