class Interpolator(object):
def __init__(self, fileName):
try:
from gridData import Grid
except ModuleNotFoundError:
raise ModuleNotFoundError("The dependency 'GridDataFormats' is required for this functionality!")
self.grid = Grid(fileName) # stores the grid data
def __call__(self, xyz):
return self.grid.interpolated(xyz[:,0], xyz[:,1], xyz[:,2])
attribute "dep" string "positions" object "regular positions regular connections" class field component "positions" value 1 component "connections" value 2 component "data" value 3 """ edge1 = g.edges[0] edge2 = g.edges[1] edge3 = g.edges[2] grid = g.grid edges = g.edges g.interpolated([1, 1, 1], [2, 3, 2], [2, 3, 2]) import numpy as np # Visualization from mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused import import matplotlib.pyplot as plt x = np.arange(30) y = np.arange(30) z = np.arange(30) xx, yy, zz = np.meshgrid(x, y, z) flat = grid.flatten() flat[flat < 1] = 0
class Interpolator(object):
def __init__(self, fileName):
self.grid = Grid(fileName) # stores the grid data
def __call__(self, xyz):
return self.grid.interpolated(xyz[:, 0], xyz[:, 1], xyz[:, 2])
# if writepdb:
# with open(surface_fname, "a") as fid:
# fid.write(f"{len(x)*len(z)}\n\n")
# for step_z in cylinder_grid:
for j, step_z in enumerate(z):
# layer[j] = np.array(
# [
# dat.interpolated(x, y, np.repeat(step_z, len(x)))
# ],
# dtype=np.float32,
# )
zcrd = np.repeat(step_z, len(x))
xyz = np.vstack((x, y, zcrd))
vals = dat.interpolated(*xyz)
if run_charge_density:
mean[j] += np.sum(vals)
stddev[j] += np.var(vals)
else:
mean[j] = vals.mean()
stddev[j] = vals.std()
# print(x.min(), x.max(), y.min(), y.max(), step_z, mean.shape)
# else:
# this_layer = np.array(
# [
# dat.interpolated(x, y, np.repeat(step_z, len(x))) / N
# ],
# dtype=np.float32,
# )
# layer.append( this_layer