Tidying up

CMakeLists.txt

@@ -15,7 +15,7 @@ enable_testing()
 find_package(TRIQS REQUIRED)
 
 if (NOT ${TRIQS_WITH_PYTHON_SUPPORT})
- MESSAGE(FATAL_ERROR "Wien2TRIQS require Python support in TRIQS")
+ MESSAGE(FATAL_ERROR "dft_tools require Python support in TRIQS")
 endif()
 
 # Check that versions are compatible

doc/reference/h5structure.rst

@@ -66,7 +66,7 @@ In order to be used with the DMFT routines, the following data needs to be provi
 Wien2k Converter
 ----------------
 
-As you might expect, wien2triqs comes with a converter to use `Wien2k <http://www.wien2k.at>`_ band structure calculations as input for the DMFT part of the calculation, through the construction of projective Wannier functions. The first step is done by the program :program:`dmftproj`, producing text output files. In the second step, this ouput is read and converted into the hdf5 format, using the python module :class:`Wien2kConverter`.
+The dft_tools package comes with a converter to use `Wien2k <http://www.wien2k.at>`_ band structure calculations as input for the DMFT part of the calculation, through the construction of projective Wannier functions. The first step is done by the program :program:`dmftproj`, producing text output files. In the second step, this ouput is read and converted into the hdf5 format, using the python module :class:`Wien2kConverter`.
 
 HERE COMES A LISTING OF THE FUNCTIONS.
 

doc/reference/h5structure.rst~

@@ -1,74 +0,0 @@
-
-H5 input file and Converters
-============================
-
-All the data is stored using the hdf5 standard, as described also in the documentation of the TRIQS package itself. In order to do a DMFT calculation, using input from DFT applications, a converter is needed on order to provide the necessary data in the hdf5 format. 
-
-
-
-hdf5 data format
-----------------
-
-In order to be used with the DMFT routines, the following data needs to be provided in the hdf5 file. It contains a lot of information in order to perform DMFT calculations for all kinds of situations, e.g. d-p Hamiltonians, more than one correlated atomic shell, or using symmetry operations for the k-summation. We store all data in subgroups of the hdf5 arxive:
-
-:program:`Main data`: There needs to be one subgroup for the main data of the calculation. The default name of this group is `SumK_LDA`. Its contents are
-
-  * `energy_unit`, numpy.float. The unit of energy used for the calculation
-
-  * `n_k`, numpy.int. The number of k-points used for the BZ integration.
-
-  * `k_dep_projection`, numpy.int. If the dimension of the projection operators depend on the k-point, set to 1. Otherwise set to 0.
-
-  * `SP`, numpy.int. 0 for paramagnetic hamiltonian, 1 for spin polarised hamiltonian.
-
-  * `SO`, numpy.int. 1 if spin-orbit interaction is included, 0 otherwise.
-
-  * `charge_below`, numpy.float. The number of electrons in the crystal below the correlated orbitals. 
-
-  * `density_required`, numpy.float. Required total electron density, important for the determination of the chemical potential. The density of the correlated electrons is then `density_required`-`charge_below`. 
-
-  * `symm_op`, numpy.int. 1 if symmetry operations are used for the BZ sums, 0 if all k-points are directly included in the input.
-
-  * `n_shells`, numpy.int. Number of atomic shells for which post processing is possible. This is `not` the number of correlated orbitals! If you have two correlated atoms in the unit cell that are equivalent, `n_shells` is 2!
- 
-  * `shells`, double list of numpy.int. First dimension: `n_shells`, second dimension: 4. Information about the atomic shells. For each shell, we give a list of 4 numbers: [index, sort, l, dim]. index is the atom index, sort defines the equivalency of the atoms. For instance, with two equivalent atoms in the unit cell, index runs from 0 to 1, but sort can take only one value 0. l is the angular quantum number, and dim the dimension of the atomic shell.
-
-  * `n_corr_shells`, numpy.int. Number of correlated atomic shells, for which correlations are included. This includes atoms which are equivalent by symmetry. If you have two correlated atoms in the unit cell that are equivalent, `n_corr_shells` is 2! 
-
-  * `corr_shells`, double list of numpy.int. First dimension: `n_corr_shells`, second dimension: 6. Information about the correlated orbitals. For each correlated shell, we give a list of 6 numbers: [index, sort, l, dim, SO, irep]. Similar as for `shells`, index is the atom index, sort defines the equivalency of the atoms. For instance, with two equivalent atoms in the unit cell, index runs from 0 to 1, but sort can take only one value 0. l is the angular quantum number, and dim the dimension of the atomic shell. If spin-orbit is included in the calculation, SO is 1, otherwise 0. irep is a dummy integer, set to 0.
-
-  * `use_rotations`, numpy.int. If local and global coordinate systems are used, this falg is set to 1. Otherwise set to 0.
-
-  * `rot_mat`, list of numpy.array.complex. If `use_rotations` is set, then this contains a list of the rotation matrices. You have to give a rotation matrix for each correlated atomic shell, i.e. the length of the list is `n_corr_shells`, the dimension of the matrices is given by the dimension of the atomic shell (c.f. `corr_shells`). You have to give at least the unity matrix, if no rotations are used!
-
-  * `rot_mat_time_inv`, list of numpy.int, length `n_corr_shells`. This is needed only if `SP` is 1. For each correlated shell, set 1 if the coordinate transformation contains inversion, 0 otherwise. If no rotations are used, or `SP` is 0, give a list of zeros. 
-
-  * `n_reps`, numpy.int. Number of irreducible representation of the correlated shell. For instance, if you plan to use the t2g/eg splitting, then set it to 2.
-
-  * `dim_reps`, list of numpy.int, length `n_reps`. Dimension of the representations. In above example, it is [2,3] for eg and t2g sub sets. 
-
-  * `T`, list of numpy.array.complex. For each `inequivalent` correlated shell, this is a general transformation matrix from the spherical harmonics basis to the basis used for the impurity problem, which is most of the time the real cubic harmonics basis. This matrix is used to calculate the 4-index U matrix.
-
-  * `n_orbitals`, numpy.array
-
-  * `proj_mat`, numpy.array
-
-  * `bz_weights`, numpy.array
-
-  * `hopping`, numpy.array
-
-
-
-:program:`Symmetry operations`: In this subgroup we store all the data for applying the symmetry 
-    operations in the DMFT loop (in case you want to use symmetry operations). The default name of this subgroup is `SymmCorr`. 
-
-
-Wien2k Converter
-----------------
-
-As you might expect, wien2triqs comes with a converter to use `Wien2k <http://www.wien2k.at>`_ band structure calculations as input for the DMFT part of the calculation, through the construction of projective Wannier functions. The first step is done by the program :program:`dmftproj`, producing text output files. In the second step, this ouput is read and converted into the hdf5 format, using the python module :class:`Wien2kConverter`.
-
-General and simple H(k) Converter
----------------------------------
-
- 

