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from dataclasses import dataclass | |
from numpy import array | |
import typing | |
class GrB_NULL: | |
pass | |
@dataclass | |
class GrB_Descriptor: | |
pass | |
@dataclass | |
class GrB_BinaryOp: | |
op: typing.Callable | |
def __call__(self, first, second): | |
return self.op(first, second) | |
@dataclass | |
class GrB_Monoid: | |
op: GrB_BinaryOp | |
identity: object | |
@dataclass | |
class GrB_Semiring: | |
add: GrB_Monoid | |
multiply: GrB_BinaryOp | |
@dataclass | |
class GrB_Matrix: | |
store: array | |
@dataclass | |
class GrB_Vector(GrB_Matrix): | |
def __post_init__(self): | |
assert len(self.store.shape) == 1, "Vector storage must be 1-dimensional." | |
def GrB_vxm( | |
u: GrB_Vector, | |
A: GrB_Matrix, | |
w: GrB_Vector = GrB_NULL, | |
mask: GrB_Vector = GrB_NULL, | |
accum: GrB_BinaryOp = GrB_NULL, | |
semiring: GrB_Semiring = GrB_NULL, | |
desc: GrB_Descriptor = GrB_NULL | |
) -> GrB_Vector: | |
""" w'<Mask> = accum (w, u'*A) """ | |
print("{}'<{}> = {} ({}, {}'*{})".format(w, mask, accum, w, u, A)) | |
return GrB_Vector(u.store @ A.store) | |
a = GrB_Vector(array([1,2,3])) | |
B = GrB_Matrix(array([[1,2,3], [4,5,6], [7,8,9]])) | |
C = GrB_vxm(a, B) | |
print(C) | |
# Output: | |
# | |
# <class 'pygraphblas.AxB.GrB_NULL'>'<<class 'pygraphblas.AxB.GrB_NULL'>> = <class 'pygraphblas.AxB.GrB_NULL'> (<class 'pygraphblas.AxB.GrB_NULL'>, GrB_Vector(store=array([1, 2, 3]))'*GrB_Matrix(store=array([[1, 2, 3], | |
# [4, 5, 6], | |
# [7, 8, 9]]))) | |
# GrB_Vector(store=array([30, 36, 42])) |
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