import unittest import TasmanianSG import numpy as np from random import shuffle import testCommon ttc = testCommon.TestTasCommon() class TestTasClass(unittest.TestCase): ''' Test the refinement capabilities: * set different refinements * estimate anisotropic coefficients * read/write refinements ''' def __init__(self): unittest.TestCase.__init__(self, "testNothing") def testNothing(self): pass def checkSetClear(self): ''' Set refinement and clear refinement ''' grid = TasmanianSG.TasmanianSparseGrid() grid.makeLocalPolynomialGrid(2, 1, 2, 1, 'semi-localp') ttc.loadExpN2(grid) self.assertEqual(grid.getNumNeeded(), 0, "num needed") grid.setSurplusRefinement(0.0001, 0, 'classic') self.assertTrue((grid.getNumNeeded() > 0), "num needed") grid.clearRefinement() self.assertEqual(grid.getNumNeeded(), 0, "num needed") def checkAnisoCoeff(self): ''' Check anisotropic coefficients ''' grid = TasmanianSG.TasmanianSparseGrid() grid.makeGlobalGrid(2, 1, 9, 'level', 'rleja') aP = grid.getPoints() aV = np.exp(aP[:,0] + aP[:,1]**2) grid.loadNeededPoints(aV.reshape([aP.shape[0], 1])) aC = grid.estimateAnisotropicCoefficients('iptotal', 0) self.assertEqual(len(aC.shape), 1, 'dimensions of the estimated anisotropic weight') self.assertEqual(aC.shape[0], 2, 'dimensions of the estimated anisotropic weight') self.assertLess(np.abs(float(aC[0]) / float(aC[1]) - 2.0), 0.2, 'wrong anisotropic weights estimated') aC = grid.estimateAnisotropicCoefficients('ipcurved', 0) self.assertEqual(len(aC.shape), 1, 'dimensions of the estimated anisotropic weight') self.assertEqual(aC.shape[0], 4, 'dimensions of the estimated anisotropic weight') self.assertLess(np.abs(float(aC[0]) / float(aC[1]) - 2.0), 0.2, 'wrong anisotropic weights estimated, alpha curved') self.assertLess(aC[2], 0.0, 'wrong anisotropic weights estimated, beta 1') self.assertLess(aC[3], 0.0, 'wrong anisotropic weights estimated, beta 2') def checkLocalpSurplus(self): ''' Check surplus refinement for local polynomial grids ''' grid = TasmanianSG.TasmanianSparseGrid() grid.makeLocalPolynomialGrid(2, 1, 4, 1, 'semi-localp') ttc.loadExpN2(grid) aPoints = grid.getPoints() aScale = np.array([[1.0 if aPoints[i,0] > 0.0 else 0.0] for i in range(aPoints.shape[0])]) grid.setSurplusRefinement(1.E-9, 0, 'classic', [], aScale) aNeeded = grid.getNeededPoints() for iI in range(aNeeded.shape[0]): self.assertLess(0.0, aNeeded[iI, 0], 'wrong set of needed points after rescaling') def checkFileIO(self): ''' Read/Write regular refinement. ''' grid = TasmanianSG.TasmanianSparseGrid() sRefinementIOGrids = ["grid.makeGlobalGrid(2, 1, 2, 'level', 'clenshaw-curtis')", "grid.makeSequenceGrid(2, 1, 2, 'level', 'rleja')"] for sTest in sRefinementIOGrids: exec(sTest) ttc.loadExpN2(grid) grid.setAnisotropicRefinement('iptotal', 20, 0) self.assertTrue(grid.getNumNeeded() > 0, 'did not refine') gridB = TasmanianSG.TasmanianSparseGrid() gridB.copyGrid(grid) ttc.compareGrids(grid, gridB) grid.write("refTestFlename.grid", bUseBinaryFormat = True) gridB.makeLocalPolynomialGrid(1, 1, 0, 1) gridB.read("refTestFlename.grid") ttc.compareGrids(grid, gridB) grid.write("refTestFlename.grid", bUseBinaryFormat = False) gridB.makeLocalPolynomialGrid(1, 1, 0, 1) gridB.read("refTestFlename.grid") ttc.compareGrids(grid, gridB) def checkConstruction(self): ''' Test read/write when