- implement transposed_view for arrays.
- .transpose method for gf
- wrapped to python
- add call op. for GfImTime, using C++
- Added ChangeLog
- rm matrix_stack
- start cleaning old code
- parameters : clean, add back serialization. Clean whitespace
- serialization : depending on the version of the hdf5 lib,
uses h5 or boost.
- TODO : test it on a machine with new hdf5.
- new parameter class :
parameters are viewed as form, built in C++, and filled in C++/python.
Each field of the form as a precise C++ type (erased using standard techniques).
First tests ok, to be reread/checked.
TODO : serialization is commented. Lead to long compilation time & large code
due to boost::serialization. Use h5 when possible.
- wrapper :
- separated the converters of the wrapped type in the TRIQS library
- necessary for parameters (it used outside an .so) and potentially
other codes, outside an .so module
When constructing the last unit vector in 2D, the sanity check was wrong because of usage of abs instead of std::abs.
Added method energy_on_bz_path_2 that returns the energy *matrix* at each k point on a given path instead of the eigenvalues of this matrix. The name of the function should be changed (to energy_matrix_on_bz_path?)
Renaming energies_on_bz_path_2 to energy_matrix_on_bz_path
- The kind() method of mesh should return a char,
like the parameter of the constructor of mesh,
not the C++ corresponding int.
- otherwise, the reduction - construction is broken
and by extension all pickling and then all mpi constructions.
- to choose mpi4py over boost.python.mpi, pass -DPython_use_mpi4py=ON
- boost.mpi stays the default for python, but
adding the possibility of using mpi4py instead.
- Due to numerous pbs on recent OS X + brew installation.
boost.mpi does not work (crash in openmpi ??), mpi4py does
- the pytriqs/utility/mpi.py is now configured by the cmake (like
version.py) to prepare one of the two possibilities.
- TODO: not tested carefully : to be done in other machines.
When an object with __hdf_write__ was written in an archive, the
corresponding key was not cached. Therefore, one could not access
the object which had just been written.
- clef : fix a little bug in storage when evaluating
(was using the wrong trait to deduce storage type).
- gf : block :
- added reinterpret_scalar_valued_gf_as_matrix_valued
for block function
- cleaned make_block_gf_view_from_vector
- added make_block_gf_view_from_vectormake_block_gf_view_from_vector_of_cython_proxy
and changed the cython accordingly because it requires a slightly different syntax.
- updated tests
- gf : cleaned some template.
- lazy_fourier and co --> fourier
- ex fourier --> make_gf_from_fourier to make a new gf
- = fourier (g) works only iif lhs is a view, like scalar.
- updated python (commented fourier method).
- Make more general constructors for the gf.
gf( mesh, target_shape_t)
- remove the old make_gf for the basic gf.
- 2 var non generic gf removed.
- clean evaluator
- add tensor_valued
- add a simple vertex test.
- clean specialisation
- Fix bug introduced in 1906dc3
- forgot to resize the gf in new version of operator =
- Fix make_singularity in gf.hpp
- clean resize in operator =
- update h5 read/write for block gf
- changed a bit the general trait to save *all* the gf.
- allows a more general specialization, then a correct for blocks
- NOT FINISHED : need to save the block indice for python.
How to reread ?
Currently it read the blocks names and reconstitute the mesh from it.
Is it sufficient ?
- clean block constructors
- block constructors simplest possible : an int for the number of blocks
- rest in free factories.
- fixed the generic constructor from GfType for the regular type :
only enable iif GfType is ImmutableGreenFunction
- multivar. fix linear index in C, and h5 format
- linear index now correctly flatten in C mode
(was in fortran mode), using a simple reverse of the tuple in the folding.
- fix the h5 read write of the multivar fonctions
in order to write an array on dimension # variables + dim_target
i.e. without flattening the indices of the meshes.
Easier for later data analysis, e.g. in Python.
- merge matrix/tensor_valued. improve factories
- matrix_valued now = tensor_valued<2>
(simplifies generic code for h5).
- factories_one_var -> factories : this is the generic case ...
only a few specialization, code is simpler.
- clef expression call with rvalue for *this
- generalize matrix_proxy to tensor and clean
- clean exception catch in tests
- exception catching catch in need in test
because the silly OS X does not print anything, just "exception occurred".
Very convenient for the developer...
- BUT, one MUST add return 1, or the make test will *pass* !!
- --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT
which return a non zero error code.
- exception : curry_and_fourier which does not work at this stage
(mesh incompatible).
- gf: clean draft of gf 2 times
- comment the python interface for the moment.
- rm useless tests
This is a fix for issue #18. The type float128 doesn't exist on 32-bit
machines. I removed it from the matrix_stack.pyx detection of a scalar.
modified: pytriqs/gf/local/matrix_stack.pyx
A trivial cythonized version of the c++ random_generator class.
Useful to get the names of the generators from the python.
new file: pytriqs/random/*
new file: doc/reference/python/random/*
Now the tail have a fixed size. It actually makes everything simpler. I took
order_min = -1 and order_max = 8. This makes the tails compatible with the
previous implementation. However we might want to change this to something like
-10, 10 so that they are self-contained. This commit should also fix issue #11.
I added a version.hpp and updated the version.py so that
one can find the version of the library either from the
c++ or the python (if there is python support).
modified: CMakeLists.txt
modified: cmake/TRIQSConfig.cmake.in
modified: pytriqs/version.py.in
modified: triqs/CMakeLists.txt
new file: triqs/version.hpp.in
gcc has a pb because the template mesh<Variable,Opt>
has the name same as the gf mesh method (!).
Clang is fine however on this...
Solution : rename the template mesh<...> to gf_mesh...
Not very elegant, but ok.
