Source code for sisl.physics.energydensitymatrix

# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at https://mozilla.org/MPL/2.0/.
from __future__ import annotations

import numpy as np

import sisl._array as _a
from sisl._internal import set_module
from sisl.messages import SislError
from sisl.typing import GaugeType

from .densitymatrix import _densitymatrix

__all__ = ["EnergyDensityMatrix"]


@set_module("sisl.physics")
class EnergyDensityMatrix(_densitymatrix):
    """Sparse energy density matrix object

    Assigning or changing elements is as easy as with standard `numpy` assignments:

    >>> EDM = EnergyDensityMatrix(...)
    >>> EDM.E[1,2] = 0.1

    which assigns 0.1 as the density element between orbital 2 and 3.
    (remember that Python is 0-based elements).

    For spin matrices the elements are defined with an extra dimension.

    For a polarized matrix:

    >>> M = EnergyDensityMatrix(..., spin="polarized")
    >>> M[0, 0, 0] = # onsite spin up
    >>> M[0, 0, 1] = # onsite spin down

    For non-colinear the indices are a bit more tricky:

    >>> M = EnergyDensityMatrix(..., spin="non-colinear")
    >>> M[0, 0, M.M11] = # Re(up-up)
    >>> M[0, 0, M.M22] = # Re(down-down)
    >>> M[0, 0, M.M12r] = # Re(up-down)
    >>> M[0, 0, M.M12i] = # Im(up-down)

    For spin-orbit it looks like this:

    >>> M = EnergyDensityMatrix(..., spin="spin-orbit")
    >>> M[0, 0, M.M11r] = # Re(up-up)
    >>> M[0, 0, M.M11i] = # Im(up-up)
    >>> M[0, 0, M.M22r] = # Re(down-down)
    >>> M[0, 0, M.M22i] = # Im(down-down)
    >>> M[0, 0, M.M12r] = # Re(up-down)
    >>> M[0, 0, M.M12i] = # Im(up-down)
    >>> M[0, 0, M.M21r] = # Re(down-up)
    >>> M[0, 0, M.M21i] = # Im(down-up)

    Thus the number of *orbitals* is unchanged but a sub-block exists for
    the spin-block.

    When transferring the matrix to a k-point the spin-box is local to each
    orbital, meaning that the spin-box for orbital i will be:

    >>> Ek = M.Ek()
    >>> Ek[i*2:(i+1)*2, i*2:(i+1)*2]

    Parameters
    ----------
    geometry : Geometry
      parent geometry to create a energy density matrix from. The energy density matrix will
      have size equivalent to the number of orbitals in the geometry
    dim : int or Spin, optional
      number of components per element, may be a `Spin` object
    dtype : np.dtype, optional
      data type contained in the energy density matrix. See details of `Spin` for default values.
    nnzpr : int, optional
      number of initially allocated memory per orbital in the energy density matrix.
      For increased performance this should be larger than the actual number of entries
      per orbital.
    spin : Spin, optional
      equivalent to `dim` argument. This keyword-only argument has precedence over `dim`.
    orthogonal : bool, optional
      whether the energy density matrix corresponds to a non-orthogonal basis. In this case
      the dimensionality of the energy density matrix is one more than `dim`.
      This is a keyword-only argument.
    """

