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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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cmake | ||
doc | ||
foreignlibs | ||
packaging/os_x | ||
pytriqs | ||
shells | ||
test | ||
triqs | ||
.clang-format | ||
ChangeLog | ||
CITATIONS.bib | ||
CMakeLists.txt | ||
COPYING.txt | ||
LICENSE.txt | ||
README.txt |
The TRIQS website is under http://ipht.cea.fr/triqs. Start there to learn about TRIQS. To install TRIQS, follow the installation steps given under http://ipht.cea.fr/triqs/doc/user_manual/install/install.html Before you proceed, make sure you have read the LICENSE.txt file. Enjoy! The TRIQS team