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mballance avatar mballance commented on July 3, 2024 1

Hi @felixdube, Have a look at the new unique_vec constraint in the 0.9.0 release. You can find a test showing its use here:

pyvsc/ve/unit/test_unique.py

Lines 204 to 234 in 36aca2d

def test_unique_vec_smoke(self):
@vsc.randobj
class my_c(object):
def __init__(self):
self.a = vsc.rand_list_t(vsc.rand_uint16_t(1), 2)
self.b = vsc.rand_list_t(vsc.rand_uint16_t(1), 2)
self.c = vsc.rand_list_t(vsc.rand_uint16_t(1), 2)
@vsc.constraint
def index_1_constraint(self):
self.a[0] < 2
self.b[0] < 2
self.c[0] < 2
self.a[1] < 2
self.b[1] < 2
self.c[1] < 2
@vsc.constraint
def unique_list_constraint(self):
vsc.unique_vec(self.a, self.b, self.c)
it = my_c()
print("A:")
for i in range(len(it.a)):
print(" %d" % it.a[i])
print("B:")
for i in range(len(it.b)):
print(" %d" % it.b[i])
print("C:")
for i in range(len(it.c)):
print(" %d" % it.c[i])

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mballance avatar mballance commented on July 3, 2024

Hi @felixdube,
The current behavior is aligned with SV behavior. Specifically, all arguments to unique are 'flattened' down to a combined list of scalar variables which must be unique.
Unfortunately, I don't think there's an easy way to synthesize your desired behavior using existing constraints. This is because you effectively need to construct an 'OR' across all the uniquification terms between the arrays.
I think it's reasonable to support 'vector' uniquification within PyVSC. Is it safe to assume that, at least for your use case, the size of all vectors is the same?

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felixdube avatar felixdube commented on July 3, 2024

Hi @mballance,
Thank you for you quick reply!

Yes, in my use case, it would be okay to assume the size of the vectors is the same.

Felix

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felixdube avatar felixdube commented on July 3, 2024

Awesome! Thank you for the help!

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