Antoine Pitrou <solipsis@pitrou.net> wrote:
By always using an aligned allocator there is some overhead: - all arrays occupy a bit more memory by a small average amount (probably 16 bytes average on a 64-bit machine, for a 16 byte guaranteed alignment)
NumPy arrays are Python objects. They have an overhead anyway, much more than this, and 16 bytes are not worse than adding a couple of pointers to the struct. In the big picture this tiny overhead does not matter.
- array resizes can be more expensive in CPU time, when the physical start changes and its alignment changes too
We are using Python. If we were worried about small inefficiencies we would not be using it. Resizing ndarrays are rare anyway. They are not used like Python lists or instead of lists. We use lists in the same way as anyone else who uses Python. So an ndarray resize can afford to be more espensive than a list append. Also the NumPy community expects an ndarray resize to be expensive and O(n) due to its current behavior: If an array has a view, realloc is out of the question. :-) Sturla