Python lu_solve_AATI示例

示例#1

    def xstep(self):
        r"""Minimise Augmented Lagrangian with respect to
        :math:`\mathbf{x}`.
        """

        self.X = np.asarray(sl.lu_solve_AATI(self.Z, self.rho, self.SZT +
                            self.rho*(self.Y - self.U), self.lu, self.piv,),
                            dtype=self.dtype)

示例#2

文件： cmod.py 项目： bwohlberg/sporco

    def xstep(self):
        r"""Minimise Augmented Lagrangian with respect to
        :math:`\mathbf{x}`.
        """

        self.X = np.asarray(sl.lu_solve_AATI(self.Z, self.rho, self.SZT +
                            self.rho*(self.Y - self.U), self.lu, self.piv,),
                            dtype=self.dtype)

示例#3

文件： test_linalg.py 项目： longchao343/sporco

 def test_04(self):
     rho = 1e-1
     N = 128
     M = 64
     K = 32
     D = np.random.randn(N, M)
     X = np.random.randn(M, K)
     S = D.dot(X)
     Z = (D.dot(X).dot(X.T) + rho*D - S.dot(X.T)) / rho
     lu, piv = linalg.lu_factor(X, rho)
     Dslv = linalg.lu_solve_AATI(X, rho, S.dot(X.T) + rho*Z, lu, piv)
     assert(linalg.rrs(Dslv.dot(X).dot(X.T) + rho*Dslv,
                     S.dot(X.T) + rho*Z) < 1e-11)

示例#4

文件： test_linalg.py 项目： bwohlberg/sporco

 def test_04(self):
     rho = 1e-1
     N = 128
     M = 64
     K = 32
     D = np.random.randn(N, M)
     X = np.random.randn(M, K)
     S = D.dot(X)
     Z = (D.dot(X).dot(X.T) + rho*D - S.dot(X.T)) / rho
     lu, piv = linalg.lu_factor(X, rho)
     Dslv = linalg.lu_solve_AATI(X, rho, S.dot(X.T) + rho*Z, lu, piv)
     assert(linalg.rrs(Dslv.dot(X).dot(X.T) + rho*Dslv,
                     S.dot(X.T) + rho*Z) < 1e-11)

示例#5

文件： dictlrn_slice.py 项目： demonzyj56/benchmark_csc

 def xstep(self):
     self.X = np.asarray(sl.lu_solve_AATI(
         self.coefs, self.rho, self.SZT + self.rho * (self.Y - self.U),
         self.lu, self.piv),
                         dtype=self.dtype)

示例#6

文件： cmod.py 项目： runngezhang/sporco

    def xstep(self):
        """Minimise Augmented Lagrangian with respect to x."""

        self.X = np.asarray(sl.lu_solve_AATI(self.A, self.rho, self.SAT +
                            self.rho*(self.Y - self.U), self.lu, self.piv,),
                            dtype=self.dtype)