Blizzard
37 lines
1020 B
Python
37 lines
1020 B
Python
import numpy as np
|
|
|
|
from qdrant_client.http.models import SparseVector
|
|
|
|
|
|
def empty_sparse_vector() -> SparseVector:
|
|
return SparseVector(
|
|
indices=[],
|
|
values=[],
|
|
)
|
|
|
|
|
|
def validate_sparse_vector(vector: SparseVector) -> None:
|
|
assert len(vector.indices) == len(
|
|
vector.values
|
|
), "Indices and values must have the same length"
|
|
assert not np.isnan(vector.values).any(), "Values must not contain NaN"
|
|
assert len(vector.indices) == len(set(vector.indices)), "Indices must be unique"
|
|
|
|
|
|
def is_sorted(vector: SparseVector) -> bool:
|
|
for i in range(1, len(vector.indices)):
|
|
if vector.indices[i] < vector.indices[i - 1]:
|
|
return False
|
|
return True
|
|
|
|
|
|
def sort_sparse_vector(vector: SparseVector) -> SparseVector:
|
|
if is_sorted(vector):
|
|
return vector
|
|
|
|
sorted_indices = np.argsort(vector.indices)
|
|
return SparseVector(
|
|
indices=[vector.indices[i] for i in sorted_indices],
|
|
values=[vector.values[i] for i in sorted_indices],
|
|
)
|