numpy.frombuffer()
- 2019 年 10 月 28 日
- 笔记
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本文链接：https://blog.csdn.net/weixin_36670529/article/details/102668346
numpy.frombuffer
numpy.frombuffer(buffer, dtype=float, count=-1, offset=0)
Interpret a buffer as a 1-dimensional array.
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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. |
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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‘x01x02‘, dtype=np.uint8) array([1, 2], dtype=uint8) >>> np.frombuffer(b‘x01x02x03x04x05‘, 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。
