mirror of
https://github.com/triqs/dft_tools
synced 2024-07-12 06:13:49 +02:00
d794bfa0f5
Added function 'ctrl_ouput()' which stores data common for all correlated shells into a file '<basename>.ctrl'. At the moment, only a very basic header is output. The signature of 'plo_output()' is also modified to include an instance of class 'ElectronicStructre' containing important information on the lattice structure, Efermi, and k-points.
437 lines
14 KiB
Python
437 lines
14 KiB
Python
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import itertools as it
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import numpy as np
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# 'simplejson' is supposed to be faster than 'json' in stdlib.
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import simplejson as json
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class Projector:
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"""
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Class describing a local-orbital projector.
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"""
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def __init__(self, matrix, ib1=1, ib2=None, nion=1):
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self.p_matrix = matrix.astype(np.complex128)
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self.norb, self.nb = matrix.shape
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self.nion = nion
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self.ib1 = ib1 - 1
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if not ib2 is None:
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self.ib2 = ib2 - 1
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else:
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self.ib2 = self.nb - 1
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def project_up(self, mat):
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return np.dot(self.p_matrix.conj().T, np.dot(mat, self.p_matrix))
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def project_down(self, mat):
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assert mat.shape == (self.nb, self.nb), " Matrix must match projector in size"
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return np.dot(self.p_matrix, np.dot(mat, self.p_matrix.conj().T))
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def orthogonalize(self):
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"""
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Orthogonalizes a projector.
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Returns an overlap matrix and its eigenvalues for initial projectors.
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"""
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self.p_matrix, overlap, over_eig = orthogonalize_projector(self.p_matrix)
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return (overlap, over_eig)
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################################################################################
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#
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# orthogonalize_projector_matrix()
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#
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################################################################################
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def orthogonalize_projector_matrix(p_matrix):
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"""
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Orthogonalizes a projector defined by a rectangular matrix `p_matrix`.
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Parameters
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----------
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p_matrix (numpy.array[complex]) : matrix `Nm x Nb`, where `Nm` is
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the number of orbitals, `Nb` number of bands
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Returns
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-------
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Orthogonalized projector matrix, initial overlap matrix and its eigenvalues.
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"""
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# Overlap matrix O_{m m'} = \sum_{v} P_{m v} P^{*}_{v m'}
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overlap = np.dot(p_matrix, p_matrix.conj().T)
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# Calculate [O^{-1/2}]_{m m'}
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eig, eigv = np.linalg.eigh(overlap)
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assert np.all(eig > 0.0), ("Negative eigenvalues of the overlap matrix:"
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"projectors are ill-defined")
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sqrt_eig = np.diag(1.0 / np.sqrt(eig))
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shalf = np.dot(eigv, np.dot(sqrt_eig, eigv.conj().T))
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# Apply \tilde{P}_{m v} = \sum_{m'} [O^{-1/2}]_{m m'} P_{m' v}
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p_ortho = np.dot(shalf, p_matrix)
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return (p_ortho, overlap, eig)
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################################################################################
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# check_data_consistency()
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################################################################################
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def check_data_consistency(pars, el_struct):
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"""
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Check the consistency of the VASP data.
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"""
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pass
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################################################################################
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# select_bands()
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################################################################################
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def select_bands(eigvals, emin, emax):
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"""
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Select a subset of bands lying within a given energy window.
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The band energies are assumed to be sorted in an ascending order.
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Parameters
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----------
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eigvals (numpy.array) : all eigenvalues
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emin, emax (float) : energy window
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Returns
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-------
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ib_win, nb_min, nb_max :
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"""
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# Sanity check
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if emin > eigvals.max() or emax < eigvals.min():
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raise Exception("Energy window does not overlap with the band structure")
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nk, nband, ns_band = eigvals.shape
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ib_win = np.zeros((nk, ns_band, 2), dtype=np.int32)
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nb_min = 10000000
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nb_max = 0
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for isp in xrange(ns_band):
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for ik in xrange(nk):
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for ib in xrange(nband):
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en = eigvals[ik, ib, isp]
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if en >= emin:
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break
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ib1 = ib
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for ib in xrange(ib1, nband):
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en = eigvals[ik, ib, isp]
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if en > emax:
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break
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else:
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# If we reached the last band add 1 to get the correct bound
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ib += 1
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ib2 = ib - 1
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ib_win[ik, isp, 0] = ib1
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ib_win[ik, isp, 1] = ib2
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nb_min = min(nb_min, ib1)
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nb_max = max(nb_max, ib2)
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return ib_win, nb_min, nb_max
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################################################################################
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################################################################################
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#
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# class ProjectorGroup
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#
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################################################################################
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################################################################################
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class ProjectorGroup:
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"""
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Container of projectors defined within a certain energy window.
