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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()
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