def test_ghost_zone_extrapolation():
ds = fake_random_ds(16)
g = ds.index.grids[0]
for i, ax in enumerate('xyz'):
xc = g[ax]
xv = g.get_vertex_centered_data(ax, no_ghost=True)
tf = lin.TrilinearFieldInterpolator(xc,
(g.LeftEdge[0] + g.dds[0]/2.0,
g.RightEdge[0] - g.dds[0]/2.0,
g.LeftEdge[1] + g.dds[1]/2.0,
g.RightEdge[1] - g.dds[1]/2.0,
g.LeftEdge[2] + g.dds[2]/2.0,
g.RightEdge[2] - g.dds[2]/2.0),
["x", "y", "z"], truncate = True)
lx,ly,lz = np.mgrid[g.LeftEdge[0]:g.RightEdge[0]:(g.ActiveDimensions[0]+1)*1j,
g.LeftEdge[1]:g.RightEdge[1]:(g.ActiveDimensions[1]+1)*1j,
g.LeftEdge[2]:g.RightEdge[2]:(g.ActiveDimensions[2]+1)*1j]
xi = tf({'x':lx, 'y':ly, 'z':lz})
xz = np.zeros(g.ActiveDimensions+1)
ghost_zone_interpolate(1, xc, np.array([0.5, 0.5, 0.5], dtype="f8"),
xz, np.array([0.0, 0.0, 0.0], dtype="f8"))
ii = (lx, ly, lz)[i]
yield assert_array_equal, ii, xv
yield assert_array_equal, ii, xi
yield assert_array_equal, ii, xz
def get_vertex_centered_data(self, field, smoothed=True, no_ghost=False):
new_field = np.zeros(self.ActiveDimensions + 1, dtype='float64')
if no_ghost:
# Ensure we have the native endianness in this array. Avoid making
# a copy if possible.
old_field = np.asarray(self[field], dtype="=f8")
# We'll use the ghost zone routine, which will naturally
# extrapolate here.
input_left = np.array([0.5, 0.5, 0.5], dtype="float64")
output_left = np.array([0.0, 0.0, 0.0], dtype="float64")
# rf = 1 here
ghost_zone_interpolate(1, old_field, input_left,
new_field, output_left)
else:
cg = self.retrieve_ghost_zones(1, field, smoothed=smoothed)
np.add(new_field, cg[field][1: ,1: ,1: ], new_field)
np.add(new_field, cg[field][:-1,1: ,1: ], new_field)
np.add(new_field, cg[field][1: ,:-1,1: ], new_field)
np.add(new_field, cg[field][1: ,1: ,:-1], new_field)
np.add(new_field, cg[field][:-1,1: ,:-1], new_field)
np.add(new_field, cg[field][1: ,:-1,:-1], new_field)
np.add(new_field, cg[field][:-1,:-1,1: ], new_field)
np.add(new_field, cg[field][:-1,:-1,:-1], new_field)
np.multiply(new_field, 0.125, new_field)
return new_field
def get_vertex_centered_data(self, field, smoothed=True, no_ghost=False):
new_field = np.zeros(self.ActiveDimensions + 1, dtype="float64")
if no_ghost:
# Ensure we have the native endianness in this array. Avoid making
# a copy if possible.
old_field = np.asarray(self[field], dtype="=f8")
# We'll use the ghost zone routine, which will naturally
# extrapolate here.
input_left = np.array([0.5, 0.5, 0.5], dtype="float64")
output_left = np.array([0.0, 0.0, 0.0], dtype="float64")
# rf = 1 here
ghost_zone_interpolate(1, old_field, input_left, new_field, output_left)
else:
cg = self.retrieve_ghost_zones(1, field, smoothed=smoothed)
np.add(new_field, cg[field][1:, 1:, 1:], new_field)
np.add(new_field, cg[field][:-1, 1:, 1:], new_field)
np.add(new_field, cg[field][1:, :-1, 1:], new_field)
np.add(new_field, cg[field][1:, 1:, :-1], new_field)
np.add(new_field, cg[field][:-1, 1:, :-1], new_field)
np.add(new_field, cg[field][1:, :-1, :-1], new_field)
np.add(new_field, cg[field][:-1, :-1, 1:], new_field)
np.add(new_field, cg[field][:-1, :-1, :-1], new_field)
np.multiply(new_field, 0.125, new_field)
return new_field
