From 734cdcebfe66ee283e7ae535cec13a857f8b4a29 Mon Sep 17 00:00:00 2001
From: "trevor.cohn" <trevor.cohn@ec762483-ff6d-05da-a07a-a48fb63a330f>
Date: Sat, 10 Jul 2010 16:49:23 +0000
Subject: Testing code for line search with simplex *equality* constraints and
 positivity constraints.

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@217 ec762483-ff6d-05da-a07a-a48fb63a330f
---
 gi/posterior-regularisation/linesearch.py | 58 +++++++++++++++++++++++++++++++
 1 file changed, 58 insertions(+)
 create mode 100644 gi/posterior-regularisation/linesearch.py

(limited to 'gi/posterior-regularisation/linesearch.py')

diff --git a/gi/posterior-regularisation/linesearch.py b/gi/posterior-regularisation/linesearch.py
new file mode 100644
index 00000000..5a3f2e9c
--- /dev/null
+++ b/gi/posterior-regularisation/linesearch.py
@@ -0,0 +1,58 @@
+## Automatically adapted for scipy Oct 07, 2005 by convertcode.py
+
+from scipy.optimize import minpack2
+import numpy
+
+import __builtin__
+pymin = __builtin__.min
+
+def line_search(f, myfprime, xk, pk, gfk, old_fval, old_old_fval,
+                args=(), c1=1e-4, c2=0.9, amax=50):
+
+    fc = 0
+    gc = 0
+    phi0 = old_fval
+    derphi0 = numpy.dot(gfk,pk)
+    alpha1 = pymin(1.0,1.01*2*(phi0-old_old_fval)/derphi0)
+    # trevor: added this test
+    alpha1 = pymin(alpha1,amax)
+
+    if isinstance(myfprime,type(())):
+        eps = myfprime[1]
+        fprime = myfprime[0]
+        newargs = (f,eps) + args
+        gradient = False
+    else:
+        fprime = myfprime
+        newargs = args
+        gradient = True
+
+    xtol = 1e-14
+    amin = 1e-8
+    isave = numpy.zeros((2,), numpy.intc)
+    dsave = numpy.zeros((13,), float)
+    task = 'START'
+    fval = old_fval
+    gval = gfk
+
+    while 1:
+        stp,fval,derphi,task = minpack2.dcsrch(alpha1, phi0, derphi0, c1, c2,
+                                               xtol, task, amin, amax,isave,dsave)
+        #print 'minpack2.dcsrch', alpha1, phi0, derphi0, c1, c2, xtol, task, amin, amax,isave,dsave
+        #print 'returns', stp,fval,derphi,task
+
+        if task[:2] == 'FG':
+            alpha1 = stp
+            fval = f(xk+stp*pk,*args)
+            fc += 1
+            gval = fprime(xk+stp*pk,*newargs)
+            if gradient: gc += 1
+            else: fc += len(xk) + 1
+            phi0 = fval
+            derphi0 = numpy.dot(gval,pk)
+        else:
+            break
+
+    if task[:5] == 'ERROR' or task[1:4] == 'WARN':
+        stp = None  # failed
+    return stp, fc, gc, fval, old_fval, gval
-- 
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