Regular Grid Multivariate linear interpolation
Non-recursive implementation of linear interpolation on regular grids.
Code from this project has been integrated into scipy v0.14.0. See scipy.interpolate.RegularGridInterpolator.
Cartesian grid regulargrid.cartesiangrid.CartesianGrid (equal spacing between points)
Uses very fast implementation based on scipy.ndimage.map_coordinates
# create a 3-dimensional cartesian grid: limits = [(0, 1), (0, 1), (0, 1)] x = numpy.linspace(0, 1, 8) y = numpy.linspace(0, 1, 9) z = numpy.linspace(0, 1, 10) Z, Y = numpy.meshgrid(z, y) X = numpy.array([[x]]).transpose() # our grid values values = X**2 + Y - Z from regulargrid.cartesiangrid import CartesianGrid # does linear interpolation grid = CartesianGrid(limits, values) # interpolate for one point print grid([0.1], [0.5], [0.3]) # interpolate many print grid([0.1, 0.3], [0.5, 0.5], [0.3, 0.2])
Regular grid regulargrid.regulargrid.RegularGrid (unequal spacing between points)
via pip/easy_install from PyPI:
pip install regulargrid
Source hosted at Github
- Trilinear interpolation. (2013, January 17). In Wikipedia, The Free Encyclopedia. Retrieved 01:28, February 27, 2013, from http://en.wikipedia.org/w/index.php?title=Trilinear_interpolation&oldid=533448871
- Weiser, Alan, and Sergio E. Zarantonello. "A note on piecewise linear and multilinear table interpolation in many dimensions." MATH. COMPUT. 50.181 (1988): 189-196. http://www.ams.org/journals/mcom/1988-50-181/S0025-5718-1988-0917826-0/S0025-5718-1988-0917826-0.pdf