- Timestamp:
- 05/21/10 13:26:14 (6 years ago)
- Location:
- releases
- Files:
-
- 1 added
- 4 deleted
- 6 edited
- 5 copied
- 1 moved
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releases/Makefile
r146 r240 1 1 # CURRENT RELEASE: 2 2 #--------------------------------------------------- 3 NPATCH_0_ 1a2= 03 NPATCH_0_2a1 = 0 4 4 #--------------------------------------------------- 5 5 … … 7 7 8 8 release: 9 tar -cvzf mystic-0.2a1.tgz mystic-0.2a1 10 11 clean: 12 svn up 13 14 15 # PRIOR RELEASE: 16 #--------------------------------------------------- 17 NPATCH_0_1a2 = 0 18 #--------------------------------------------------- 19 20 release_0_1a2: 9 21 tar -cvzf mystic-0.1a2.tgz mystic-0.1a2 10 22 11 clean :23 clean_0_1a2: 12 24 svn up 13 25 -
releases/mystic-0.2a1/_math/__init__.py
r237 r240 9 9 Mystic provides a set of mathematical functions that support various 10 10 advanced optimization features such as uncertainty analysis and 11 parameter sensitivity. These functions are provided::12 ... -- ... 11 parameter sensitivity. (These functions are to be provided in an 12 upcoming release.) 13 13 14 14 -
releases/mystic-0.2a1/_math/grid.py
r236 r240 40 40 41 41 def random_samples(lb,ub,npts=10000): 42 "generate npts random samples between given lb & ub" 42 """ 43 generate npts random samples between given lb & ub 44 45 Inputs: 46 - lower bounds -- a list of the lower bounds 47 - upper bounds -- a list of the upper bounds 48 - npts -- number of sample points [default = 10000] 49 """ 43 50 from numpy.random import random 44 51 dim = len(lb) … … 53 60 takes upper and lower bounds (e.g. ub = [2,4], lb = [0,3]) 54 61 produces a list of sample points s = [[1,3],[1,4],[2,3],[2,4]] 62 63 Inputs: 64 - lower bounds -- a list of the lower bounds 65 - upper bounds -- a list of the upper bounds 66 - npts -- number of sample points 55 67 """ 56 68 q = random_samples(lb,ub,npts) -
releases/mystic-0.2a1/mystic/__init__.py
r224 r240 3 3 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4 4 # 5 # Patrick Hung & Mike McKerns, Caltech5 # Mike McKerns & Patrick Hung, Caltech 6 6 # (C) 1997-2010 All Rights Reserved 7 7 # … … 52 52 - easily generate a fit model (several example models are included) 53 53 - configure and auto-generate a cost function from a model 54 - extend fit jobs to parallel & distributed resources 54 55 - couple models with optimization parameter constraints [COMING SOON] 55 - extend fit jobs to parallel & distributed resources [COMING SOON]56 56 57 57 … … 59 59 =============== 60 60 61 This release version is mystic-0. 1a2. You can download it here.61 This release version is mystic-0.2a1. You can download it here. 62 62 The latest version of mystic is available from:: 63 63 http://dev.danse.us/trac/mystic … … 72 72 download the tarball, unzip, and run the installer:: 73 73 [download] 74 $ tar -xvzf mystic-0. 1a2.tgz75 $ cd mystic-0. 1a274 $ tar -xvzf mystic-0.2a1.tgz 75 $ cd mystic-0.2a1 76 76 $ python setup py build 77 77 $ python setup py install … … 127 127 interface. 128 128 129 Mystic extends the solver API to parallel computing by providing a solver 130 class that utilizes the parallel map-reduce algorithm. Mystic includes 131 a set of defaults in `mystic.mystic.python_map` that mirror the behavior 132 of serial python and the built-in python map function. Mystic solvers 133 built on map-reduce can utilize the distributed and parallel tools provided 134 by the `pathos` package, and thus with little new code solvers are 135 extended to high-performance computing. For more information, see 136 `mystic.mystic.abstract_map_solver`, `mystic.mystic.abstract_nested_solver`, 137 and the pathos documentation at http://dev.danse.us/trac/pathos. 