--- title: counts (latest version) description: API reference for qiskit_addon_sqd.counts in the latest version of qiskit-addon-sqd source: https://eu-de.quantum.cloud.ibm.com/docs/en/api/qiskit-addon-sqd/counts --- # Counts `qiskit_addon_sqd.counts` Functions for transforming counts dictionaries. ### counts\_to\_arrays `counts_to_arrays(counts)` [GitHub](https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.12/qiskit_addon_sqd/counts.py#L24-L42) Convert a counts dictionary into a bitstring matrix and a probability array. **Parameters** **counts** ([*Mapping*](https://docs.python.org/3/library/collections.abc.html#collections.abc.Mapping)*\[*[*str*](https://docs.python.org/3/library/stdtypes.html#str)*,* [*float*](https://docs.python.org/3/library/functions.html#float) *|*[*int*](https://docs.python.org/3/library/functions.html#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](https://docs.python.org/3/library/stdtypes.html#tuple)\[[*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray), [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray)] ### generate\_counts\_uniform `generate_counts_uniform(num_samples, num_bits, rand_seed=None)` [GitHub](https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.12/qiskit_addon_sqd/counts.py#L64-L97) Generate a bitstring counts dictionary of samples drawn from the uniform distribution. **Parameters** - **num\_samples** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The number of samples to draw - **num\_bits** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The number of bits in the bitstrings - **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator) *|*[*int*](https://docs.python.org/3/library/functions.html#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**](https://docs.python.org/3/library/exceptions.html#ValueError) – `num_samples` and `num_bits` must be positive integers. **Return type** [dict](https://docs.python.org/3/library/stdtypes.html#dict)\[[str](https://docs.python.org/3/library/stdtypes.html#str), [int](https://docs.python.org/3/library/functions.html#int)] ### generate\_counts\_bipartite\_hamming `generate_counts_bipartite_hamming(num_samples, num_bits, *, hamming_right, hamming_left, rand_seed=None)` [GitHub](https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.12/qiskit_addon_sqd/counts.py#L120-L173) Generate a bitstring counts dictionary with specified bipartite hamming weight. **Parameters** - **num\_samples** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The number of samples to draw - **num\_bits** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The number of bits in the bitstrings - **hamming\_right** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The hamming weight on the right half of each bitstring - **hamming\_left** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The hamming weight on the left half of each bitstring - **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator) *|*[*int*](https://docs.python.org/3/library/functions.html#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**](https://docs.python.org/3/library/exceptions.html#ValueError) – `num_bits` and `num_samples` must be positive integers. - [**ValueError**](https://docs.python.org/3/library/exceptions.html#ValueError) – Hamming weights must be specified as non-negative integers. - [**ValueError**](https://docs.python.org/3/library/exceptions.html#ValueError) – `num_bits` must be even. **Return type** [dict](https://docs.python.org/3/library/stdtypes.html#dict)\[[str](https://docs.python.org/3/library/stdtypes.html#str), [int](https://docs.python.org/3/library/functions.html#int)] ### normalize\_counts\_dict `normalize_counts_dict(counts)` [GitHub](https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.12/qiskit_addon_sqd/counts.py#L176-L183) Convert a counts dictionary into a probability dictionary. **Parameters** **counts** ([*Mapping*](https://docs.python.org/3/library/collections.abc.html#collections.abc.Mapping)*\[*[*str*](https://docs.python.org/3/library/stdtypes.html#str)*,* [*float*](https://docs.python.org/3/library/functions.html#float) *|*[*int*](https://docs.python.org/3/library/functions.html#int)*]*) **Return type** [*Mapping*](https://docs.python.org/3/library/collections.abc.html#collections.abc.Mapping)\[[str](https://docs.python.org/3/library/stdtypes.html#str), [float](https://docs.python.org/3/library/functions.html#float)] ### bit\_array\_to\_arrays `bit_array_to_arrays(bit_array)` [GitHub](https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.12/qiskit_addon_sqd/counts.py#L45-L61) Convert a bit array into a bitstring matrix and a probability array. **Parameters** **bit\_array** ([*BitArray*](/docs/api/qiskit/qiskit.primitives.BitArray)) – The bit array 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](https://docs.python.org/3/library/stdtypes.html#tuple)\[[*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray), [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray)] ### generate\_bit\_array\_uniform `generate_bit_array_uniform(num_samples, num_bits, rand_seed=None)` [GitHub](https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.12/qiskit_addon_sqd/counts.py#L100-L117) Generate a bit array of samples drawn from the uniform distribution. **Parameters** - **num\_samples** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The number of samples to draw - **num\_bits** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The number of bits in the bitstrings - **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator) *|*[*int*](https://docs.python.org/3/library/functions.html#int) *| None*) – A seed for controlling randomness **Returns** The sampled bit array. **Raises** [**ValueError**](https://docs.python.org/3/library/exceptions.html#ValueError) – `num_samples` and `num_bits` must be positive integers. **Return type** [*BitArray*](/docs/api/qiskit/qiskit.primitives.BitArray)