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There are some compatibility issues with pypubsub installing on the documentation servers. and confusion when installing this on other peoples comps. I have put a warning in. Code should work regardless of if you have pypubsub installed or not.

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This commit is contained in:
Rowan Cockett
2013-11-04 10:26:56 -08:00
parent faa2be56a5
commit ac099f08cd
1 changed files with 17 additions and 10 deletions
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SimPEG/inverse/Optimize.py
+17 -10
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@@ -3,7 +3,14 @@ import matplotlib.pyplot as plt
from SimPEG.utils import mkvc, sdiag
norm = np.linalg.norm
import scipy.sparse as sp
from pubsub import pub
try:
from pubsub import pub
doPub = True
except Exception, e:
print 'Warning: you may not have the required pubsub installed, use pypubsub. You will not be able to listen to events.'
doPub = False
class Minimize(object):
@@ -52,20 +59,20 @@ class Minimize(object):
while True:
self.f, self.g, self.H = evalFunction(self.xc, return_g=True, return_H=True)
pub.sendMessage('Minimize.evalFunction', minimize=self, f=self.f, g=self.g, H=self.H)
if doPub: pub.sendMessage('Minimize.evalFunction', minimize=self, f=self.f, g=self.g, H=self.H)
self.printIter()
if self.stoppingCriteria(): break
p = self.findSearchDirection()
pub.sendMessage('Minimize.searchDirection', minimize=self, p=p)
if doPub: pub.sendMessage('Minimize.searchDirection', minimize=self, p=p)
p = self.scaleSearchDirection(p)
pub.sendMessage('Minimize.scaleSearchDirection', minimize=self, p=p)
if doPub: pub.sendMessage('Minimize.scaleSearchDirection', minimize=self, p=p)
xt, passLS = self.modifySearchDirection(p)
pub.sendMessage('Minimize.modifySearchDirection', minimize=self, xt=xt)
if doPub: pub.sendMessage('Minimize.modifySearchDirection', minimize=self, xt=xt)
if not passLS:
xt, caught = self.modifySearchDirectionBreak(p)
if not caught: return self.xc
self.doEndIteration(xt)
pub.sendMessage('Minimize.endIteration', minimize=self, xt=xt)
if doPub: pub.sendMessage('Minimize.endIteration', minimize=self, xt=xt)
self.printDone()
@@ -95,7 +102,7 @@ class Minimize(object):
printIter is called at the beginning of the optimization routine.
"""
pub.sendMessage('Minimize.printInit', minimize=self)
if doPub: pub.sendMessage('Minimize.printInit', minimize=self)
if self.parent is not None and hasattr(self.parent, 'printInit'):
self.parent.printInit()
return
@@ -108,14 +115,14 @@ class Minimize(object):
printIter is called directly after function evaluations.
"""
pub.sendMessage('Minimize.printIter', minimize=self)
if doPub: pub.sendMessage('Minimize.printIter', minimize=self)
if self.parent is not None and hasattr(self.parent, 'printIter'):
self.parent.printIter()
return
print "%3d\t%1.2e\t%1.2e\t%d" % (self._iter, self.f, norm(self.g), self._iterLS)
def printDone(self):
pub.sendMessage('Minimize.printDone', minimize=self)
if doPub: pub.sendMessage('Minimize.printDone', minimize=self)
if self.parent is not None and hasattr(self.parent, 'printDone'):
self.parent.printDone()
return
@@ -221,7 +228,7 @@ if __name__ == '__main__':
def listener1(minimize,p):
print 'hi: ', p
pub.subscribe(listener1, 'Minimize.searchDirection')
if doPub: pub.subscribe(listener1, 'Minimize.searchDirection')
xOpt = GaussNewton(maxIter=20,tolF=1e-10,tolX=1e-10,tolG=1e-10).minimize(Rosenbrock,x0)
print "xOpt=[%f, %f]" % (xOpt[0], xOpt[1])