import math import numpy import copy import time import unittest from sans.dataloader.loader import Loader from sans.fit.Fitting import Fit from sans.models.CylinderModel import CylinderModel import sans.models.dispersion_models from sans.models.qsmearing import smear_selection NPTS = 1 def classMapper(classInstance, classFunc, *args): """ Take an instance of a class and a function name as a string. Execute class.function and return result """ return getattr(classInstance,classFunc)(*args) def mapapply(arguments): return apply(arguments[0], arguments[1:]) class BatchScipyFit: """ test fit module """ def __init__(self, qmin=None, qmax=None): """ """ self.list_of_fitter = [] self.list_of_function = [] self.param_to_fit = ['scale', 'length', 'radius'] self.list_of_constraints = [] self.list_of_mapper = [] self.polydisp = sans.models.dispersion_models.models self.qmin = qmin self.qmax = qmin self.reset_value() def set_range(self, qmin=None, qmax=None): self.qmin = qmin self.qmax = qmax def _reset_helper(self, path=None, engine="scipy", npts=NPTS): """ Set value to fitter engine and prepare inputs for map function """ for i in range(npts): data = Loader().load(path) fitter = Fit(engine) #create model model = CylinderModel() model.setParam('scale', 1.0) model.setParam('radius', 20.0) model.setParam('length', 400.0) model.setParam('sldCyl', 4e-006) model.setParam('sldSolv', 1e-006) model.setParam('background', 0.0) for param in model.dispersion.keys(): model.set_dispersion(param, self.polydisp['gaussian']()) model.setParam('cyl_phi.width', 10) model.setParam('cyl_phi.npts', 3) model.setParam('cyl_theta.nsigmas', 10) """ for 2 data cyl_theta = 60.0 [deg] cyl_phi= 60.0 [deg]""" fitter.set_model(model, i, self.param_to_fit, self.list_of_constraints) #smear data current_smearer = smear_selection(data, model) import cPickle p = cPickle.dumps(current_smearer) sm = cPickle.loads(p) fitter.set_data(data=data, id=i, smearer=current_smearer, qmin=self.qmin, qmax=self.qmax) fitter.select_problem_for_fit(id=i, value=1) self.list_of_fitter.append(copy.deepcopy(fitter)) self.list_of_function.append('fit') self.list_of_mapper.append(classMapper) def reset_value(self): """ Initialize inputs for the map function """ self.list_of_fitter = [] self.list_of_function = [] self.param_to_fit = ['scale', 'length', 'radius'] self.list_of_constraints = [] self.list_of_mapper = [] engine ="scipy" path = "testdata_line3.txt" self._reset_helper(path=path, engine=engine, npts=NPTS) path = "testdata_line.txt" self._reset_helper(path=path, engine=engine, npts=NPTS) path = "SILIC010_noheader.DAT" self._reset_helper(path=path, engine=engine, npts=NPTS) path = "cyl_400_20.txt" self._reset_helper(path=path, engine=engine, npts=NPTS) path = "sphere_80.txt" self._reset_helper(path=path, engine=engine, npts=NPTS) path = "PolySpheres.txt" self._reset_helper(path=path, engine=engine, npts=NPTS) path = "latex_qdev.txt" self._reset_helper(path=path, engine=engine, npts=NPTS) path = "latex_qdev2.txt" self._reset_helper(path=path, engine=engine, npts=NPTS) def test_map_fit(self): """ """ results = map(classMapper,self.list_of_fitter, self.list_of_function) print len(results) for result in results: print result.fitness, result.stderr, result.pvec def test_process_map_fit(self, n=1): """ run fit usong map , n is the number of processes used """ t0 = time.time() print "start fit with %s process(es) at %s" % (str(n), time.strftime(" %H:%M:%S", time.localtime(t0))) from multiprocessing import Pool temp = zip(self.list_of_mapper, self.list_of_fitter, self.list_of_function) results = Pool(n).map(func=mapapply, iterable=temp) t1 = time.time() print "got fit results ", time.strftime(" %H:%M:%S", time.localtime(t1)), t1 - t0 print len(results) for result in results: print result.fitness, result.stderr, result.pvec t2 = time.time() print "print fit1 results ", time.strftime(" %H:%M:%S", time.localtime(t2)), t2 - t1 class testBatch(unittest.TestCase): """ fitting """ def setUp(self): self.test = BatchScipyFit(qmin=None, qmax=None) def __test_fit1(self): """test fit with python built in map function---- full range of each data""" self.test.test_map_fit() def __test_fit2(self): """test fit with python built in map function---- common range for all data""" self.test.set_range(qmin=0.013, qmax=0.05) self.test.reset_value() self.test.test_map_fit() def test_fit3(self): """test fit with data full range using 1 processor and map""" self.test.set_range(qmin=None, qmax=None) self.test.reset_value() self.test.test_process_map_fit(n=2) def test_fit4(self): """test fit with a common fixed range for data using 1 processor and map""" self.test.set_range(qmin=-1, qmax=10) self.test.reset_value() self.test.test_process_map_fit(n=1) if __name__ == '__main__': unittest.main()