add code

scripts/optimization/LagrangeMultiplierMethod/LagrangeMultiplierMethod.py

@@ -4,60 +4,64 @@ import matplotlib.pyplot as plt
 import numpy as np
 import random
 from math import *
-from scipy.optimize import fsolve
 
 delta = 0.1
-minXY=-5.0
-maxXY=5.0
-nContour=50
+minXY = -5.0
+maxXY = 5.0
+nContour = 50
+
 
 def dfunc(d):
-    x=d[0]
-    y=d[1]
-    l=d[2]
-    dx=-2*l+4*x*(x**2+y-11)
-    dy=l+2*x*x+2*y-22
-    dl=-2*x+y-1
-    return [dx,dy,dl]
+    x = d[0]
+    y = d[1]
+    l = d[2]
+    dx = -2 * l + 4 * x * (x ** 2 + y - 11)
+    dy = l + 2 * x * x + 2 * y - 22
+    dl = -2 * x + y - 1
+    return [dx, dy, dl]
+
+
+def SampleFunc(x, y):
+    return (x ** 2 + y - 11) ** 2
 
-def SampleFunc(x,y):
-    return (x**2+y-11)**2
 
 def ConstrainFunction(x):
-    return (2.0*x+1.0)
+    return (2.0 * x + 1.0)
+
 
 def CreateMeshData():
     x = np.arange(minXY, maxXY, delta)
     y = np.arange(minXY, maxXY, delta)
     X, Y = np.meshgrid(x, y)
-    Z=[SampleFunc(x,y) for (x,y) in zip(X,Y)]
-    return(X,Y,Z)
+    Z = [SampleFunc(ix, iy) for (ix, iy) in zip(X, Y)]
+    return(X, Y, Z)
+
 
 # Main
-start=np.matrix([random.uniform(minXY,maxXY),random.uniform(minXY,maxXY),0])
+start = np.matrix([random.uniform(minXY, maxXY),
+                   random.uniform(minXY, maxXY), 0])
 
-(X,Y,Z)=CreateMeshData()
-CS = plt.contour(X, Y, Z,nContour)
+(X, Y, Z) = CreateMeshData()
+CS = plt.contour(X, Y, Z, nContour)
 
-Xc=np.arange(minXY,maxXY,delta)
-Yc=[ConstrainFunction(x) for x in Xc]
+Xc = np.arange(minXY, maxXY, delta)
+Yc = [ConstrainFunction(x) for x in Xc]
 
 #  plt.plot(start[0,0],start[0,1],"xr");
-plt.plot(Xc,Yc,"-r");
+plt.plot(Xc, Yc, "-r")
 
 #  X1 = fsolve(dfunc, [-3, -3, 10])
 #  print(X1)
 #  print(dfunc(X1))
 
 # the answer from sympy
-result=np.matrix([
-[-1,-1],
-#  [-1+sqrt(11),-1+2*sqrt(11)],
-#  [-sqrt(11)-1,-2*sqrt(11)-1]])
+result = np.matrix([
+    [-1, -1],
+    [-1 + sqrt(11), -1 + 2 * sqrt(11)],
+    [-sqrt(11) - 1, -2 * sqrt(11) - 1]])
 print(result)
 
-plt.plot(result[:,0],result[:,1],"or");
+plt.plot(result[:, 0], result[:, 1], "or")
 
 plt.axis([minXY, maxXY, minXY, maxXY])
 plt.show()
-