def interpolate(self, int_grid):
"""
Convert the 1D gridfunction to another grid using interpolation.
This method returns the same density, but on another grid.
For the interpolation, the IMLS algorithm is used (see
L{interpolation} for details).
The main purpose of this routine is to obtain a density/potential on
a L{cubegrid} that is suitable for visualization from one that is
available only on an L{adfgrid}.
@param int_grid: the grid to use for the interpolated density
@type int_grid: subclass of L{grid}
@return: the interpolated gridfunction
@rtype: L{GridFiunction1D}
"""
new_values = numpy.empty((int_grid.npoints, ))
interp = Grids.interpolation(self)
for i, point in enumerate(int_grid.coorditer()):
if i % 500 == 0:
print "Interpolating point %i of %i " % (i, int_grid.npoints)
new_values[i] = interp.get_value_at_point(point)
import hashlib
m = hashlib.md5()
m.update("Interpolated from :\n")
m.update(self.get_checksum())
m.update("on grid :\n")
m.update(int_grid.get_grid_block(True))
return GridFunction1D(int_grid, new_values, m.digest())
def get_value_at_point(self, point):
"""
Get value at one point by interpolation.
@param point: the point for which the interpolated gridfunction is needed.
"""
interp = Grids.interpolation(self)
return interp.get_value_at_point(point)