using construction. ''' llTest = ["gridA.makeGlobalGrid(3, 2, 2, 'level', 'clenshaw-curtis'); gridB.makeGlobalGrid(3, 2, 2, 'level', 'clenshaw-curtis')", "gridA.makeSequenceGrid(3, 2, 4, 'level', 'leja'); gridB.makeSequenceGrid(3, 2, 4, 'level', 'leja')", "gridA.makeLocalPolynomialGrid(3, 2, 2); gridB.makeLocalPolynomialGrid(3, 2, 2)", "gridA.makeWaveletGrid(3, 2, 2); gridB.makeWaveletGrid(3, 2, 2)", "gridA.makeFourierGrid(3, 2, 2, 'level'); gridB.makeFourierGrid(3, 2, 2, 'level')",] for sMakeGrids in llTest: for sFormat in [False, True]: # test binary and ascii format gridA = TasmanianSG.TasmanianSparseGrid() gridB = TasmanianSG.TasmanianSparseGrid() gridC = TasmanianSG.TasmanianSparseGrid() exec(sMakeGrids) gridA.beginConstruction() gridB.beginConstruction() #gridA.printStats() gridB.write("testSave", bUseBinaryFormat = sFormat) gridB.makeSequenceGrid(1, 1, 0, "level", "rleja") # clean the grid gridB.read("testSave") ttc.compareGrids(gridA, gridB) gridC.copyGrid(gridA) ttc.compareGrids(gridA, gridC) for t in range(5): # use 5 iterations if (gridA.isLocalPolynomial() or gridA.isWavelet()): aPointsA = gridA.getCandidateConstructionPointsSurplus(1.E-4, "fds") aPointsB = gridB.getCandidateConstructionPointsSurplus(1.E-4, "fds") aPointsC = gridC.getCandidateConstructionPointsSurplus(1.E-4, "fds") else: aPointsA = gridA.getCandidateConstructionPoints("level", 0) aPointsB = gridB.getCandidateConstructionPoints("level", 0) aPointsC = gridC.getCandidateConstructionPoints("level", 0) np.testing.assert_almost_equal(aPointsA, aPointsB, decimal=11) np.testing.assert_almost_equal(aPointsA, aPointsC, decimal=11) iNumPoints = int(aPointsA.shape[0] / 2) if (iNumPoints > 32): iNumPoints = 32 # use the first samples (up to 32) and shuffle the order # add one of the samples further in the list liSamples = list(range(iNumPoints + 1)) shuffle(liSamples) for iI in range(len(liSamples)): if (liSamples[iI] == iNumPoints): liSamples[iI] = iNumPoints + 1 #liSamples = map(lambda i: i if i < iNumPoints else iNumPoints + 1, liSamples) for iI in liSamples: # compute and load the samples aPoint = aPointsA[iI, :] aValue = np.array([np.exp(aPoint[0] + aPoint[1]), 1.0 / ((aPoint[0] - 1.3) * (aPoint[1] - 1.6) * (aPoint[2] - 2.0))]) gridA.loadConstructedPoint(aPoint, aValue) gridB.loadConstructedPoint(aPoint, aValue) gridC.loadConstructedPoint(aPoint, aValue) # using straight construction or read/write should produce the same result ttc.compareGrids(gridA, gridC) gridB.write("testSave", bUseBinaryFormat = sFormat) gridB.makeSequenceGrid(1, 1, 0, "level", "rleja") gridB.read("testSave") ttc.compareGrids(gridA, gridB) gridC.copyGrid(gridA) ttc.compareGrids(gridA, gridC) gridA.finishConstruction() gridB.finishConstruction() gridB.write("testSave", bUseBinaryFormat = sFormat) gridB.makeSequenceGrid(1, 1, 0, "level", "rleja") gridB.read("testSave") ttc.compareGrids(gridA, gridB) gridC.copyGrid(gridA) ttc.compareGrids(gridA, gridC) # check multi-point load gridA = TasmanianSG.TasmanianSparseGrid() gridA.makeLocalPolynomialGrid(3, 2, 4); ttc.loadExpN2(gridA) gridB = TasmanianSG.TasmanianSparseGrid() gridB.makeLocalPolynomialGrid(3, 2, 0) gridB.beginConstruction() aX = gridA.getPoints() aY = gridA.evaluateBatch(aX) gridB.loadConstructedPoint(aX, aY) gridB.finishConstruction() ttc.compareGrids(gridA, gridB) # check