for testing and deploying your application
for finding and fixing issues
for empowering human code reviews
# Author: Simon Blanke
# Email: [email protected]
# License: MIT License
import numpy as np
def position2value(search_space, position):
value = []
for n, space_dim in enumerate(search_space):
value.append(space_dim[position[n]])
return value
def values2positions(search_space, values):
init_pos_conv_list = []
values_np = np.array(values)
pos_1d = values_np[:, n]
init_pos_conv = np.where(space_dim == pos_1d)[0]
init_pos_conv_list.append(init_pos_conv)
return init_pos_conv_list
def positions2values(search_space, positions):
pos_converted = []
positions_np = np.array(positions)
pos_1d = positions_np[:, n]
pos_conv = np.take(space_dim, pos_1d, axis=0)
pos_converted.append(pos_conv)
return list(np.array(pos_converted).T)
SimonBlanke /
Gradient-Free-Optimizers