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The constructor selects a subset of projectors according to
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the parameters from the config-file (passed in `pars`).
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Parameters:
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- gr_pars (dict) : group parameters from the config-file
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- shells ([ProjectorShell]) : array of ProjectorShell objects
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- eigvals (numpy.array) : array of KS eigenvalues
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"""
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def __init__(self, gr_pars, shells, eigvals):
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"""
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Constructor
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"""
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self.emin = gr_pars['emin']
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self.emax = gr_pars['emax']
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self.ishells = gr_pars['shells']
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self.ortho = gr_pars['normalize']
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self.normion = gr_pars['normion']
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self.shells = shells
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# Determine the minimum and maximum band numbers
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ib_win, nb_min, nb_max = select_bands(eigvals, self.emin, self.emax)
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self.ib_win = ib_win
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self.nb_min = nb_min
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self.nb_max = nb_max
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# Select projectors within the energy window
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for ish in self.ishells:
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shell = self.shells[ish]
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shell.select_projectors(ib_win, nb_min, nb_max)
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################################################################################
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#
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# orthogonalize
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#
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################################################################################
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def orthogonalize(self):
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"""
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Orthogonalize a group of projectors.
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"""
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# Quick exit if no normalization is requested
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if not self.ortho:
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return
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# TODO: add the case of 'normion = True'
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assert not self.normion, "'NORMION = True' is not yet implemented"
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# Determine the dimension of the projector matrix
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# and map the blocks to the big matrix
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i1_bl = 0
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bl_map = [{} for ish in self.ishells]
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for ish in self.ishells:
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_shell = self.shells[ish]
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nion, ns, nk, nlm, nb_max = _shell.proj_win.shape
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bmat_bl = [] # indices corresponding to a big block matrix
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for ion in xrange(nion):
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i2_bl = i1_bl + nlm
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bmat_bl.append((i1_bl, i2_bl))
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i1_bl = i2_bl
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bl_map[ish]['bmat_blocks'] = bmat_bl
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ndim = i2_bl
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p_mat = np.zeros((ndim, nb_max), dtype=np.complex128)
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for isp in xrange(ns):
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for ik in xrange(nk):
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nb = self.ib_win[ik, isp, 1] - self.ib_win[ik, isp, 0] + 1
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# Combine all projectors of the group to one block projector
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for ish in self.ishells:
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shell = self.shells[ish]
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blocks = bl_map[ish]['bmat_blocks']
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for ion in xrange(nion):
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i1, i2 = blocks[ion]
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p_mat[i1:i2, :nb] = shell.proj_win[ion, isp, ik, :nlm, :nb]
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# Now orthogonalize the obtained block projector
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p_orth, overl, eig = orthogonalize_projector_matrix(p_mat)
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# Distribute back projectors in the same order
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for ish in self.ishells:
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shell = self.shells[ish]
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blocks = bl_map[ish]['bmat_blocks']
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for ion in xrange(nion):
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i1, i2 = blocks[ion]
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shell.proj_win[ion, isp, ik, :nlm, :nb] = p_mat[i1:i2, :nb]
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################################################################################
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################################################################################
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#
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# class ProjectorShell
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#
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################################################################################
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################################################################################
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class ProjectorShell:
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"""
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Container of projectors related to a specific shell.
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The constructor pre-selects a subset of projectors according to
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the shell parameters passed from the config-file.
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Parameters:
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- sh_pars (dict) : shell parameters from the config-file
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- proj_raw (numpy.array) : array of raw projectors
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"""
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def __init__(self, sh_pars, proj_raw):
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self.lorb = sh_pars['lshell']
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self.ion_list = sh_pars['ion_list']
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try:
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self.tmatrix = sh_pars['tmatrix']
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except KeyError:
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self.tmatrix = None
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self.lm1 = self.lorb**2
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self.lm2 = (self.lorb+1)**2
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# Pre-select a subset of projectors (this should be an array view => no memory is wasted)
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# !!! This sucks but I have to change the order of 'ib' and 'ilm' indices here
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# This should perhaps be done right after the projector array is read from PLOCAR
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self.proj_arr = proj_raw[self.ion_list, :, :, :, self.lm1:self.lm2].transpose((0, 1, 2, 4, 3))
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################################################################################
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#
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# select_projectors
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#
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################################################################################
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def select_projectors(self, ib_win, nb_min, nb_max):
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"""
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Selects a subset of projectors corresponding to a given energy window.
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"""
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self.ib_win = ib_win
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self.nb_min = nb_min
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self.nb_max = nb_max
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# Set the dimensions of the array
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nb_win = self.nb_max - self.nb_min + 1
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nion, ns, nk, nlm, nbtot = self.proj_arr.shape
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# !!! Note that the order of the two last indices is different !!!
