microproduct/soilMoisture_geo_sar/test_tool/minimize.py

156 lines
4.6 KiB
Python
Raw Permalink Normal View History

2023-08-28 10:17:29 +00:00
# -*- coding: UTF-8 -*-
"""
@Project onestar
@File minimize.py
@Contact
@Author SHJ
@Date 2021/11/24 15:46
@Version 1.0.0
"""
from scipy.optimize import minimize
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import pyplot as plt
#目标函数:
def func(args):
fun = lambda x: 10 - x[0]**2 - x[1]**2
return fun
#约束条件,包括等式约束和不等式约束
def con(args):
cons = ({'type': 'ineq', 'fun': lambda x: x[1]-x[0]**2},
{'type': 'eq', 'fun': lambda x: x[0]+x[1]})
return cons
#画三维模式图
def draw3D():
fig = plt.figure()
ax = Axes3D(fig)
x_arange = np.arange(-5.0, 5.0)
y_arange = np.arange(-5.0, 5.0)
X, Y = np.meshgrid(x_arange, y_arange)
Z1 = 10 - X**2 - Y**2
Z2 = Y - X**2
Z3 = X + Y
plt.xlabel('x')
plt.ylabel('y')
ax.plot_surface(X, Y, Z1, rstride=1, cstride=1, cmap='rainbow')
ax.plot_surface(X, Y, Z2, rstride=1, cstride=1, cmap='rainbow')
ax.plot_surface(X, Y, Z3, rstride=1, cstride=1, cmap='rainbow')
plt.show()
#画等高线图
def drawContour():
x_arange = np.linspace(-3.0, 4.0, 256)
y_arange = np.linspace(-3.0, 4.0, 256)
X, Y = np.meshgrid(x_arange, y_arange)
Z1 = 10 - X**2 - Y**2
Z2 = Y - X**2
Z3 = X + Y
plt.xlabel('x')
plt.ylabel('y')
plt.contourf(X, Y, Z1, 8, alpha=0.75, cmap='rainbow')
plt.contourf(X, Y, Z2, 8, alpha=0.75, cmap='rainbow')
plt.contourf(X, Y, Z3, 8, alpha=0.75, cmap='rainbow')
C1 = plt.contour(X, Y, Z1, 8, colors='black')
C2 = plt.contour(X, Y, Z2, 8, colors='blue')
C3 = plt.contour(X, Y, Z3, 8, colors='red')
plt.clabel(C1, inline=1, fontsize=10)
plt.clabel(C2, inline=1, fontsize=10)
plt.clabel(C3, inline=1, fontsize=10)
plt.show()
# 目标函数:
def func1(args):
fun = lambda x: 10 - x[0] ** 2 - x[1] ** 2
return fun
def samper():
args = ()
args1 = ()
cons = con(args1)
x0 = np.array((1.0, 2.0)) #设置初始值,初始值的设置很重要,很容易收敛到另外的极值点中,建议多试几个值
#求解#
res = minimize(func(args), x0, method='SLSQP', constraints=cons)
#####
print(res.fun)
print(res.success)
print(res.x)
# draw3D()
drawContour()
def samper1():
fun = lambda x: np.abs(np.abs((0.7- (x[0] -0.49)**0.5)/(0.7- (x[0] +0.49)**0.5)) - 0.5*np.abs((0.7- (x[1] -0.49)**0.5)/(0.7- (x[1] +0.49)**0.5)))
# fun = lambda x: np.abs(x[0]**2 -x[1]**2)
x_min = 1
x_max = 20
cons = ({'type': 'ineq', 'fun': lambda x: x[0] - x_min},
{'type': 'ineq', 'fun': lambda x: -x[0] + x_max},
{'type': 'ineq', 'fun': lambda x: x[1] - x_min},
{'type': 'ineq', 'fun': lambda x: -x[1] + x_max})
bnds = ((0, 30), (0, 30))
res = minimize(fun, (3, 3), method='SLSQP', bounds=bnds,constraints=cons)
print("res::",res)
x_arange = np.linspace(0, 25, 256)
y_arange = np.linspace(0, 25, 256)
X, Y = np.meshgrid(x_arange, y_arange)
Z1 = np.abs(np.abs((0.7- (X -0.49)**0.5)/(0.7- (X +0.49)**0.5)) - 0.5*np.abs((0.7- (Y -0.49)**0.5)/(0.7- (Y +0.49)**0.5)))
# Z1 = np.abs(X**2 - Y**2)
plt.xlabel('x')
plt.ylabel('y')
plt.contourf(X, Y, Z1, 8, alpha=0.75, cmap='rainbow')
C1 = plt.contour(X, Y, Z1, 8, colors='black')
plt.clabel(C1, inline=1, fontsize=10)
plt.show()
if __name__ == "__main__":
# samper1()
s1 = 0.9414927
c1 = 0.24188292
s2 = 0.9414927
c2 = 0.24188292
t = 1.0
x_min = 1
x_max = 20
bnds = ((x_min, x_max), (x_min, x_max))
x_mid = 0.5 * (x_max - x_min)
x = [9,8]
a = (s2 - x[1]*(1 + s2))
b = np.abs((x[1] - 1)*(s2 - x[1]*(1 + s2)) / (x[1] * c2 + (x[1] - s2) ** 0.5) ** 2)- t * np.abs((x[0] - 1)*(s1 - x[0]*(1 + s1)) / (x[0] * c1 + (x[0] - s1) ** 0.5) ** 2)
fun = lambda x: np.abs(
np.abs((x[1] - 1)*(s2 - x[1]*(1 + s2)) / (x[1] * c2 + (x[1] - s2) ** 0.5) ** 2)
- t * np.abs((x[0] - 1)*(s1 - x[0]*(1 + s1)) / (x[0] * c1 + (x[0] - s1) ** 0.5) ** 2)
)
res = minimize(fun, (x_mid, x_mid), method='SLSQP', bounds=bnds)
print("res::", res)
x_arange = np.linspace(0, 25, 256)
y_arange = np.linspace(0, 25, 256)
X, Y = np.meshgrid(x_arange, y_arange)
Z1 = np.abs(
np.abs((Y - 1)*(s2 - Y*(1 + s2)) / (Y * c2 + (Y - s2) ** 0.5) ** 2)
- t * np.abs((X - 1)*(s1 - X*(1 + s1)) / (X * c1 + (X - s1) ** 0.5) ** 2)
)
# Z1 = np.abs(X**2 - Y**2)
plt.xlabel('x')
plt.ylabel('y')
plt.contourf(X, Y, Z1, 8, alpha=0.75, cmap='rainbow')
C1 = plt.contour(X, Y, Z1, 8, colors='black')
plt.clabel(C1, inline=1, fontsize=10)
plt.show()
print('done')