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src/i/m/imagen-1.0/imagen/random.py   imagen(Download)
 
        random_array.seed(random_seed*12,random_seed*99)
        col=where(random_array.random((ndots))>=0.5, 1.0, -1.0)
 
        random_array.seed(random_seed*122,random_seed*799)
        xpos=floor(random_array.random((ndots))*(bigxsize+2*dotsize)) - halfdot
 
        random_array.seed(random_seed*1243,random_seed*9349)
        ypos=floor(random_array.random((ndots))*(bigysize+2*dotsize)) - halfdot

src/b/i/biskit-2.4/Biskit/FuzzyCluster.py   biskit(Download)
import tools
 
from numpy.oldnumeric.random_array import seed, random
 
## def average(x):
        seed(self.seedx, self.seedy)
 
        r = random((self.npoints, self.n_cluster))
        return N.transpose(r / N.sum(r))
 
    def test_FuzzyCluster( self):
        """FuzzyCluster test"""
        import gnuplot as G
 
        x1 = random((500,2))
        x2 = random((500,2)) + 1
        x3 = random((500,2)) + 2

src/b/i/biskit-2.4/Biskit/TrajFlexMaster.py   biskit(Download)
    def test_FlexMaster(self):
        """TrajFlexMaster test"""
        from Biskit.MatrixPlot import MatrixPlot
        from numpy.oldnumeric.random_array import random
 
            d = N.zeros( N.shape( f ), N.Float32)
            if i > 0:
                d = random( N.shape( f ) ) * ((i / 10) + 1) 
            frames += [f + d]
 

src/b/i/biskit-2.4/Biskit/Dock/ComplexRandomizer.py   biskit(Download)
        """
        radius = (self.d_max_rec + self.d_max_lig) / 2.0
        xyz = ra.random( 3 ) - 0.5
 
        scale = radius*1.0 / N.sqrt( N.sum( xyz**2 ) )

src/t/o/topographica-0.9.8/topo/sheet/slissom.py   topographica(Download)
        if self.noise_rate > 0.0:
            self.activity = self.activity * (1.0-self.noise_rate) \
                + RandomArray.random(self.activity.shape) * self.noise_rate
 
        # Thresholding: baseline + dynamic threshold + absolute refractory 

src/t/o/topographica-HEAD/topo/sheet/slissom.py   topographica(Download)
        if self.noise_rate > 0.0:
            self.activity = self.activity * (1.0-self.noise_rate) \
                + RandomArray.random(self.activity.shape) * self.noise_rate
 
        # Thresholding: baseline + dynamic threshold + absolute refractory

src/b/i/biskit-2.4/Biskit/mathUtils.py   biskit(Download)
    @rtype: array
    """
    alpha = RandomArray.random() * 2 * N.pi
    gamma = RandomArray.random() * 2 * N.pi
    beta  = N.arccos(2*(RandomArray.random() - 0.5))

src/t/o/topographica-HEAD/topo/tests/unit/testplot.py   topographica(Download)
        ### SheetView1:
        ### Find a way to assign randomly the matrix.
        self.matrix1 = zeros((10,10),Float) + RandomArray.random((10,10))
        self.bounds1 = BoundingBox(points=((-0.5,-0.5),(0.5,0.5)))
        sv = SheetView(self.matrix1, self.bounds1, metadata=metadata)
        ### SheetView3:
        ### Find a way to assign randomly the matrix.
        self.matrix3 = zeros((10,10),Float) + RandomArray.random((10,10))
        self.bounds3 = BoundingBox(points=((-0.5,-0.5),(0.5,0.5)))
        sv = SheetView(self.matrix3, self.bounds3, metadata=metadata)

src/c/s/csc-pysparse-1.1.1.4/test/test_spmatrix.py   csc-pysparse(Download)
              y2 = numpy.zeros(n, 'd')
              for s in range(10):
                  x = RandomArray.random((m, ))
                  C.matvec(x, y1)
                  B.matvec(x, t)

src/t/o/topographica-0.9.8/topo/tests/testplot.py   topographica(Download)
        ### SheetView1:
        ### Find a way to assign randomly the matrix.
        self.matrix1 = zeros((10,10),Float) + RandomArray.random((10,10))
        self.bounds1 = BoundingBox(points=((-0.5,-0.5),(0.5,0.5)))
        self.sheet_view1 = SheetView((self.matrix1,self.bounds1),
        ### SheetView3:
        ### Find a way to assign randomly the matrix.
        self.matrix3 = zeros((10,10),Float) + RandomArray.random((10,10))
        self.bounds3 = BoundingBox(points=((-0.5,-0.5),(0.5,0.5)))
        self.sheet_view3 = SheetView((self.matrix3,self.bounds3),

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