doc/reference/put_Sigma.rst~

@@ -1,5 +0,0 @@
-
-put_Sigma
-=========
-
-Here comes put Sigma

doc/reference/sumk_lda.rst~

@@ -1,8 +0,0 @@
-
-SumK_LDA
-========
-
-.. toctree::
-   :maxdepth: 1
-
-   analyse_BS

python/build_sigma_from_txt.py

@@ -1,4 +1,11 @@
-    # FIXME MOVE OUT OF HERE! THIS IS TEXT FILE READING!
+    def read_fortran_file (filename):
+        """ Returns a generator that yields all numbers in the Fortran file as float, one by one"""
+        import os.path
+        if not(os.path.exists(filename)) : raise IOError, "File %s does not exist."%filename
+        for line in open(filename,'r') :
+            for x in line.replace('D','E').split() :
+                yield string.atof(x)
+
     def constr_Sigma_real_axis(self, filename, hdf=True, hdf_dataset='SigmaReFreq',n_om=0,orb=0, tol_mesh=1e-6):
         """Uses Data from files to construct Sigma (or GF)  on the real axis."""
 

python/sumk_lda.py

@@ -21,12 +21,12 @@
 ################################################################################
 
 from types import *
-from symmetry import *
 import numpy
 import pytriqs.utility.dichotomy as dichotomy
 from pytriqs.gf.local import *
-from pytriqs.archive import *
 import pytriqs.utility.mpi as mpi
+from pytriqs.archive import *
+from symmetry import *
 
 class SumkLDA:
     """This class provides a general SumK method for combining ab-initio code and pytriqs."""

python/sumk_lda_tools.py

@@ -24,21 +24,9 @@ from types import *
 import numpy
 import pytriqs.utility.dichotomy as dichotomy
 from pytriqs.gf.local import *
-from pytriqs.operators import *
 import pytriqs.utility.mpi as mpi
-from datetime import datetime
 from symmetry import *
 from sumk_lda import SumkLDA
-import string
-
-def read_fortran_file (filename):
-    """ Returns a generator that yields all numbers in the Fortran file as float, one by one"""
-    import os.path
-    if not(os.path.exists(filename)) : raise IOError, "File %s does not exist."%filename
-    for line in open(filename,'r') :
-        for x in line.replace('D','E').split() :
-            yield string.atof(x)
-
 
 class SumkLDATools(SumkLDA):
     """Extends the SumkLDA class with some tools for analysing the data."""
@@ -539,11 +527,8 @@ class SumkLDATools(SumkLDA):
         for ish in xrange(self.n_shells): Gproj[ish].zero()
 
         ikarray=numpy.array(range(self.n_k))
-        #print mpi.rank, mpi.slice_array(ikarray)
-        #print "K-Sum starts on node",mpi.rank," at ",datetime.now()
 
         for ik in mpi.slice_array(ikarray):
-            #print mpi.rank, ik, datetime.now()
             S = self.lattice_gf_matsubara(ik=ik,mu=mu,beta=beta)
             S *= self.bz_weights[ik]
 
@@ -553,17 +538,14 @@ class SumkLDATools(SumkLDA):
                     for sig,gf in tmp: tmp[sig] << self.downfold_pc(ik,ir,ish,sig,S[sig],gf)
                     Gproj[ish] += tmp
 
-        #print "K-Sum done on node",mpi.rank," at ",datetime.now()
         #collect data from mpi:
         for ish in xrange(self.n_shells):
             Gproj[ish] << mpi.all_reduce(mpi.world,Gproj[ish],lambda x,y : x+y)
         mpi.barrier()
 
-        #print "Data collected on node",mpi.rank," at ",datetime.now()
 
         # Symmetrisation:
         if (self.symm_op!=0): Gproj = self.Symm_par.symmetrize(Gproj)
-        #print "Symmetrisation done on node",mpi.rank," at ",datetime.now()
 
         for ish in xrange(self.n_shells):