SLERP.py

# CONTRIBUTORS: * Ericsson Chenebuah, Michel Nganbe and Alain Tchagang 
# Department of Mechanical Engineering, University of Ottawa, 75 Laurier Ave. East, Ottawa, ON, K1N 6N5 Canada
# Digital Technologies Research Centre, National Research Council of Canada, 1200 Montréal Road, Ottawa, ON, K1A 0R6 Canada
# * email: echen013@uottawa.ca 
# (June-2023)

# Sampling: Spherical Linear Interpolation (SLERP).

from numpy import linspace
import numpy as np

ratios = linspace(0,1, num=5)
print(ratios)

sampled_vec = list()

# z_space is the isolated/interested region within z-hyperdimension

for ratio in ratios:
  for i in range(len(z_space)):
    for iter in range(len(z_space)):
      theta = np.arccos((np.dot(z_space[i,:], z_space[iter,:]))/(np.linalg.norm(z_space[i,:])*np.linalg.norm(z_space[iter,:])))
      v = ((np.sin((1-ratio)*theta))/(np.sin(theta)))*z_space[i,:] + ((np.sin(ratio*theta))/(np.sin(theta)))*z_space[iter,:]
      sampled_vec.append(v)

sampled_vec = np.asarray(sampled_vec)