pKaTool/LM_Fitter.py
def simplex_fit(self):
        """Use the Scipy simple algorithm to minimize R^2"""
        try:
            import scipy.optimize
        except:
            return False,[]
        #print self.variables
        #solution=scipy.optimize.fmin(self.get_difference,self.variables,callback=self.callback_scipy)
        #print 'Simple solution',solution
        solution=scipy.optimize.fmin(self.get_difference,self.variables,callback=self.callback_scipy)
        return True,solution
Use the Scipy simple algorithm to minimize R^2
Use the Scipy simple algorithm to minimize R^2
Use the Scipy simple algorithm to minimize R^2
def simplex_fit(self):
        try:
            import scipy.optimize
        except:
            return False,[]
        solution=scipy.optimize.fmin(self.get_difference,self.variables,callback=self.callback_scipy)
        return True,solution
def simplex_fit ( self ) : try : import scipy . optimize except : return False , [ ] solution = scipy . optimize . fmin ( self . get_difference , self . variables , callback = self . callback_scipy ) return True , solution
Use the Scipy simple algorithm to minimize R^2
Use the Scipy simple algorithm to minimize R^2
"""Use the Scipy simple algorithm to minimize R^2""" #print self.variables #solution=scipy.optimize.fmin(self.get_difference,self.variables,callback=self.callback_scipy) #print 'Simple solution',solution
self