[docs] def __init__(self, geometry, dim=1, dtype=None, nnzpr=None, **kwargs): super().__init__(geometry, dim, dtype, nnzpr, **kwargs) self._reset()
def _reset(self): super()._reset() self.Ek = self.Pk self.dEk = self.dPk self.ddEk = self.ddPk @property def E(self): r"""Access the energy density matrix elements""" self._def_dim = self.UP return self
[docs] def Ek( self, k=(0, 0, 0), dtype=None, gauge: GaugeType = "cell", format="csr", *args, **kwargs, ): r"""Setup the energy density matrix for a given k-point Creation and return of the energy density matrix for a given k-point (default to Gamma). Notes ----- Currently the implemented gauge for the k-point is the cell vector gauge: .. math:: \mathbf E(\mathbf k) = \mathbf E_{ij} e^{i\mathbf k\cdot\mathbf R} where :math:`\mathbf R` is an integer times the cell vector and :math:`i`, :math:`j` are orbital indices. Another possible gauge is the orbital distance which can be written as .. math:: \mathbf E(\mathbf k) = \mathbf E_{ij} e^{i\mathbf k\cdot\mathbf r} where :math:`\mathbf r` is the distance between the orbitals. Parameters ---------- k : array_like the k-point to setup the energy density matrix at dtype : numpy.dtype , optional the data type of the returned matrix. Do NOT request non-complex data-type for non-Gamma k. The default data-type is `numpy.complex128` gauge : {'cell', 'orbital'} the chosen gauge, `cell` for cell vector gauge, and `orbital` for orbital distance gauge. format : {'csr', 'array', 'dense', 'coo', ...} the returned format of the matrix, defaulting to the `scipy.sparse.csr_matrix`, however if one always requires operations on dense matrices, one can always return in `numpy.ndarray` (`'array'`/`'dense'`/`'matrix'`). Prefixing with 'sc:', or simply 'sc' returns the matrix in supercell format with phases. spin : int, optional if the energy density matrix is a spin polarized one can extract the specific spin direction matrix by passing an integer (0 or 1). If the energy density matrix is not `Spin.POLARIZED` this keyword is ignored. See Also -------- dEk : Energy density matrix derivative with respect to `k` ddEk : Energy density matrix double derivative with respect to `k` Returns ------- matrix : numpy.ndarray or scipy.sparse.*_matrix the energy density matrix at :math:`\mathbf k`. The returned object depends on `format`. """ pass
[docs] def dEk( self, k=(0, 0, 0), dtype=None, gauge: GaugeType = "cell", format="csr", *args, **kwargs, ): r"""Setup the energy density matrix derivative for a given k-point Creation and return of the energy density matrix derivative for a given k-point (default to Gamma). Notes ----- Currently the implemented gauge for the k-point is the cell vector gauge: .. math:: \nabla_{\mathbf k} \mathbf E_\alpha(\mathbf k) = i\mathbf R_\alpha \mathbf E_{ij} e^{i\mathbf k\cdot\mathbf R} where :math:`\mathbf R` is an integer times the cell vector and :math:`i`, :math:`j` are orbital indices. And :math:`\alpha` is one of the Cartesian directions. Another possible gauge is the orbital distance which can be written as .. math:: \nabla_{\mathbf k} \mathbf E_\alpha(\mathbf k) = i\mathbf r_\alpha \mathbf E_{ij} e^{i\mathbf k\cdot\mathbf r} where :math:`\mathbf r` is the distance between the orbitals. Parameters ---------- k : array_like the k-point to setup the energy density matrix at dtype : numpy.dtype , optional the data type of the returned matrix. Do NOT request non-complex data-type for non-Gamma k. The default data-type is `numpy.complex128` gauge : {'cell', 'orbital'} the chosen gauge, `cell` for cell vector gauge, and `orbital` for orbital distance gauge. format : {'csr', 'array', 'dense', 'coo', ...} the returned format of the matrix, defaulting to the `scipy.sparse.csr_matrix`, however if one always requires operations on dense matrices, one can always return in `numpy.ndarray` (`'array'`/`'dense'`/`'matrix'`). spin : int, optional if the energy density matrix is a spin polarized one can extract the specific spin direction matrix by passing an integer (0 or 1). If the energy density matrix is not `Spin.POLARIZED` this keyword is ignored. See Also -------- Ek : Energy density matrix with respect to `k` ddEk : Energy density matrix double derivative with respect to `k` Returns ------- tuple for each of the Cartesian directions a :math:`\partial \mathbf E(\mathbf k)/\partial\mathbf k` is returned. """ pass
