DataSet

class pinnx.problem.DataSet(X_train, y_train, X_test, y_test, standardize=False, approximator=None, loss_fn='MSE', loss_weights=None)

Fitting Problem set.

Parameters:

• X_train (Dict[str, Union[Array, ndarray, bool, number, bool, int, float, complex, Quantity]]) – Training input data.

• y_train (Dict[str, Union[Array, ndarray, bool, number, bool, int, float, complex, Quantity]]) – Training output data.

• X_test (Dict[str, Union[Array, ndarray, bool, number, bool, int, float, complex, Quantity]]) – Testing input data.

• y_test (Dict[str, Union[Array, ndarray, bool, number, bool, int, float, complex, Quantity]]) – Testing output data.

• standardize (bool) – Standardize input data. Defaults to False.

losses(inputs, outputs, targets, **kwargs)

Return a list of losses, i.e., constraints.

test()

Return a test dataset.

train_next_batch(batch_size=None)

Return a training dataset of the size batch_size.