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self.proj_win = np.zeros((nion, ns, nk, nlm, nb_win), dtype=np.complex128)
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# Select projectors for a given energy window
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ns_band = self.ib_win.shape[1]
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for isp in xrange(ns):
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for ik in xrange(nk):
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# TODO: for non-collinear case something else should be done here
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is_b = min(isp, ns_band)
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ib1 = self.ib_win[ik, is_b, 0]
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ib2 = self.ib_win[ik, is_b, 1] + 1
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ib1_win = ib1 - self.nb_min
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ib2_win = ib2 - self.nb_min
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self.proj_win[:, isp, ik, :, ib1_win:ib2_win] = self.proj_arr[:, isp, ik, :, ib1:ib2]
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################################################################################
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#
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# select_projectors
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#
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################################################################################
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def density_matrix(self, el_struct, site_diag=True, spin_diag=True):
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"""
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Returns occupation matrix/matrices for the shell.
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"""
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nion, ns, nk, nlm, nbtot = self.proj_win.shape
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assert site_diag, "site_diag = False is not implemented"
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assert spin_diag, "spin_diag = False is not implemented"
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occ_mats = np.zeros((ns, nion, nlm, nlm), dtype=np.float64)
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kweights = el_struct.kmesh['kweights']
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occnums = el_struct.ferw
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ib1 = self.nb_min
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ib2 = self.nb_max + 1
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for isp in xrange(ns):
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for ik, weight, occ in it.izip(it.count(), kweights, occnums[isp, :, :]):
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for io in xrange(nion):
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proj_k = self.proj_win[isp, io, ik, ...]
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occ_mats[isp, io, :, :] += np.dot(proj_k * occ[ib1:ib2],
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proj_k.conj().T).real * weight
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# if not symops is None:
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# occ_mats = symmetrize_matrix_set(occ_mats, symops, ions, perm_map)
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return occ_mats
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################################################################################
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#
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# generate_ortho_plos
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#
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################################################################################
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def generate_ortho_plos(conf_pars, el_struct):
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"""
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Parameters
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----------
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conf_pars (dict) : dictionary of input parameters (from conf-file)
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el_struct : ElectronicStructure object
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"""
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check_data_consistency(conf_pars, el_struct)
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proj_raw = el_struct.proj_raw
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try:
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efermi = conf_pars.general['efermi']
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except (KeyError, AttributeError):
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efermi = el_struct.efermi
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# eigvals(nktot, nband, ispin) are defined with respect to the Fermi level
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eigvals = el_struct.eigvals - efermi
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pshells = []
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for sh_par in conf_pars.shells:
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pshells.append(ProjectorShell(sh_par, proj_raw))
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pgroups = []
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for gr_par in conf_pars.groups:
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pgroup = ProjectorGroup(gr_par, pshells, eigvals)
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pgroup.orthogonalize()
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pgroups.append(pgroup)
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return pshells, pgroups
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################################################################################
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#
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# ctrl_output
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#
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################################################################################
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def ctrl_output(conf_pars, el_struct, ng):
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"""
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Outputs a ctrl-file.
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"""
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ctrl_fname = conf_pars.general['basename'] + '.ctrl'
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head_dict = {}
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# Construct the header dictionary
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head_dict['ngroups'] = ng
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head_dict['nk'] = el_struct.kmesh['nktot']
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head_dict['ns'] = el_struct.nspin
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head_dict['nc_flag'] = 1 if el_struct.nc_flag else 0
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# head_dict['efermi'] = conf_pars.general['efermi'] # We probably don't need Efermi
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header = json.dumps(head_dict, indent=4, separators=(',', ': '))
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with open(ctrl_fname, 'wt') as f:
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f.write(header)
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################################################################################
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#
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# plo_output
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#
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################################################################################
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# TODO: k-points with weights should be stored once and for all
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def plo_output(conf_pars, el_struct, pshells, pgroups):
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"""
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Outputs PLO groups into text files.
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Filenames are defined by <basename> that is passed from config-file.
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All necessary general parameters are stored in a file '<basename>.ctrl'.
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Each group is stored in a '<basename>.plog<Ng>' file. The format is the
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following:
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# Energy window: emin, emax
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ib_min, ib_max
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# Eigenvalues
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ik1, kx, ky, kz, kweight
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ib1, ib2
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eig1
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eig2
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...
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eigN
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ik2, kx, ky, kz, kweight
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...
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# Projected shells
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Nshells
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# Shells: <shell indices>
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# Shell <1>
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Shell 1
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ndim
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# complex arrays: plo(ns, nion, ndim, nb)
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...
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# Shells: <shell indices>
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# Shell <2>
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Shell 2
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...
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"""
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ctrl_output(conf_pars, el_struct, len(pgroups))
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