示例#1
0
def balance(grid):
    gs = grid.getStorage()
    newgps = []

    for gp in [gs.getPoint(i) for i in range(gs.getSize())]:
        for dim in range(gs.getDimension()):
            # left child in dimension dim
            lgp = HashGridPoint(gp)
            lgp.getLeftChild(dim)

            # right child in dimension dim
            rgp = HashGridPoint(gp)
            rgp.getRightChild(dim)

            if gs.isContaining(lgp) and not gs.isContaining(rgp):
                inserted = insertPoint(grid, rgp)
            elif gs.isContaining(rgp) and not gs.isContaining(lgp):
                inserted = insertPoint(grid, lgp)
            else:
                inserted = []

            newgps += inserted
            gs.recalcLeafProperty()

    return newgps
示例#2
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    def addChildren(self, grid, gp):
        gs = grid.getStorage()
        for d in range(gs.getDimension()):
            # check left child in d
            gpl = HashGridPoint(gp)
            gpl.getLeftChild(d)
            if not gs.isContaining(gpl) and isValid(grid, gpl) and \
                    self.checkRange(gpl, self.maxLevel):
                self.addCollocationNode(grid, gpl)

            # check right child in d
            gpr = HashGridPoint(gp)
            gpr.getRightChild(d)
            if not gs.isContaining(gpr) and isValid(grid, gpr) and \
                    self.checkRange(gpr, self.maxLevel):
                self.addCollocationNode(grid, gpr)
示例#3
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def isRefineable(grid, gp):
    gs = grid.getStorage()
    for d in range(gs.getDimension()):
        # left child in dimension dim
        gpl = HashGridPoint(gp)
        gpl.getLeftChild(d)
        if not gs.isContaining(gpl) and isValid(grid, gpl):
            return True

        # right child in dimension dim
        gpr = HashGridPoint(gp)
        gpr.getRightChild(d)
        if not gs.isContaining(gpr) and isValid(grid, gpr):
            return True

    return False
示例#4
0
文件: general.py 项目: pfluegdk/SGpp
def insert_children(grid, gp, d):
    cnt = []
    gs = grid.getStorage()

    # left child in dimension dim
    gpl = HashGridPoint(gp)
    gpl.getLeftChild(d)
    if not gs.isContaining(gpl) and isValid(grid, gpl):
        success = gs.insert(gpl) > -1
        cnt += 1 if success else 0

    # right child in dimension dim
    gpr = HashGridPoint(gp)
    gpr.getRightChild(d)
    if not gs.isContaining(gpr) and isValid(grid, gpr):
        success = gs.insert(gpr) > -1
        cnt += 1 if success else 0

    return cnt
示例#5
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    def getMaxLevelOfChildrenUpToMaxLevel(self, gp, grid, idim):
        gs = grid.getStorage()
        children = []
        gps = [gp]
        while len(gps) > 0:
            currentgp = gps.pop()
            children.append(getLevel(currentgp))
            if currentgp.getLevel(idim) < self.maxLevel:
                gpl = HashGridPoint(currentgp)
                gpl.getLeftChild(idim)
                if gs.isContaining(gpl):
                    gps.append(gpl)

                # get right child
                gpr = HashGridPoint(currentgp)
                gs.right_child(gpr, idim)
                if gs.isContaining(gpr):
                    gps.append(gpr)

        return children
示例#6
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    def refine(self, grid, gp):
        ans = []
        gs = grid.getStorage()
        for d in range(gs.getDimension()):
            gpl = HashGridPoint(gp)
            gpl.getLeftChild(d)
            if isValid(grid, gpl):
                ans += insertPoint(grid, gpl)
                if hasBorder(grid.getType()):
                    ans += insertTruncatedBorder(grid, gpl)

            gpr = HashGridPoint(gp)
            gpr.getRightChild(d)
            if isValid(grid, gpr):
                ans += insertPoint(grid, gpr)
                if hasBorder(grid.getType()):
                    ans += insertTruncatedBorder(grid, gpr)

        gs.recalcLeafProperty()
        return ans
示例#7
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    def split(self, idim):
        # split the current grid up into three new ones
        gs = self.grid.getStorage()

        # central grid
        centralFullGrid = LocalFullGrid.copy(self)
        centralFullGrid.fullGridLevels[idim] = 1

        # left grid
        gpLeft = HashGridPoint(self.gp)
        gpLeft.getLeftChild(idim)
        fullGridLevels = np.array(self.fullGridLevels)
        fullGridLevels[idim] -= 1
        leftFullGrid = LocalFullGrid(self.grid, gpLeft, fullGridLevels)

