Starting with a Fortran-contiguous array:
>>> import numpy as np >>> x = np.ones((2, 3), order='F') >>> x.flags['F_CONTIGUOUS'] True
Calling ascontiguousarray makes a C-contiguous copy:
>>> y = np.ascontiguousarray(x) >>> y.flags['C_CONTIGUOUS'] True >>> np.may_share_memory(x, y) False
Now, starting with a C-contiguous array:
>>> x = np.ones((2, 3), order='C') >>> x.flags['C_CONTIGUOUS'] True
Then, calling ascontiguousarray returns the same object:
>>> y = np.ascontiguousarray(x) >>> x is y True
Note: This function returns an array with at least one-dimension (1-d) so it will not preserve 0-d arrays.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4