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https://github.com/triqs/dft_tools
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c7a1a25846
- 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 |
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| .. | ||
| blas_lapack | ||
| expression_template | ||
| functional | ||
| h5 | ||
| impl | ||
| indexmaps | ||
| linalg | ||
| python | ||
| storages | ||
| algorithms.hpp | ||
| array.hpp | ||
| asserts.hpp | ||
| cache.hpp | ||
| CMakeLists.txt | ||
| h5.hpp | ||
| make_immutable_array.hpp | ||
| mapped_functions.hpp | ||
| matrix_tensor_proxy.hpp | ||
| matrix_view_proxy.hpp | ||
| matrix.hpp | ||
| vector.hpp | ||