sampler.py 文件源码

def __init__(self, dimension,
                 lazy_update_gap=0,
                 constant_trace='',
                 randn=np.random.randn,
                 eigenmethod=np.linalg.eigh):
        try:
            self.dimension = len(dimension)
            standard_deviations = np.asarray(dimension)
        except TypeError:
            self.dimension = dimension
            standard_deviations = np.ones(dimension)
        assert len(standard_deviations) == self.dimension

        # prevent equal eigenvals, a hack for np.linalg:
        self.C = np.diag(standard_deviations**2
                    * np.exp((1e-4 / self.dimension) *
                             np.arange(self.dimension)))
        "covariance matrix"
        self.lazy_update_gap = lazy_update_gap
        self.constant_trace = constant_trace
        self.randn = randn
        self.eigenmethod = eigenmethod
        self.B = np.eye(self.dimension)
        "columns, B.T[i] == B[:, i], are eigenvectors of C"
        self.D = np.diag(self.C)**0.5  # we assume that C is yet diagonal
        idx = self.D.argsort()
        self.D = self.D[idx]
        self.B = self.B[:, idx]
        "axis lengths, roots of eigenvalues, sorted"
        self._inverse_root_C = None  # see transform_inv...
        self.last_update = 0
        self.count_tell = 0
        self.count_eigen = 0