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Restructured 'orthogonalization()'

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The part responsible for generating a mapping between the shell/ions
and block projector matrices has now been relocated to a separate
method 'get_block_matrix_map()'. This simplifies the source code
and makes testing easier.
This commit is contained in:
Oleg E. Peil 2015-11-19 14:48:45 +01:00
parent c426946803
commit 72d030c5c5
1 changed files with 49 additions and 30 deletions
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79
python/vasp/proj_group.py
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@ -92,6 +92,52 @@ class ProjectorGroup:
projector arrays. Note that the blocks can comprise several projector arrays
contained in different projector shells.
The construction of block maps is performed in 'self.get_block_matrix_map()'.
"""
# Quick exit if no normalization is requested
if not self.ortho:
return
block_maps, ndim = self.get_block_matrix_map()
p_mat = np.zeros((ndim, nb_max), dtype=np.complex128)
# Note that 'ns' and 'nk' are the same for all shells
for isp in xrange(ns):
for ik in xrange(nk):
nb = self.ib_win[ik, isp, 1] - self.ib_win[ik, isp, 0] + 1
# Combine all projectors of the group to one block projector
for bl_map in block_maps:
p_mat[:, :] = 0.0j # !!! Clean-up from the last k-point and block!
for ibl, block in enumerate(bl_map):
i1, i2 = block['bmat_range']
ish, ion = block['shell_ion']
shell = self.shells[ish]
p_mat[i1:i2, :nb] = shell.proj_win[ion, isp, ik, :nlm, :nb]
# Now orthogonalize the obtained block projector
ibl_max = i2
p_orth, overl, eig = self.orthogonalize_projector_matrix(p_mat[:ibl_max, :nb])
# Distribute projectors back using the same mapping
for ibl, block in enumerate(bl_map):
i1, i2 = block['bmat_range']
ish, ion = block['shell_ion']
shell = self.shells[ish]
shell.proj_win[ion, isp, ik, :nlm, :nb] = p_orth[i1:i2, :nb]
################################################################################
#
# gen_block_matrix_map
#
################################################################################
def get_block_matrix_map(self):
"""
Generates a map from a set of projectors belonging to different shells
and ions onto a set of block projector matrices, each of which is
orthonormalized.
Returns the map and the maximum orbital dimension of the block projector
matrix.
Mapping is defined as a list of 'block_maps' corresponding to subsets
of projectors to be orthogonalized. Each subset corresponds to a subset of sites
and spans all orbital indices. defined by 'bl_map' as
@ -129,15 +175,9 @@ class ProjectorGroup:
((i2_start, i2_end), (i2_shell, i2_shell.ion1)),
((i2_start, i2_end), (i2_shell, i2_shell.ion2)),
...],
"""
# Quick exit if no normalization is requested
if not self.ortho:
return
# Determine the dimension of the projector matrix
# and map the blocks to the big matrix
if self.normion:
# Projectors for each site are mapped onto a separate block matrix
block_maps = []
ndim = 0
for ish in self.ishells:
@ -153,6 +193,7 @@ class ProjectorGroup:
block_maps.append(bl_map)
else:
# All projectors within a group are combined into one big block matrix
block_maps = []
bl_map = []
i1_bl = 0
@ -169,29 +210,7 @@ class ProjectorGroup:
ndim = i2_bl
block_maps.append(bl_map)
print block_maps
p_mat = np.zeros((ndim, nb_max), dtype=np.complex128)
# Note that 'ns' and 'nk' are the same for all shells
for isp in xrange(ns):
for ik in xrange(nk):
nb = self.ib_win[ik, isp, 1] - self.ib_win[ik, isp, 0] + 1
# Combine all projectors of the group to one block projector
for bl_map in block_maps:
p_mat[:, :] = 0.0j # !!! Clean-up from the last k-point and block!
for ibl, block in enumerate(bl_map):
i1, i2 = block['bmat_range']
ish, ion = block['shell_ion']
shell = self.shells[ish]
p_mat[i1:i2, :nb] = shell.proj_win[ion, isp, ik, :nlm, :nb]
# Now orthogonalize the obtained block projector
ibl_max = i2
p_orth, overl, eig = self.orthogonalize_projector_matrix(p_mat[:ibl_max, :nb])
# Distribute projectors back using the same mapping
for ibl, block in enumerate(bl_map):
i1, i2 = block['bmat_range']
ish, ion = block['shell_ion']
shell = self.shells[ish]
shell.proj_win[ion, isp, ik, :nlm, :nb] = p_orth[i1:i2, :nb]
return block_maps, ndim
################################################################################
#