def _init_ORB_grid(data, grid_par=-6, over_s=7):
u"""Initializes ORBKIT's grid and returns necessary data for visualization.
**Parameters:**
data : dict
QCinfo instance representing the molecule.
grid_par : int
Parameter controlling grid. If positive or zero, it specifies number of points; otherwise it specifies the resolution in inverse atomic units.
over_s : int|float
Oversizing, to be tuned
**Returns**
X, Y, Z
Meshgrid (as returned by numpy.mgrid) for positioning the voxels.
"""
from orbkit import grid
## Reinitialization of the grid
grid.is_initialized = False
## Spacing/Number of points
if grid_par > 0:
grid.N_ = [grid_par] * 3
elif grid_par == 0:
grid.N_ = [80] * 3
else:
grid.delta_ = [1.0 / (-grid_par)] * 3
grid.max_ = np.amax(data.geo_spec, axis=0) + over_s
grid.min_ = np.amin(data.geo_spec, axis=0) - over_s
grid.adjust_to_geo(data, extend=over_s, step=grid.delta_[0])
grid.init(force=True)
## The meshgrid MUST be generated in this manner,
## in order to be maximally consistent with ORBKIT
## which uses numpy.arange to generate its grid
## (i.e. start:stop+step:step)
X, Y, Z = np.mgrid[grid.min_[0]:grid.max_[0] +
grid.delta_[0]:grid.delta_[0],
grid.min_[1]:grid.max_[1] +
grid.delta_[1]:grid.delta_[1],
grid.min_[2]:grid.max_[2] +
grid.delta_[2]:grid.delta_[2]]
## NOTICE: numpy.arange does not return consistent results if step is a float,
## specifically if (stop - start)/step overflows, resulting in
## arange(start, stop, step)[-1] > stop
return X, Y, Z
def _alt_init_ORB_grid(data, N, D):
from orbkit import grid
grid.N_ = np.array(N)
grid.delta_ = np.array(D)
T = grid.N_*grid.delta_
P = np.mean(data.geo_spec, axis=0)
grid.min_ = P - T/2
grid.max_ = P + T/2
grid.init()
X, Y, Z = np.mgrid[grid.min_[0] : grid.max_[0] + grid.delta_[0] : grid.delta_[0],
grid.min_[1] : grid.max_[1] + grid.delta_[1] : grid.delta_[1],
grid.min_[2] : grid.max_[2] + grid.delta_[2] : grid.delta_[2]]
return X, Y, Z