some mem-leaks and crashes (correctness is elsewhere) gridA = TasmanianSG.TasmanianSparseGrid() gridA.makeLocalPolynomialGrid(2, 5, 0) gridA.beginConstruction() gridA.loadConstructedPoint(np.empty([0, 2]), np.empty([0, 5])) # empty input, check for crash gridA.makeLocalPolynomialGrid(2, 1, 1) gridA.loadNeededPoints(np.ones([5, 1])) gridA.beginConstruction() aPoints = gridA.getCandidateConstructionPointsSurplus(1.E-4, "classic") # should generate empty output np.testing.assert_almost_equal(aPoints, np.empty([0, 0]), 14, "failed to generate empty list of construction points", True) gridA.makeLocalPolynomialGrid(2, 1, 0) gridA.loadNeededPoints(np.ones([1, 1])) gridA.beginConstruction() aPoints = gridA.getCandidateConstructionPointsSurplus(1.E-4, "classic", 0, [], np.array([[1.E-6]])) # should generate empty output np.testing.assert_almost_equal(aPoints, np.empty([0, 0]), 14, "failed to generate empty list of construction points", True) gridA.makeGlobalGrid(2, 1, 1, "tensor", "clenshaw-curtis") gridA.loadNeededPoints(np.ones([9, 1])) gridA.beginConstruction() aPoints = gridA.getCandidateConstructionPoints("ipcurved", [5, 5, 2, 2], [1, 1]) # should generate empty output np.testing.assert_almost_equal(aPoints, np.empty([0, 0]), 14, "failed to generate empty list of construction points", True) def checkRemovePoints(self): ''' tests removePointsByHierarchicalCoefficient() ''' grid = TasmanianSG.makeLocalPolynomialGrid(2, 1, 1) aPoints = grid.getNeededPoints() grid.loadNeededValues(np.exp(-aPoints[:,0]**2 -0.5*aPoints[:,1]**2).reshape((grid.getNumNeeded(), 1))) reduced = TasmanianSG.TasmanianSparseGrid() reduced.copyGrid(grid) reduced.removePointsByHierarchicalCoefficient(0.6) self.assertEqual(reduced.getNumPoints(), 3, "failed to remove points with threshold 0.6") np.testing.assert_almost_equal(reduced.getLoadedPoints(), np.array([[0.0, 0.0], [-1.0, 0.0], [1.0, 0.0]]), 14, "failed reduce 1", True) reduced.copyGrid(grid) reduced.removePointsByHierarchicalCoefficient(0.7) self.assertEqual(reduced.getNumPoints(), 1, "failed to remove points with threshold 0.7") np.testing.assert_almost_equal(reduced.getLoadedPoints(), np.array([[0.0, 0.0]]), 14, "failed reduce 2", True) reduced.copyGrid(grid) reduced.removePointsByHierarchicalCoefficient(0.0, iNumKeep = 3) self.assertEqual(reduced.getNumPoints(), 3, "failed to remove points down to 3") np.testing.assert_almost_equal(reduced.getLoadedPoints(), np.array([[0.0, 0.0], [-1.0, 0.0], [1.0, 0.0]]), 14, "failed reduce 3", True) reduced.copyGrid(grid) reduced.removePointsByHierarchicalCoefficient(0.0, iNumKeep = 1) self.assertEqual(reduced.getNumPoints(), 1, "failed to remove points down to 1") np.testing.assert_almost_equal(reduced.getLoadedPoints(), np.array([[0.0, 0.0]]), 14, "failed reduce 4", True) reduced.copyGrid(grid) reduced.removePointsByHierarchicalCoefficient(0.0, aScaleCorrection = np.array([[1.0], [1.0], [1.0], [0.1], [0.1]]), iNumKeep = 3) self.assertEqual(reduced.getNumPoints(), 3, "failed to remove corrected points") np.testing.assert_almost_equal(reduced.getLoadedPoints(), np.array([[0.0, 0.0], [0.0, -1.0], [0.0, 1.0]]), 14, "failed reduce 5", True) def performRefinementTest(self): self.checkSetClear() self.checkAnisoCoeff() self.checkLocalpSurplus() self.checkFileIO() self.checkConstruction() self.checkRemovePoints()