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
class SearchTracker:
def __init__(self):
self._pos_new = None
self._score_new = -np.inf
self._pos_current = None
self._score_current = -np.inf
self._pos_best = None
self._score_best = -np.inf
self.pos_new_list = []
self.score_new_list = []
self.pos_current_list = []
self.score_current_list = []
self.pos_best_list = []
self.score_best_list = []
### new ###
@property
def pos_new(self):
return self._pos_new
@pos_new.setter
def pos_new(self, pos):
self.pos_new_list.append(pos)
self._pos_new = pos
def score_new(self):
return self._score_new
@score_new.setter
def score_new(self, score):
self.score_new_list.append(score)
self._score_new = score
### current ###
def pos_current(self):
return self._pos_current
@pos_current.setter
def pos_current(self, pos):
self.pos_current_list.append(pos)
self._pos_current = pos
def score_current(self):
return self._score_current
@score_current.setter
def score_current(self, score):
self.score_current_list.append(score)
self._score_current = score
### best ###
def pos_best(self):
return self._pos_best
@pos_best.setter
def pos_best(self, pos):
self.pos_best_list.append(pos)
self._pos_best = pos
def score_best(self):
return self._score_best
@score_best.setter
def score_best(self, score):
self.score_best_list.append(score)
self._score_best = score
SimonBlanke /
Gradient-Free-Optimizers
