我有一个内存映射，其中包含一个 2D 数组，我想从中创建一个 numpy 数组。理想情况下，我想避免复制，因为涉及的数组可能很大。
我的代码如下所示：
n_bytes = 10000
tagname = "Some Tag from external System"
map = mmap.mmap(-1, n_bytes, tagname)
offsets = [0, 5000]
columns = []
for offset in offsets:
#type and count vary in the real code, but for this dummy code I simply made them up. But I know the count and type for every column.
np_type = np.dtype('f4')
column_data = np.frombuffer(map, np_type, count=500, offset=offset)
columns.append(column_data)
# this line seems to copy the data, which I would like to avoid
data = np.array(columns).T
假设您有一个字节数组并且您知道它的尺寸，那么答案非常简单。
想象一下，您将图像的原始 RGB 数据（每像素 24 位）存储在缓冲区（名为“buff”）中
尺寸为 1024x768
#read the buffer into 1D byte array
arr = numpy.frombuffer(buff, dtype=numpy.uint8)
#now shape the array as you please
arr.shape = (768,1024,3)
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