def generate_random_point(self): co_od = [] for _ in xrange(self.dim): co_od.append(np.random.uniform(self.range_lower_limit, self.range_upper_limit)) self.coords = copy.deepcopy(co_od) self.z = evaluate(self.coords)
def generate_random_point(self): co_od = [] for _ in xrange(self.dim): co_od.append( np.random.uniform(self.range_lower_limit, self.range_upper_limit)) self.coords = copy.deepcopy(co_od) self.z = evaluate(self.coords)
def generate_neighbour(self): for ix in xrange(self.dim): offset = (2 * np.random.random() - 1.0) * 0.5 self.coords[ix] += offset if self.coords[ix] < self.range_lower_limit: self.coords[ix] = self.range_lower_limit elif self.coords[ix] > self.range_upper_limit: self.coords[ix] = self.range_upper_limit self.z = evaluate(self.coords)
def evaluate_point(self): self.z = evaluate(self.coords)