Revision 855,
1.2 KB
checked in by mmckerns, 5 months ago
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updated copyright to 2016
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Property svn:executable set to
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1 | #!/usr/bin/env python |
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2 | # |
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3 | # Author: Mike McKerns (mmckerns @caltech and @uqfoundation) |
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4 | # Copyright (c) 1997-2016 California Institute of Technology. |
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5 | # License: 3-clause BSD. The full license text is available at: |
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6 | # - http://mmckerns.github.io/project/mystic/browser/mystic/LICENSE |
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7 | """ |
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8 | Example: |
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9 | - Minimize Rosenbrock's Function with Nelder-Mead. |
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10 | - Plot of parameter convergence to function minimum. |
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11 | |
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12 | Demonstrates: |
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13 | - standard models |
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14 | - minimal solver interface |
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15 | - parameter trajectories using retall |
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16 | """ |
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17 | |
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18 | # Nelder-Mead solver |
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19 | from mystic.solvers import fmin |
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20 | |
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21 | # Rosenbrock function |
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22 | from mystic.models import rosen |
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23 | |
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24 | # tools |
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25 | import pylab |
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26 | |
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27 | |
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28 | if __name__ == '__main__': |
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29 | |
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30 | # initial guess |
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31 | x0 = [0.8,1.2,0.7] |
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32 | |
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33 | # use Nelder-Mead to minimize the Rosenbrock function |
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34 | solution = fmin(rosen,x0,disp=0,retall=1) |
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35 | allvecs = solution[-1] |
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36 | |
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37 | # plot the parameter trajectories |
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38 | pylab.plot([i[0] for i in allvecs]) |
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39 | pylab.plot([i[1] for i in allvecs]) |
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40 | pylab.plot([i[2] for i in allvecs]) |
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41 | |
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42 | # draw the plot |
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43 | pylab.title("Rosenbrock parameter convergence") |
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44 | pylab.xlabel("Nelder-Mead solver iterations") |
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45 | pylab.ylabel("parameter value") |
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46 | pylab.legend(["x", "y", "z"]) |
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47 | pylab.show() |
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48 | |
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49 | # end of file |
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