[docs] def ddEk( self, k=(0, 0, 0), dtype=None, gauge: GaugeType = "cell", format="csr", *args, **kwargs, ): r"""Setup the energy density matrix double derivative for a given k-point Creation and return of the energy density matrix double derivative for a given k-point (default to Gamma). Notes ----- Currently the implemented gauge for the k-point is the cell vector gauge: .. math:: \nabla_{\mathbf k^2} \mathbf E_{\alpha\beta}(\mathbf k) = -\mathbf R_\alpha\mathbf R_\beta \mathbf E_{ij} e^{i\mathbf k\cdot\mathbf R} where :math:`\mathbf R` is an integer times the cell vector and :math:`i`, :math:`j` are orbital indices. And :math:`\alpha` and :math:`\beta` are one of the Cartesian directions. Another possible gauge is the orbital distance which can be written as .. math:: \nabla_{\mathbf k^2} \mathbf E_{\alpha\beta}(\mathbf k) = -\mathbf r_\alpha\mathbf r_\beta \mathbf E_{ij} e^{i\mathbf k\cdot\mathbf r} where :math:`\mathbf r` is the distance between the orbitals. Parameters ---------- k : array_like the k-point to setup the energy density matrix at dtype : numpy.dtype , optional the data type of the returned matrix. Do NOT request non-complex data-type for non-Gamma k. The default data-type is `numpy.complex128` gauge : {'cell', 'orbital'} the chosen gauge, `cell` for cell vector gauge, and `orbital` for orbital distance gauge. format : {'csr', 'array', 'dense', 'coo', ...} the returned format of the matrix, defaulting to the `scipy.sparse.csr_matrix`, however if one always requires operations on dense matrices, one can always return in `numpy.ndarray` (`'array'`/`'dense'`/`'matrix'`). spin : int, optional if the energy density matrix is a spin polarized one can extract the specific spin direction matrix by passing an integer (0 or 1). If the energy density matrix is not `Spin.POLARIZED` this keyword is ignored. See Also -------- Ek : Energy density matrix with respect to `k` dEk : Energy density matrix derivative with respect to `k` Returns ------- list of matrices for each of the Cartesian directions (in Voigt representation); xx, yy, zz, zy, xz, xy """ pass
[docs] def shift(self, E, DM): r"""Shift the energy density matrix to a common energy by using a reference density matrix This is equal to performing this operation: .. math:: \mathfrak E_\sigma = \mathfrak E_\sigma + E \boldsymbol \rho_\sigma where :math:`\mathfrak E_\sigma` correspond to the spin diagonal components of the energy density matrix and :math:`\boldsymbol \rho_\sigma` is the spin diagonal components of the corresponding density matrix. Parameters ---------- E : float or (2,) the energy (in eV) to shift the energy density matrix, if two values are passed the two first spin-components get shifted individually. DM : DensityMatrix density matrix corresponding to the same geometry """ if not self.spsame(DM): raise SislError( f"{self.__class__.__name__}.shift requires the input DM to have " "the same sparsity as the shifted object." ) E = _a.asarrayd(E) if E.size == 1: E = np.tile(E, 2) if np.abs(E).sum() == 0.0: # When the energy is zero, there is no shift return for i in range(self.spin.spinor): self._csr._D[:, i] += DM._csr._D[:, i] * E[i]
[docs] @staticmethod def read(sile, *args, **kwargs): """Reads density matrix from `Sile` using `read_energy_density_matrix`. Parameters ---------- sile : Sile, str or pathlib.Path a `Sile` object which will be used to read the density matrix and the overlap matrix (if any) if it is a string it will create a new sile using `get_sile`. * : args passed directly to ``read_energy_density_matrix(,**)`` """ # This only works because, they *must* # have been imported previously from sisl.io import BaseSile, get_sile if isinstance(sile, BaseSile): return sile.read_energy_density_matrix(*args, **kwargs) else: with get_sile(sile, mode="r") as fh: return fh.read_energy_density_matrix(*args, **kwargs)