data¶

import tensorwaves.data

The data module takes care of data generation.

class NumpyDomainGenerator(boundaries: Dict[str, Tuple[float, float]])[source]¶

Generate a uniform DataSample as a domain for a Function.

Parameters: boundaries – A mapping of the keys in the DataSample that is to be generated. The boundaries have to be a tuple of a minimum and a maximum value that define the range for each key in the DataSample.

generate(size: int, rng: RealNumberGenerator) → Dict[str, ndarray][source]¶

class IntensityDistributionGenerator(domain_generator: Union[DataGenerator, WeightedDataGenerator], function: Function, domain_transformer: Optional[DataTransformer] = None, bunch_size: int = 50000)[source]¶

Generate an hit-and-miss DataSample distribution for a Function.

Parameters

domain_generator – A DataGenerator that can be used to generate a domain DataSample over which to evaluate the function.
function – An intensity Function with which the output distribution DataSample is generated using a hit-and-miss strategy.
domain_transformer – Optional DataTransformer that can convert a generated domain DataSample to a DataSample that the function can take as input.
bunch_size – Size of a bunch that is generated during a hit-and-miss iteration.

generate(size: int, rng: RealNumberGenerator) → Dict[str, ndarray][source]¶

Submodules and Subpackages

TensorWaves