- Simplify group_indices
- Only for C ordered, remove complex compile time.
- Could be generalized to non C ordered, but no need.
- Fix slice for custom orders.
- Generalize the group_indices for the custom order.
- Add c_ordered_transposed_view (useful ?)
- Improve slice, special for ellipsis (quicker).
- Simplify TraversalOrder
- Assignement. Specialize one case for speed.
- use FORCEINLINE in foreach, according to speed test for clang
- add one speed test
- Modify iterators for better speed.
- along the lines decided for the foreach
- update doc.
- the flag is really enforce_copy and should force a copy
- for a view : it is false, no change
- for a regular type : it is true, and now this will enforce the
copy in the call of numpy. numpy does it for us.
- The problematic case was when we construct a regular type
from a complicated view in python, which is an array
but is not C contiguous.
(hence the PyArray_Check was false, and the C_Contiguous flag was not set)
Now it is fine, since we ask numpy to systematically copy the data for us
and build a C contigous array.
--> the constructor from python does not support custom memory layout
because numpy only support C and Fortran
Conflicts:
triqs/arrays/impl/indexmap_storage_pair.hpp
