grid¶

Module author: Adam Gagorik <adam.gagorik@gmail.com>

class grid.Grid(xsize, ysize, zsize)[source]¶

A class to represent the Langmuir simulation lattice. Alternate contructors exist.

Parameters:	xsize (int) – x points ysize (int) – y points zsize (int) – z points

classmethod from_checkpoint(chk)[source]¶

Create grid instance from checkpoint file.

Parameters:	chk – checkpoint filename or object

>>> grid = lm.grid.Grid.from_checkpoint('out.chk')

create_zeros()[source]¶

Compute a grid of zeros.

parameters()[source]¶

Return a langmuir.parameters.Parameters.

refine(factor=0)[source]¶

Refines the mesh. If factor=0 or dx/factor > 1.0, the mesh is reset to the default spacing of 1.0.

Parameters:	factor (float) – zoom factor; > 0 refines the mesh, < 0 zooms out.

class grid.IndexMapper(grid)[source]¶

A class that maps between site indicies the Langmuir way.

>>> grid = lm.grid.Grid(10, 10, 10)
>>> imap = lm.grid.IndexMapper(grid)

indexS(x_index, y_index, z_index)[source]¶

Compute (Langmuir’s) site index from x, y, and z index

Parameters:	x_index (int) – x-site y_index (int) – y-site z_index (int) – z-site

>>> grid = lm.grid.Grid(10, 10, 10)
>>> imap = lm.grid.IndexMapper(grid)
>>> s = imap.indexS(0, 0, 0)

indexX(s_index)[source]¶

Compute (Langmuir’s) x index from site index

Parameters:	s_index (int) – site index

>>> grid = lm.grid.Grid(10, 10, 10)
>>> imap = lm.grid.IndexMapper(grid)
>>> x = imap.indexX(10)

indexY(s_index)[source]¶

Compute (Langmuir’s) y index from site index

Parameters:	s_index (int) – site index

>>> grid = lm.grid.Grid(10, 10, 10)
>>> imap = lm.grid.IndexMapper(grid)
>>> y = imap.indexX(10)

indexZ(s_index)[source]¶

Compute (Langmuir’s) z index from site index

Parameters:	s_index (int) – site index

>>> grid = lm.grid.Grid(10, 10, 10)
>>> imap = lm.grid.IndexMapper(grid)
>>> z = imap.indexX(10)

class grid.XYZV(grid, s, v=None)[source]¶

Put site values on a mesh using site ids.

Parameters:	grid (Grid) – grid object s (list) – site indcies v (list or scalar) – site values

>>> chk  = lm.checkpoint.load('out.chk')
>>> grid = lm.grid.Grid.from_checkpoint(chk)
>>> xyzv = lm.grid.XYZV(grid, chk.electrons, -1)

class grid.PrecalculatedMesh(grid)[source]¶

Perform fast computation of Coulomb interactions and distances with a precomputed mesh.

Parameters:	grid (Grid) – grid object

>>> grid = lm.grid.Grid(5, 5, 5)
>>> mesh = lm.grid.PrecalculatedMesh(grid)

coulomb(xi_ids, yi_ids, zi_ids, xj_ids=None, yj_ids=None, zj_ids=None, q=1)[source]¶

Compute coulomb interaction at j’s due to charges at i’s. If no j’s are passed, then the answer will be computed at every mesh point (expensive!)’

Parameters:	xi_ids (list, int) – charge x-position(s) yi_ids (list, int) – charge y-position(s) zi_ids (list, int) – charge z-position(s) xj_ids – energy x-position(s) yj_ids – energy y-position(s) zj_ids – energy z-position(s) q (int, float) – charge

>>> grid = lm.grid.Grid(10, 10, 10)
>>> mesh = lm.grid.PrecalculatedMesh(grid)
>>> coul = mesh.coulomb(0, 0, 0, 1, 1, 1, -1)

distances(xi_ids, yi_ids, zi_ids, xj_ids=None, yj_ids=None, zj_ids=None)[source]¶

Compute all distances between i’s, or compute all distances between i’s and j’s

Parameters:	xi_ids (list, int) – initial x-position(s) yi_ids (list, int) – initial y-position(s) zi_ids (list, int) – initial z-position(s) xj_ids – final x-position(s) yj_ids – final y-position(s) zj_ids – final z-position(s)

>>> grid = lm.grid.Grid(10, 10, 10)
>>> mesh = lm.grid.PrecalculatedMesh(grid)
>>> dist = mesh.distances(0, 0, 0, 1, 1, 1)