What is it?

This package provides functionality for bilinear interpolation. The current capabilities are the following:

• Computation of an interpolant function based on the least sqares method.

  • The interpolant is a bilinear polynomial.

  • The degree of the polynomial is chosen automatically so that it would provide a perfect fit for given set of coordinates.

• Visualisation of the bivariate function.

• Mathematical representation of the interpolant polynomial.

How to install it?

pip install simple-interpolator

Find out more here.

How to use it?

The library simple_interpolator provides a file interpolator encapsulating a class Interpolator.

from simple_interpolator.interpolator import Interpolator

Interpolator class

members	desription
graph()	three-dimentional graph of the interpolant
colormap()	two-dimentional colormap of the interpolant
show()	renders all of the visualisations
add_coordinate()	provide an additional coordiante
add_coordinates()	provide a list of additional coordinates
set_rank()	set a max power of a variable
auto_rank()	fit the data perfectly automatically
data	a list of the provided coordinates
f	an interpolant function
print_f()	mathematical representation of the interpolant

Example

from simple_interpolator.interpolator import Interpolator

i = Interpolator([(2,-5,2),(6,-3,4),(3,-6,4),(-4,3,5),(5,-4,8),(3,7,-5)])

print("Provided coordinates:\n\n\t", i.data, "\n")

print("An interpolant:\n\n",end='\t')
i.print_f(1)

i.graph()
i.colormap()

i.show()

Output:

Provided coordinates:

         [(2, 5, -4), (6, 3, -4), (3, -6, 4), (4, -3, 5), (5, -4, 8)]

Generated interpolant:

        9.7+1.5x+0.4x²-0.1y-0.1xy-0.1x²y+0.2y²

The spacial visualisation is provided as a rotatable 3D object. The picture presented here is just an illustration.