def obj_func3(x):
Q_et = heat_flux.heat_flux_solve(x[0], 1, x[1], 0.9,x[2],0.9)
shiyingdu0 = np.sum(np.square(Q_et[0]-Q_real[0]))
shiyingdu1 = np.sum(np.square(Q_et[1]-Q_real[1]))
shiyingdu2 = np.sum(np.square(Q_et[2]-Q_real[2]))
shiyingdu = shiyingdu0 + shiyingdu1 + shiyingdu2
return shiyingdu
def temprature_main():
t1_generation = []
t3_generation = []
for i in range(9):
F = 0.1*(i+1)
de = DE(func=obj_func, n_dim=2, size_pop=100, max_iter=100, lb=[0, 0 ],
ub=[1, 1], F = F)
best_x, best_y, t_best = de.run()
print('best_x:', best_x, '\n', 'best_y:', best_y)
Q_best = heat_flux.heat_flux_solve(best_x[0], 1, best_x[1])[1]
t1_generation.append(t_best[:,0])
t3_generation.append(t_best[:,1])
df = pd.DataFrame(best_x)
df.to_csv('/biyesheji/交叉因子为'+str(F)+'.csv')
save_t1 = pd.DataFrame(t1_generation)
save_t3 = pd.DataFrame(t3_generation)
save_t1.to_csv('/biyesheji/t1_data.csv')
save_t3.to_csv('/biyesheji/t3_data.csv')
import heat_flux
from sko.DE import DE
# from sko.DE_ori import DE_ori
import numpy as np
import pandas as pd
from sko.DE_gai import DE_gai
Q_real = heat_flux.heat_flux_solve()
# 温度实验迭代
def obj_func(x):
Q_et = heat_flux.heat_flux_solve(x[0], 1, x[1])
shiyingdu0 = np.sum(np.square(Q_et[0]-Q_real[0]))
shiyingdu1 = np.sum(np.square(Q_et[1]-Q_real[1]))
shiyingdu2 = np.sum(np.square(Q_et[2]-Q_real[2]))
shiyingdu = shiyingdu0 + shiyingdu1 + shiyingdu2
return shiyingdu
def temprature_main():
t1_generation = []
t3_generation = []
for i in range(9):
F = 0.1*(i+1)
de = DE(func=obj_func, n_dim=2, size_pop=100, max_iter=100, lb=[0, 0 ],
ub=[1, 1], F = F)
best_x, best_y, t_best = de.run()
print('best_x:', best_x, '\n', 'best_y:', best_y)
def main(i):
x = np.linspace(0, 4, i)
y = heat_flux.heat_flux_solve(l_divide=i)[1]
return x, y