[SciPy-User] fmin_slsqp- Bounds are not obeyed

jagan prabhu jagan_cbe2003@yahoo.co...
Tue Nov 3 13:58:32 CST 2009

Dear users,

Problem is " Bounded with inequality constrains", in slssqp often Bounds are not obeyed, its deviates the bounds. So if deviates i made it to come back with in the region(bounds). But i face a problem in execution. i get error like,

File "/usr/lib/python2.5/site-packages/scipy/optimize/slsqp.py", line 277, in fmin_slsqp
    c_ieq = array([ ieqcons[i](x) for i in range(len(ieqcons)) ])
  File "/usr/lib/python2.5/site-packages/scipy/optimize/optimize.py", line 97, in function_wrapper
    return function(x, *args)
TypeError: <lambda>() takes exactly 1 argument (2 given)

program will look like,

#import os
#import scipy.optimize
from scipy import *
import numpy
from scipy import optimize
from numpy import asarray
from math import *

def cst(aParams,bounds):
  aParams = numpy.asarray(aParams)
  for par in range(len(aParams)):
   if ((bounds[par][0]<= aParams[par]<= bounds[par][1])):
     if (aParams[par]< bounds[par][0]): aParams[par] = bounds[par][0]
     if (aParams[par]> bounds[par][1]): aParams[par] = bounds[par][1]

  x = aParams[0]
  y = aParams[1]
  z = aParams[2]
# objective function
  eqn = -cos(x)*cos(y)*cos(z)*log(-((x-pi)**2-(y-pi)**2-(z-pi)**2)) 
  return eqn

#Initial guess
Init = numpy.array([5.0,15.0,17.0]) # parameters x,y,z
bounds = [(2.0, 20000.0),(4.0, 50000.0),(5.0, 60000.0)]
# inequality constraints x must be least,y larger than x smaller than z,and z the largest of all
con1 = lambda x:numpy.asarray(x[1]-x[0], x[2]-x[1]) 

opt = fmin_slsqp(cst,Init,ieqcons= [con1] , bounds=bounds, fprime = None, args=(bounds,), full_output=True, iter=20000, iprint=2, acc=0.001)

print '****************************************'

print opt[0]
print opt[1]
print opt[2]
print opt[4]

Problems are,
1, bounds i could not able to pass to the function as args( ).
2, Whether implementation of the ineq. constraints are correct? any better way?
3, How to avoid bounds deviation?

Please help me.


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