pybop._dataset#

Classes#

Represents a collection of experimental observations.

class pybop._dataset.Dataset(data_dictionary, domain: str | None = None)[source]#

Represents a collection of experimental observations.

This class provides a structured way to store and work with experimental data, which may include applying operations such as interpolation.

Parameters:

data_dictionary (dict or instance of pybamm.solvers.solution.Solution) – The experimental data to store within the dataset.
domain (str, optional) – The domain of the dataset. Defaults to “Time [s]”.

__getitem__(key)[source]#

Return the data corresponding to a particular key.

Parameters:: key (str) – The name of a data series within the dataset.
Returns:: The data series corresponding to the key.
Return type:: list or np.ndarray
Raises:: ValueError – The key must exist in the dataset.

__repr__()[source]#

Return a string representation of the Dataset instance.

__setitem__(key, value)[source]#

Set the data corresponding to a particular key.

Parameters:

key (str) – The name of the key to be set.
value (list or np.ndarray) – The data series to be stored in the dataset.

_check_data_consistency(domain_data: numpy.ndarray, signals: list[str]) → None[source]#

static _check_frequency_constraints(freq_data: numpy.ndarray) → None[source]#

static _check_time_constraints(time_data: numpy.ndarray) → None[source]#

check(domain: str = None, signal: str | list[str] = None) → bool[source]#

Check the consistency of a PyBOP Dataset against the expected format.

Parameters:

domain (str, optional) – If not None, updates the domain of the dataset.
signal (str or List[str], optional) – The signal(s) to check. Defaults to [“Voltage [V]”].

Returns:

True if the dataset has the expected attributes.

Return type:

bool

Raises:

ValueError – If the time series and the data series are not consistent.

get_subset(index: list | numpy.ndarray)[source]#: Reduce the dataset to a subset defined by the list of indices.