qibocal package#
qibocal: Quantum Calibration Verification and Validation using Qibo.
Subpackages#
- qibocal.auto package
- Submodules
- qibocal.auto.draw module
- qibocal.auto.execute module
- qibocal.auto.graph module
- qibocal.auto.history module
- qibocal.auto.operation module
- qibocal.auto.runcard module
- qibocal.auto.status module
- qibocal.auto.task module
- qibocal.auto.validate module
- qibocal.cli package
- qibocal.protocols package
- Subpackages
- qibocal.protocols.characterization package
Operation
- Subpackages
- Submodules
- qibocal.protocols.characterization.classification module
- qibocal.protocols.characterization.dispersive_shift module
- qibocal.protocols.characterization.flipping module
- qibocal.protocols.characterization.qubit_spectroscopy module
- qibocal.protocols.characterization.ramsey module
- qibocal.protocols.characterization.ramsey_sequences module
- qibocal.protocols.characterization.readout_characterization module
- qibocal.protocols.characterization.resonator_punchout module
- qibocal.protocols.characterization.resonator_punchout_attenuation module
- qibocal.protocols.characterization.resonator_spectroscopy module
- qibocal.protocols.characterization.resonator_spectroscopy_attenuation module
- qibocal.protocols.characterization.test module
- qibocal.protocols.characterization.two module
- qibocal.protocols.characterization.utils module
- qibocal.protocols.characterization package
- Subpackages
- qibocal.web package
Submodules#
qibocal.bootstrap module#
- qibocal.bootstrap.data_uncertainties(data, method=None, data_median=None, homogeneous=True)[source]#
Compute the uncertainties of the median (or specified) values.
- Parameters
data (list or np.ndarray) – 2d array with rows containing data points from which the median value is extracted.
method (str or int or float, optional) – method of computing the method. If
"std"
, computes the standard deviation. If number between 0 and 100, computes the corresponding confidence interval usingnp.percentile
. Otherwise, returnsNone
. Defaults toNone
.data_median (list or np.ndarray, optional) – 1d array for computing the errors from the confidence interval. If
None
, the median values are computed fromdata
.homogeneous (bool) – if
True
, assumes that all rows indata
are of the same size and returnsnp.ndarray
. Default isTrue
.
- Returns
uncertainties of the data.
- Return type
np.ndarray
- qibocal.bootstrap.bootstrap(data: Union[ndarray, list], n_bootstrap: int, homogeneous: bool = True, sample_size: Optional[int] = None, seed: Optional[int] = None)[source]#
Non-parametric bootstrap resampling.
- Parameters
data (list or np.ndarray) – 2d array with rows containing samples.
n_bootstrap (int) – number of bootstrap iterations.
homogeneous (bool) – if
True
, assumes that all rows indata
are of the same size and returnsnp.ndarray
. IfFalse
, returns a list of lists. Default isTrue
.sample_size (int, optional) – number of samples per row in
data
. IfNone
, defaults tolen(row)
fromdata
.seed (int, optional) – A fixed seed to initialize
np.random.Generator
. IfNone
, initializes a generator with a random seed. Defaults isNone
.
- Returns
resampled data of shape (len(data), sample_size, n_bootstrap)
- Return type
list or np.ndarray
qibocal.config module#
Custom logger implemenation.
- qibocal.config.raise_error(exception, message=None, args=None)[source]#
Raise exception with logging error.
- class qibocal.config.CustomHandler[source]#
Bases:
StreamHandler
Custom handler for logging algorithm.
qibocal.utils module#
- qibocal.utils.allocate_single_qubits(platform: Optional[Platform], qubit_ids: list[Union[str, int]]) dict[Union[str, int], qibolab.qubits.Qubit] [source]#
Construct the map from the chosen ids to the corresponding physical qubits available on the platform.
- qibocal.utils.allocate_qubits_pairs(platform: Optional[Platform], qubit_pairs_ids: list[tuple[Union[str, int], Union[str, int]]]) dict[tuple[Union[str, int], Union[str, int]], qibolab.qubits.QubitPair] [source]#
Construct the map from the chosen id pairs to the corresponding physical qubit pairs available on the platform.