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src/o/r/Orange-Bioinformatics-2.5.25/orangecontrib/bio/widgets/Anova.py   Orange-Bioinformatics(Download)
            assert len(numReplicas.shape) == 1, "len(numReplicas.shape) != 1"
            assert numReplicas.shape[0] == numSubjList.shape[0], "numReplicas: int or a list of the same length as numSubjList expected"
        si0 = Numeric.concatenate(([0], Numeric.add.accumulate(numSubjList)))      # indices for axis 0 of dm
        si1 = Numeric.concatenate(([0], Numeric.add.accumulate(numSubjList-1)))    # indices for axis 1 of dm
        dm = Numeric.zeros((si0[-1], si1[-1]))                                     # subject dummy codes matrix
        # check for empty cells, raise exception if empty cells exist and addInteraction=1
        if addInteraction:
            ax1Ind = Numeric.concatenate(([0], Numeric.add.accumulate(rgLens)))
            for idx in range(rgLens.shape[0]):
                if Numeric.add.reduce(MA.count(arr2d[:,ax1Ind[idx]:ax1Ind[idx+1]],1) == 0) > 0:
                # fix arr2d
                print "Warning: removing factor B level(s) with single observation: %s" % str(grpIndSingle)
                groupLensAcc = [0] + list(Numeric.add.accumulate(groupLens))
                arr2dRemInd = map(lambda i: groupLensAcc[i], grpIndSingle)
                arr2dTakeInd = Numeric.ones(arr2d.shape[1])
        # check for empty cells; if exist and addInteraction=1, switch to no interaction and continue
        if addInteraction:
            ax1Ind = Numeric.concatenate(([0], Numeric.add.accumulate(groupLens)))
            for idx in range(groupLens.shape[0]):
                if Numeric.add.reduce(MA.count(arr2d[:,ax1Ind[idx]:ax1Ind[idx+1]],1) == 0) > 0:

src/o/r/Orange-Bioinformatics-2.5.25/orangecontrib/bio/widgets/prototypes/OWANOVA.py   Orange-Bioinformatics(Download)
        else:
            fAnova = Anova.Anova1wayLR_2D
        grpLensAcc = Numeric.concatenate([[0],Numeric.add.accumulate(groupLens)])
        grpInd = map(lambda i,j: range(i, j), grpLensAcc[:-1], grpLensAcc[1:])
        for eIdx in range(ma3d.shape[0]):
        # check for empty cells for all genes at once and remove them
        tInd2rem = []
        ax2Ind = Numeric.concatenate(([0], Numeric.add.accumulate(groupLens)))
        for aIdx in range(ma3d.shape[1]):
            for rIdx in range(groupLens.shape[0]):

src/b/i/biskit-2.4/Biskit/Statistics/Density.py   biskit(Download)
        """          
        order = N.argsort(self.p).tolist()
        cumulative = N.add.accumulate(N.take(self.p, order)) * self.delta_x
 
        ind = N.nonzero(N.greater_equal(cumulative, 1. - level))
    def median(self):
        """
        Median of distribution.
        """
        cum = N.add.accumulate(self.p) * self.delta_x

src/b/i/biskit-2.4/Biskit/mathUtils.py   biskit(Download)
    @rtype: float
    """
    return N.add.accumulate( a ) / N.sum( a )
 
 

src/o/r/Orange-Bioinformatics-2.5.25/orangecontrib/bio/widgets/prototypes/OWHypTest.py   Orange-Bioinformatics(Download)
        else:
            fAnova = Anova.Anova1wayLR_2D
        grpLensAcc = Numeric.concatenate([[0],Numeric.add.accumulate(groupLens)])
        grpInd = map(lambda i,j: range(i, j), grpLensAcc[:-1], grpLensAcc[1:])
        for eIdx in range(ma3d.shape[0]):
        # check for empty cells for all genes at once and remove them
        tInd2rem = []
        ax2Ind = Numeric.concatenate(([0], Numeric.add.accumulate(groupLens)))
        for aIdx in range(ma3d.shape[1]):
            for rIdx in range(groupLens.shape[0]):