138 129 139 Important classes and functions are found here:: 130 140 - mystic.mystic.abstract_solver [the solver API definition] 141 - mystic.mystic.abstract_map_solver [the parallel solver API] 142 - mystic.mystic.abstract_nested_solver [the nested solver API] 131 143 - mystic.mystic.termination [solver termination conditions] 132 144 - mystic.mystic.strategy [solver population mutation strategies] 133 145 - mystic.models.abstract_model [the model API definition] 134 146 - mystic.models.forward_model [cost function generator] 135 - mystic.mystic.tools [monitors, function wrappers, and other useful tools] 147 - mystic.mystic.tools [monitors, function wrappers, and other tools] 148 - mystic.mystic.math [some useful mathematical functions and tools] 136 149 137 150 Solvers are found here:: 138 151 - mystic.mystic.differential_evolution [Differential Evolution solvers] 139 152 - mystic.mystic.scipy_optimize [Nelder-Mead and Powell's Directional solvers] 153 - mystic.mystic.nested [Batch Grid and Scattershot solvers] 140 154 141 155 … … 145 159 Please see http://dev.danse.us/trac/mystic for further information. 146 160 """ 147 __version__ = '0. 1a2'148 __author__ = 'Mike McKerns , Patrick Hung'161 __version__ = '0.2a1' 162 __author__ = 'Mike McKerns' 149 163 150 164 __license__ = """ … … 182 196 ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 183 197 184 Copyright (c) 20 09California Institute of Technology. All rights reserved.198 Copyright (c) 2010 California Institute of Technology. All rights reserved. 185 199 186 200 … … 196 210 197 211 # solvers 198 import differential_evolution, scipy_optimize 212 import differential_evolution, scipy_optimize, nested 199 213 200 214 # strategies, termination conditions -
releases/mystic-0.2a1/mystic/abstract_map_solver.py
r234 r240 37 37 >>> from pyina.launchers import mpirun_launcher 38 38 >>> from pyina.mappers import equalportion_mapper 39 >>> from pyina.ez_map import ez_map 39 >>> from pyina.ez_map import ez_map2 40 40 >>> NNODES = 4 41 41 >>> … … 44 44 >>> solver = NelderMeadSimplexMapSolver(len(x0)) 45 45 >>> solver.SetInitialPoints(x0) #FIXME: use batchgrid w/ bounds 46 >>> solver.SetMapper(ez_map , equalportion_mapper)46 >>> solver.SetMapper(ez_map2, equalportion_mapper) 47 47 >>> solver.SetLauncher(mpirun_launcher, NNODES) 48 48 >>> solver.Solve(rosen, CRT(), StepMonitor=stepmon) … … 222 222 return 223 223 224 '''225 def Solve(self, func, termination, sigint_callback=None,226 EvaluationMonitor=Null, StepMonitor=Null, ExtraArgs=(), **kwds):227 """solve function 'func' with given termination conditions228 229 *** this method must be overwritten ***"""230 raise NotImplementedError, "must be overwritten..."231 '''232 233 224 234 225 if __name__=='__main__': -
releases/mystic-0.2a1/mystic/abstract_nested_solver.py
r234 r240 37 37 >>> # select the parallel launch configuration 38 38 >>> from pyina.launchers import mpirun_launcher 39 >>> from pyina.ez_map import ez_map 39 >>> from pyina.ez_map import ez_map2 40 40 >>> NNODES = 4 41 41 >>> nbins = [4,4,4] … … 47 47 >>> solver.SetNestedSolver(NelderMeadSimplexSolver) 48 48 >>> solver.SetStrictRanges(lb, ub) 49 >>> solver.SetMapper(ez_map )49 >>> solver.SetMapper(ez_map2) 50 50 >>> solver.SetLauncher(mpirun_launcher, NNODES) 51 51 >>> solver.Solve(rosen, CRT(), StepMonitor=stepmon) -
releases/mystic-0.2a1/setup.py
r236 r240 16 16 setup_code = """ 17 17 setup(name='mystic', 18 version='0. 1a2',18 version='0.2a1', 19 19 description='a simple interactive inversion analysis framework', 20 author = 'Mike McKerns , Patrick Hung',20 author = 'Mike McKerns', 21 21 maintainer = 'Mike McKerns', 22 22 maintainer_email = 'mmckerns@caltech.edu', … … 30 30 packages = ['mystic','mystic.models','mystic.math'], 31 31 package_dir = {'mystic':'mystic','mystic.models':'models', 32 'mystic.math':' math'},32 'mystic.math':'_math'}, 33 33 """ 34 34
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