Source code for agentlib_mpc.data_structures.interpolation

from enum import Enum

a = 1


[docs]class InterpolationMethods(str, Enum): linear = "linear" previous = "previous" no_interpolation = "no_interpolation" spline3 = "spline3" # this interpolation method is a custom implementation, intended for the case where # the source data is sampled finer that the target data. It takes the average of # all points between two adjacent time steps on the target grid. # Example: # source_grid: [0, 10, 20, 30, 40, 50, 60] # source_data: [a, b, c, d, e, f, g] # target_grid: [15, 35, 55] # Will yield: [(c+d)/2, (e+f)/2, (e+f)/2] # The last value is always duplicated, to get a lenght consistent with other # interpolation methods # This is intended for the case, where the target data is input for an intgration # / prediction between two points. mean_over_interval = "mean_over_interval"
c = 2