- The issue comes from the fact that the default generated
+= and co by the Python API is the one for immutable types, like int.
- Indeed, in python, for an int :
x=1
id(x)
140266967205832
x+=1
id(x)
140266967205808
- For a mutable type, like a gf, it is necessary to
add explicitly the xxx_inplace_add functions.
- Added :
- the generation of the inplace_xxx functions
- a method in class_ in the wrapper generator that
deduce all += operator from the + operators.
- this assumes that the +=, ... are defined in C++.
- The generation of such operators are optional, with option
with_inplace_operators in the arithmetic flag.
- Also, added the overload g += M and g -= M for
g : GfImfreq, M a complex matrix.
Mainly for legacy Python codes.
- 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 reverts the part of the commit 1906dc30a5
which introduced modifications in the expr templates of the Green's
functions. The commit had introduced some bugs and this revert
removes them (the expr templates will be taken care of fully in later
commits). This is a temporary fix for issues #18 and #25.
reverted: triqs/gfs/data_proxies.hpp
reverted: triqs/gfs/gf.hpp
reverted: triqs/gfs/gf_expr.hpp
- add move semantics in expression template.
for gfs :
- rm descriptor
- Remove data from expr, rewrote assignment
which now iterates on the mesh, simply.
RHS models now FunctionOnMesh
- This fix the multiplication bug of gf
- Remove assign_no_resize/assign_with_resize from proxy
