LCPQ/dft_tools
3
0
Fork 0
mirror of https://github.com/triqs/dft_tools synced 2024-12-23 04:43:42 +01:00
Code Issues Releases Wiki Activity

Merge branch 'unstable' into py3

Browse Source 
merge latest commit de163cce03 for
enhanced warning for set_Sigma if ReFreqMesh is too small into py3
This commit is contained in:
Alexander Hampel 2020-06-23 11:24:08 +02:00
commit 9d94c78cba
1 changed files with 24 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

24
python/triqs_dft_tools/sumk_dft.py
View File

@ -165,6 +165,9 @@ class SumkDFT(object):
if use_dft_blocks: if use_dft_blocks:
self.analyse_block_structure() self.analyse_block_structure()
self.min_band_energy = None
self.max_band_energy = None
################ ################
# hdf5 FUNCTIONS # hdf5 FUNCTIONS
################ ################
@ -639,6 +642,15 @@ class SumkDFT(object):
else: else:
gf << Sigma_imp[icrsh][bname] gf << Sigma_imp[icrsh][bname]
#warning if real frequency self energy is within the bounds of the band energies
if isinstance(Sigma_imp[0].mesh, MeshReFreq):
if self.min_band_energy is None or self.max_band_energy is None:
self.calculate_min_max_band_energies()
for gf in Sigma_imp:
Sigma_mesh = numpy.array([i for i in gf.mesh.values()])
if Sigma_mesh[0] > (self.min_band_energy - self.chemical_potential) or Sigma_mesh[-1] < (self.max_band_energy - self.chemical_potential):
warn('The given Sigma is on a mesh which does not cover the band energy range. The Sigma MeshReFreq runs from %f to %f, while the band energy (minus the chemical potential) runs from %f to %f'%(Sigma_mesh[0], Sigma_mesh[-1], self.min_band_energy, self.max_band_energy))
def transform_to_sumk_blocks(self, Sigma_imp, Sigma_out=None): def transform_to_sumk_blocks(self, Sigma_imp, Sigma_out=None):
r""" transform Sigma from solver to sumk space r""" transform Sigma from solver to sumk space
@ -2144,6 +2156,18 @@ class SumkDFT(object):
return res return res
def calculate_min_max_band_energies(self):
hop = self.hopping
diag_hop = numpy.zeros(hop.shape[:-1])
hop_slice = mpi.slice_array(hop)
diag_hop_slice = mpi.slice_array(diag_hop)
diag_hop_slice[:] = numpy.linalg.eigvalsh(hop_slice)
diag_hop = mpi.all_reduce(mpi.world, diag_hop, lambda x, y: x + y)
min_band_energy = diag_hop.min().real
max_band_energy = diag_hop.max().real
self.min_band_energy = min_band_energy
self.max_band_energy = max_band_energy
return min_band_energy, max_band_energy
################ ################
# FIXME LEAVE UNDOCUMENTED # FIXME LEAVE UNDOCUMENTED