generators

Provides generators for the simulation.

class PertubationGenerator(sm: SystemModelInterface, species_start_values_noiser: Optional[Noiser] = None, kinetic_parameters_noiser: Optional[Noiser] = None)

Bases: object

Defines how to generate data for a PertubationTask.

The PertubationGenerator generates data for a PertubationTask by generating a signal for a given system model and check if the signal has a steady state. The initial values for the species and the kinetic parameters are then pertubed. Afterwards the signal is generated again and checked if it has a steady state. If each of the signals has steady states, the data is saved and a table containing the concrete start values for the species, arguments and the according steady-states is returned.

Initializes the PertubationGenerator.

Note

Only the use of a constant_kinetic_parameter is allowed.

Parameters:

• sm – The system model.

• species_start_values_noiser – The noiser for the species start values.

• kinetic_parameters_noiser – The noiser for the kinetic parameters.

generate_signals(n: int = 100) → DataFrame

Generates signals.

Parameters:

n – The number of samples.

Returns:

A list of (noised and sparsed) signals.

Raises:

ValueError – if a signal has no steady state.

Note

This method will probably not work for prediction tasks using a derivative noiser.

class SteadyStateGenerator(sm: SystemModelInterface)

Bases: object

Defines how to generate signals from a PredictionTask.

Initializes the PredictionTaskBuilder.

Parameters:

sm – A SystemModel, for which the signals should be built.

generate_signals(n: int = 100) → DataFrame

Generates signals.

Parameters:

n – The number of samples.

Returns:

A list of (noised and sparsed) signals.

Raises:

ValueError – if a signal has no steady state.

Note

This method will probably not work for prediction tasks using a derivative noiser.

class TimePointsGenerator(sm: SystemModelInterface)

Bases: object

Defines how to generator time points from a Prediction Task.

Initializes the TimePointsGenerator.

Parameters:

sm – A SystemModel, for which the signals should be built.

generate_timepoints(number_of_timepoints: int = 10, save_dir: str = './data/') → None

Generates a specific amount of time points.

Parameters:

• number_of_timepoints – The number of time points that should be generated.

• save_dir – The name of the directory to save the data. Default is ‘./data/’.

Raises:

ValueError – If the number of time points the user wants generate is negative.

class TimeSeriesGenerator(sm: SystemModelInterface)

Bases: object

Defines how to generate signals from a PredictionTask.

Initializes the PredictionTaskBuilder.

Parameters:

sm – A SystemModel, for which the signals should be built.

generate_csv(save_dir: str = './data/') → None

Generates and saves a signal as csv-file.

Parameters:

save_dir – The name of the directory to save the data.

generate_csvs(n: int = 1, save_dir: str = './data/') → None

Generates and saves signals as csv-files.

Parameters:

• n – The number of csvs that will be generated.

• save_dir – The name of the directory to save the data.

generate_signal() → DataFrame

Generates a signal.

Returns:

A (noised and sparsed) signal.

generate_signals(n: int = 100) → list[pandas.core.frame.DataFrame]

Generates signals.

Parameters:

n – The number of samples.

Returns:

A list of (noised and sparsed) signals.

Raises:

ValueError – If the method is not ‘hypercube’ or ‘random’.

save_signal(signal: DataFrame, save_dir: str = './data/', save_name: str = '0') → None

Saves a generated signal as csv-file.

Parameters:

• signal (pd.DataFrame) – Signal.

• save_dir (str) – The name of the directory to save the data. Default is ‘./data/’.

• save_name (str) – Suffix of the filename. Default is ‘0’.

simba_ml.simulation.generators.pertubation_generator	Provides the generator for PredictionTask signals.
simba_ml.simulation.generators.steady_state_generator	Provides the generator for PredictionTask signals.
simba_ml.simulation.generators.time_points_generator	Generator that generates a specific amounts of time points.
simba_ml.simulation.generators.time_series_generator	Provides the generator for PredictionTask signals.