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Pasqal Documentation

qek.data.processed_data

module
qek.data.processed_data

Loading, saving, manipulation or processed data.

Classes

  • ProcessedData — Data on a single graph obtained from the Quantum Device.

Functions

  • dist_excitation — Calculates the distribution of excitation energies from a dictionary of bitstrings to their respective counts.

  • save_dataset — Saves a dataset to a JSON file.

  • load_dataset — Loads a dataset from a JSON file.

class
ProcessedData (sequence: pl.Sequence, state_dict: dict[str, int | np.int64], target: int | None)

Data on a single graph obtained from the Quantum Device.

Attributes

  • register : pl.Register — The geometry of atoms on the Quantum Device, obtained by compiling the graph for execution on the Quantum Device.

  • pulse : pl.Pulse — The laser pulse, obtained by compiling the graph for execution on the Quantum Device.

  • state_dict : Final[dict[str, int]] — A dictionary {bitstring: number of instances} for this graph.

  • target : Final[int | None] — If specified, the machine-learning target, as a value 0 or 1.

Methods

classmethod
custom (register: targets.Register, pulse: targets.Pulse, device: pl.devices.Device, state_dict: dict[str, int | np.int64], target: int | None) → ProcessedData

method
save_to_file (file_path: str) → None

method
dist_excitation (size: int | None = None) → np.ndarray

Return the distribution of excitations for this graph.

Parameters

  • size : int | None — If specified, truncate or pad the array to this size.

property
pulse : pl.Pulse

The laser pulse used to process this data.

property
register : pl.Register

The register to which the graph was compiled.

method
draw_pulse () → None

Draw the pulse on screen

method
draw_register () → None

Draw the register on screen

method
draw_excitation () → None

Draw an histogram for the excitation level on screen

dist_excitation (state_dict: dict[str, int], size: int | None = None) → np.ndarray

Calculates the distribution of excitation energies from a dictionary of bitstrings to their respective counts.

Parameters

  • size : int | None — If specified, only keep size energy distributions in the output. Otherwise, keep all values.

Returns

  • np.ndarray — A histogram of excitation energies. - index: an excitation level (i.e. a number of 1 bits in a bitstring) - value: normalized count of samples with this excitation level.

save_dataset (dataset: list[ProcessedData], file_path: str) → None

Saves a dataset to a JSON file.

Parameters

  • dataset : list[ProcessedData] — The dataset to be saved, containing RegisterData instances.

  • file_path : str — The path where the dataset will be saved as a JSON file.

Returns

  • None — None

load_dataset (file_path: str) → list[ProcessedData]

Loads a dataset from a JSON file.

Parameters

  • file_path : str — The path to the JSON file containing the dataset.

Returns

  • list[ProcessedData] — A list of ProcessedData instances, corresponding to the data stored in the JSON file.