Cyclops Tensor Framework
parallel arithmetic on multidimensional arrays
core.pyx File Reference

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Data Structures

class  ctf.core.comm
class  ctf.core.term
class  ctf.core.contract_term
class  ctf.core.sum_term
class  ctf.core.itensor
class  ctf.core.tensor




def ctf.core.MPI_Stop ()
def ctf.core.__cinit__ (self)
def ctf.core.__dealloc__ (self)
def ctf.core.rank (self)
def (self)
def ctf.core.__get__ (self)
def ctf.core.scale (self, scl)
def ctf.core.__add__ (self, other)
def ctf.core.__sub__ (self, other)
def ctf.core.__mul__ (first, second)
def ctf.core.conv_type (self, dtype)
def ctf.core.__repr__ (self)
def ctf.core.__lshift__ (self, other)
def ctf.core.__cinit__ (self, term, a, term, b)
def ctf.core.__cinit__ (self, tensor, a, string)
def ctf.core.scl (self, s)
def ctf.core.tril (A, k=0)
def ctf.core.triu (A, k=0)
def ctf.core.real (tensor, A)
def ctf.core.imag (tensor, A)
def ctf.core.array (A, dtype=None, copy=True, order='K', subok=False, ndmin=0)
def ctf.core.diag (A, k=0, sp=False)
def ctf.core.spdiag (A, k=0)
def ctf.core.diagonal (init_A, offset=0, axis1=0, axis2=1)
def ctf.core.trace (init_A, offset=0, axis1=0, axis2=1, dtype=None, out=None)
def ctf.core.take (init_A, indices, axis=None, out=None, mode='raise')
def ctf.core.copy (tensor, A)
def ctf.core.reshape (A, newshape, order='F')
def ctf.core.astensor (A, dtype=None, order=None)
def (tA, tB, out=None)
def ctf.core.tensordot (tA, tB, axes=2)
def ctf.core.exp (init_x, out=None, where=True, casting='same_kind', order='F', dtype=None, subok=True)
def ctf.core.to_nparray (t)
def ctf.core.from_nparray (arr)
def ctf.core.zeros_like (init_A, dtype=None, order='F')
def ctf.core.zeros (shape, dtype=np.float64, order='F')
def ctf.core.empty (shape, dtype=np.float64, order='F')
def ctf.core.empty_like (A, dtype=None)
def ctf.core.sum (tensor, init_A, axis=None, dtype=None, out=None, keepdims=None)
def ctf.core.ravel (init_A, order="F")
def ctf.core.any (tensor, init_A, axis=None, out=None, keepdims=None)
def ctf.core.hstack (in_tup)
def ctf.core.vstack (in_tup)
def ctf.core.conj (init_A)
def ctf.core.all (inA, axis=None, out=None, keepdims=False)
def ctf.core.transpose (init_A, axes=None)
def ctf.core.ones (shape, dtype=None, order='F')
def ctf.core.eye (n, m=None, k=0, dtype=np.float64, sp=False)
def ctf.core.identity (n, dtype=np.float64)
def ctf.core.speye (n, m=None, k=0, dtype=np.float64)
def ctf.core.einsum (subscripts, operands, out=None, dtype=None, order='K', casting='safe')
def ctf.core.svd (tensor, A, rank=None)
def ctf.core.qr (tensor, A)
def ctf.core.vecnorm (A, ord=2)
def ctf.core.power (first, second)
def ctf.core.abs (initA)


dictionary ctf.core.type_index = {}
 ctf.core.SYM = _enum(NS=0, SY=1, AS=2, SH=3)
 ctf.core.dim = len(a) = <char*>malloc(dim*sizeof(char))