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Unanimous Models

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Unanimous Models#

Identity samplers are not fascinating per se as all voters have the same preferences. There are useful tools however, for instance when using them in mixtures.

identity(num_voters: int, num_candidates: int, seed: int = None) → ndarray[source]#

Generates unanimous ordinal votes, all votes being 0, 1, 2, ….

Parameters:

  • num_voters (int) – Number of Voters.

  • num_candidates (int) – Number of Candidates.

  • seed (int, default: None) – Seed for numpy random number generator.

Returns:

Ordinal votes.

Return type:

np.ndarray

Examples

from prefsampling.ordinal import identity

# Sample a unanimous profile with 2 voters and 3 candidates
identity(2, 3)

# The seed will not change anything here, but you can still set it.
identity(2, 3, seed=1002)

Validation

Validation is trivial here, we thus omit it.

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