        # right grid
        gpRight = HashGridPoint(self.gp)
        gpRight.getRightChild(idim)
        fullGridLevels = np.array(self.fullGridLevels)
        fullGridLevels[idim] -= 1
        rightFullGrid = LocalFullGrid(self.grid, gpRight, fullGridLevels)

        return centralFullGrid, leftFullGrid, rightFullGrid
示例#8
0
    def getMaxLevelOfChildrenUpToMaxLevel(self, gp, grid, idim):
        gs = grid.getStorage()
        children = []
        maxSteps = 0
        gps = [(0, gp)]
        while len(gps) > 0:
            currentSteps, currentgp = gps.pop()

            if maxSteps < currentSteps:
                maxSteps = currentSteps

            gpl = HashGridPoint(currentgp)
            gpl.getLeftChild(idim)
            if gs.isContaining(gpl):
                gps.append((currentSteps + 1, gpl))

            # get right child
            gpr = HashGridPoint(currentgp)
            gpr.getRightChild(idim)
            if gs.isContaining(gpr):
                gps.append((currentSteps + 1, gpr))

        return maxSteps
示例#9
0
def hierarchizeBruteForce(grid, nodalValues, ignore=None):
    if hasBorder(grid):
        print(
            'brute force hierarchization is not supported for boundary grids')
        return nodalValues

    alpha = DataVector(nodalValues)

    gs = grid.getStorage()
    basis = getBasis(grid)

    # hierarchize dimension-wise
    for d in range(gs.getDimension()):
        # compute starting points by level sum
        ixs = {}
        for i in range(gs.getSize()):
            accLevel = gs.getPoint(i).getLevel(d)
            if accLevel in ixs:
                ixs[accLevel].append(i)
            else:
                ixs[accLevel] = [i]

        # collect all possible starting points
        starting_points = []
        for key in sorted(ixs.keys()):
            starting_points += ixs[key]

        while len(starting_points) > 0:
            # get next starting node
            ix = starting_points.pop(0)
            gp = gs.getPoint(ix)

            # append left and right child
            gpl = HashGridPoint(gp)
            gpl.getLeftChild(d)
            gpr = HashGridPoint(gp)
            gpr.getRightChild(d)

            gps = []
            if gs.isContaining(gpr):
                gps.append(gpr)
            if gs.isContaining(gpl):
                gps.append(gpl)

            while len(gps) > 0:
                gpc = gps.pop()
                ix = gs.getSequenceNumber(gpc)
                # removeSample point from possible starting points
                starting_points.remove(ix)
                diff = evalHierToTop(basis, grid, alpha, gpc, d)
                # print( "%i: %.20f - %.20f = %.20f" % (ix, alpha[ix], diff, alpha[ix] - diff) )
                alpha[ix] -= diff

                # append left and right child
                gpl = HashGridPoint(gpc)
                gpl.getLeftChild(d)
                gpr = HashGridPoint(gpc)
                gpr.getRightChild(d)

                if gs.isContaining(gpr):
                    gps.append(gpr)
                if gs.isContaining(gpl):
                    gps.append(gpl)

    return alpha
示例#10
0
p = DataVector(gs.getDimension())

for i in range(gs.getSize()):
    gs.getCoordinates(gs.getPoint(i), p)
    nodalValues[i] = f(p.array())

v = hierarchize(grid, nodalValues)

ipar = 1
assert ipar < len(v)
gp = gs.getPoint(ipar)
print("Grand father:", gs.getCoordinate(gs.getPoint(0), 0), v[0])
print("Father:", gs.getCoordinate(gs.getPoint(0), 0), v[ipar])

gpl = HashGridPoint(gp)
gpl.getLeftChild(0)
gpr = HashGridPoint(gp)
gpr.getRightChild(0)

assert gsc.isContaining(gpl)
assert gsc.isContaining(gpr)

print(gs.getCoordinate(gpl, 0), \
    estimateSurplus(grid, gpl, v), \
    estimateConvergence(grid, gpl, v), \
    w[gsc.getSequenceNumber(gpl)])

print(gs.getCoordinate(gpr, 0), \
    estimateSurplus(grid, gpr, v), \
    estimateConvergence(grid, gpr, v), \
    w[gsc.getSequenceNumber(gpr)])