PAOFLOW.utils.get_K_grid_fft#

Functions#

get_K_grid_fft(data_controller)

Build the Cartesian k-grid and uniform k-point weights from the FFT mesh.

get_K_grid_fft_crystal(nk1, nk2, nk3)

Build the k-grid in reduced crystal coordinates.

Module Contents#

PAOFLOW.utils.get_K_grid_fft.get_K_grid_fft(data_controller)[source]#

Build the Cartesian k-grid and uniform k-point weights from the FFT mesh.

Parameters:

data_controller (DataController) – Object providing data_arrays and data_attributes. Required arrays: b_vectors (shape (3, 3)). Required attributes: nk1, nk2, nk3.

Returns:

Adds the following entries to data_controller.data_arrays:

  • kgrid : np.ndarray, shape (3, nktot) — Cartesian k-coordinates (in units of \(2\pi/a\)) of all nktot = nk1*nk2*nk3 grid points, centred around \(\Gamma\) (folded into \([-0.5, 0.5)\)).

  • kq_wght : np.ndarray, shape (nktot,) — uniform k-point weights, each equal to 1 / nktot.

Return type:

None

PAOFLOW.utils.get_K_grid_fft.get_K_grid_fft_crystal(nk1, nk2, nk3)[source]#

Build the k-grid in reduced crystal coordinates.

Parameters:

  • nk1 (int) – Number of k-points along the first reciprocal-lattice vector.

  • nk2 (int) – Number of k-points along the second reciprocal-lattice vector.

  • nk3 (int) – Number of k-points along the third reciprocal-lattice vector.

Returns:

k-coordinates in reduced crystal units, centred around \(\Gamma\) (each component folded into \([-0.5, 0.5)\)).

Return type:

np.ndarray, shape (nk1*nk2*nk3, 3), float