def interpolator(self, point_values):
"""
Given a self.nsd dimension array point_values with
values at each grid point, this method returns a function
for interpolating the scalar field defined by point_values
at an arbitrary point.
2D Example:
given a filled array point_values[i,j], compute
interpolator = grid.interpolator(point_values)
v = interpolator(0.1243, 9.231) # interpolate point_values
>>> g=UniformBoxGrid(x=(0,2), nx=2, y=(-1,1), ny=2)
>>> g
UniformBoxGrid(x=(0,2), nx=2, y=(-1,1), ny=2)
>>> def f(x,y): return 2+2*x-y
>>> f=g.vectorized_eval(f)
>>> f
array([[ 3., 2., 1.],
[ 5., 4., 3.],
[ 7., 6., 5.]])
>>> i=g.interpolator(f)
>>> i(0.1,0.234) # interpolate (not a grid point)
1.9660000000000002
>>> f(0.1,0.234) # exact answer
1.9660000000000002
"""
args = self.coor
args.append(point_values)
# make use of wrap2callable, which applies ScientificPython
return wrap2callable(args)
def interpolator(self, point_values):
"""
Given a self.nsd dimension array point_values with
values at each grid point, this method returns a function
for interpolating the scalar field defined by point_values
at an arbitrary point.
2D Example:
given a filled array point_values[i,j], compute
interpolator = grid.interpolator(point_values)
v = interpolator(0.1243, 9.231) # interpolate point_values
>>> g=UniformBoxGrid(x=(0,2), nx=2, y=(-1,1), ny=2)
>>> g
UniformBoxGrid(x=(0,2), nx=2, y=(-1,1), ny=2)
>>> def f(x,y): return 2+2*x-y
>>> f=g.vectorized_eval(f)
>>> f
array([[ 3., 2., 1.],
[ 5., 4., 3.],
[ 7., 6., 5.]])
>>> i=g.interpolator(f)
>>> i(0.1,0.234) # interpolate (not a grid point)
1.9660000000000002
>>> f(0.1,0.234) # exact answer
1.9660000000000002
"""
args = self.coor
args.append(point_values)
# make use of wrap2callable, which applies ScientificPython
return wrap2callable(args)
def continuous(self):
if not hasattr(self, 'x') and hasattr(self, 'y'):
self.discrete()
from scitools.numpyutils import wrap2callable
self.g = wrap2callable((self.y, self.x))
return self.g
def continuous(self):
if not hasattr(self, 'x') and hasattr(self, 'y'):
self.discrete()
from scitools.numpyutils import wrap2callable
self.g = wrap2callable((self.y, self.x))
return self.g
