Source Code for Module snobfit.softConstraint

  1  """ 
  2  softConstraint Class 
  3   
  4  Usage 
  5  ----- 
  6  Usage:  c = softConstraint() 
  7          
  8   
  9  History: 
 10  ------- 
 11  1) Ziwen Fu. 01/08/2009 
 12   
 13  """ 
 14  __docformat__ = "restructuredtext en" 
 15   
 16  import numpy 
 17   
 18   
 19  # ----------------------------------------------------------------- 
 20 -class SoftConstraint: 
 21      """ 
 22      SoftConstraint Class 
 23      """ 
 24 -    def __init__(self, F=None, Flo = 0, Fhi = numpy.inf, sigma=1.25): 
 25          self.F = F 
 26          self.Flo = Flo 
 27          self.Fhi = Fhi 
 28          self.sigmaLo = sigma 
 29          self.sigmaHi = sigma 
 30   
 31 -    def delta(self, x): 
 32          Fx = self.F(x) 
 33          if   Fx < self.Flo: 
 34               return  (Fx - self.Flo)/self.sigmaLo 
 35          elif Fx > self.Fhi: 
 36               return  (Fx - self.Fhi)/self.sigmaHi 
 37          else: 
 38               return 0 
 39   
 40 -    def getFx(self,x): 
 41          return self.F(x) 
 42   
 43       
 44   
 45  # ----------------------------------------------------------------- 
 46 -class SoftConstraints: 
 47      """ 
 48      SoftConstraints Class 
 49      """ 
 50 -    def __init__(self): 
 51          self.C = [] 
 52           
 53 -    def add(self, c): 
 54          self.C.append(c) 
 55   
 56 -    def r(self,x): 
 57          m = len(self.C) 
 58          delta = 0 
 59          for i in xrange(m): 
 60              delta += self.C[i].delta(x)**2 
 61          return delta 
 62   
 63 -    def F(self,x): 
 64          Fs = numpy.zeros( len(self.C) ) 
 65          for i in xrange(len(self.C)): 
 66              Fs[i] = self.C[i].getFx(x) 
 67          return Fs 
 68   
 69 -    def F1(self): 
 70          F1s = numpy.zeros( len(self.C) ) 
 71          for i in xrange(len(self.C)): 
 72              F1s[i] = self.C[i].Flo 
 73          return F1s 
 74   
 75 -    def F2(self): 
 76          F2s = numpy.zeros( len(self.C) ) 
 77          for i in xrange(len(self.C)): 
 78              F2s[i] = self.C[i].Fhi 
 79          return F2s 
 80   
 81 -    def sigmaLo(self): 
 82          s = numpy.zeros( len(self.C) ) 
 83          for i in xrange(len(self.C)): 
 84              s[i] = self.C[i].sigmaLo 
 85          return s 
 86   
 87 -    def sigmaHi(self): 
 88          s = numpy.zeros( len(self.C) ) 
 89          for i in xrange(len(self.C)): 
 90              s[i] = self.C[i].sigmaHi 
 91          return s 
 92   
 93   
 94          
 95  # ------------------------------------------------------------ 
 96 -def hsc18_1(x): 
 97      return x[0]*x[1] - 25 
 98   
 99 -def hsc18_2(x): 
100      return x[0]**2 + x[1]**2 - 25 
101   
102  if __name__ == '__main__': 
103      s =  SoftConstraints() 
104      s.add(  SoftConstraint( F=hsc18_1, Flo=0, Fhi=numpy.inf) ) 
105      s.add(  SoftConstraint( F=hsc18_2, Flo=0, Fhi=numpy.inf) ) 
106      print s.C 
107      print len(s.C) 
108      print s.r( [1,1] ) 
109      print s.F( [1,1] ) 
110      print s.F1( ) 
111      print s.F2( ) 
112