Changeset 829

Timestamp:

09/18/15 17:50:42 (8 months ago)

Author:

mmckerns

Message:

replacing qld with mystic.diffev in test_smo1.py

File:

• mystic/examples_other/test_smo1.py (modified) (5 diffs)

mystic/examples_other/test_smo1.py

@@ -2 +2 @@
 #
 # Author: Patrick Hung (patrickh @caltech)
+# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
 # Copyright (c) 1997-2015 California Institute of Technology.
 # License: 3-clause BSD.  The full license text is available at:
@@ -12 +13 @@
 
 from numpy import *
-import qld
 import pylab
 from mystic.svctools import *
+
+# a common objective function for solving a QP problem
+# (see http://www.mathworks.com/help/optim/ug/quadprog.html)
+def objective(x, H, f):
+    return 0.5 * dot(dot(x,H),x) + dot(f,x)
 
 c1 = array([[0., 0.],[1., 0.],[ 0.2, 0.2],[0.,1.]])
@@ -22 +27 @@
 XX = concatenate([c1,-c2])
 nx = XX.shape[0]
+
+# quadratic and linear terms of QP
 Q = KernelMatrix(XX)
 b = -1 * ones(nx)
@@ -30 +37 @@
 Beq = array([0])
 lb = zeros(nx)
-ub = zeros(nx) + 99999
+ub = 99999 * ones(nx)
 
-# first, use a general purpose IQP solver.
-alpha = qld.quadprog2(H, f, None, None, Aeq, Beq, lb, ub)
-print alpha
+from mystic.symbolic import linear_symbolic, solve, \
+     generate_solvers as solvers, generate_constraint as constraint
+constrain = linear_symbolic(Aeq,Beq)
+constrain = constraint(solvers(solve(constrain,target=['x0'])))
+
+from mystic import supressed
+@supressed(1e-5)
+def conserve(x):
+    return constrain(x)
+
+#from mystic.monitors import VerboseMonitor
+#mon = VerboseMonitor(1)
+
+from mystic.solvers import diffev
+alpha = diffev(objective, zip(lb,ub), args=(H,f), npop=nx*3, gtol=200, \
+#              itermon=mon, \
+               ftol=1e-8, bounds=zip(lb,ub), constraints=conserve, disp=1)
+
+print 'solved x: ', alpha
+print "constraint A*x == 0: ", inner(Aeq, alpha)
+print "minimum 0.5*x'Hx + f'*x: ", objective(alpha, H, f)
+
 
 # let's play. We will need to bootstrap the SMO with an initial
@@ -159 +185 @@
         break
 
+X = concatenate([c1,c2])
 y = Aeq.flatten()
 p,a,b,c = f, lb, ub, 0
-X = concatenate([c1,c2])
 QP_smo(Q, p, a, b, c, y, 0.01, a, X)