Counts

counts_to_arrays(counts)

Convert a counts dictionary into a bitstring matrix and a probability array.

Parameters

counts (dict[str, float |int]) – The counts dictionary to convert

Returns

• A 2D array representing the sampled bitstrings. Each row represents a bitstring, and each element is a bool representation of the bit’s value
• A 1D array containing the probability with which each bitstring was sampled

Return type

tuple[ndarray, ndarray]

generate_counts_uniform(num_samples, num_bits, rand_seed=None)

Generate a bitstring counts dictionary of samples drawn from the uniform distribution.

Parameters

• num_samples (int) – The number of samples to draw
• num_bits (int) – The number of bits in the bitstrings
• rand_seed (Generator |int | None) – A seed for controlling randomness

Returns

A dictionary mapping bitstrings of length num_bits to the number of times they were sampled.

Raises

ValueError – num_samples and num_bits must be positive integers.

Return type

dict[str, int]

generate_counts_bipartite_hamming(num_samples, num_bits, *, hamming_right, hamming_left, rand_seed=None)

Generate a bitstring counts dictionary with specified bipartite hamming weight.

Parameters

• num_samples (int) – The number of samples to draw
• num_bits (int) – The number of bits in the bitstrings
• hamming_right (int) – The hamming weight on the right half of each bitstring
• hamming_left (int) – The hamming weight on the left half of each bitstring
• rand_seed (Generator |int | None) – A seed for controlling randomness

Returns

A dictionary mapping bitstrings to the number of times they were sampled. Each half of each bitstring in the output dictionary will have a hamming weight as specified by the inputs.

Raises

• ValueError – num_bits and num_samples must be positive integers.
• ValueError – Hamming weights must be specified as non-negative integers.
• ValueError – num_bits must be even.

Return type

dict[str, int]

normalize_counts_dict(counts)

Convert a counts dictionary into a probability dictionary.

Parameters

counts (dict[str, float |int])

Return type

dict[str, float]