MultiProcess

pycomo.helper.multiprocess.fva(pycomo_model, reactions, fraction_of_optimum=None, verbose=False, processes=None, time_out=30, max_time_out=300, restart_on_timeout=False)

Performs flux variability analysis.

Parameters:

• pycomo_model – A pycomo community metabolic model

• reactions – A list of reactions that should be analysed

• fraction_of_optimum – The fraction of the optimal objective flux that needs to be reached

• use_loop_reactions_for_ko – Find loops in the model and use these reactions as ko_candidates. Overwrites value in ko_candidates

• ko_candidate_ids – Reactions to be constrained and used in the objective (as set of reaction ids)

• verbose – Prints progress messages

• processes – The number of processes to use for the calculation

• time_out – The time in seconds to wait for a result (default=30)

• max_time_out – The maximum time in seconds to wait for a result (default=300)

• restart_on_timeout – If set True, the process pool restarts all unfinished jobs and increases the time_out (up to a max_time_out). Default is False

Returns:

A dataframe of reaction flux solution ranges. Contains the columns minimum and maximum with index of reaction IDs

pycomo.helper.multiprocess.log_call_by_verbosity(verbosity)

Function to log a message with specified verbosity.

Parameters:

verbosity – Log level (info, warning, error, debug)

Returns:

Logger function of specified level

pycomo.helper.multiprocess.log_or_queue_message(verbosity, status, target=None)

Handle decision of logging a message or writing it to the status queue. If a status queue is present, the function writes to the queue, otherwise to the logger.

Parameters:

• verbosity – Log level

• status – The message to be written

• target – For fva steps only, set the current reaction, defaults to None

pycomo.helper.multiprocess.loopless_fva(pycomo_model, reactions, fraction_of_optimum=None, use_loop_reactions_for_ko=False, ko_candidate_ids=None, verbose=False, processes=None, time_out=30, max_time_out=300, restart_on_timeout=False)

Performs flux variability analysis and removes futile cycles from the solutions. This is achieved by fixing the direction of reactions as found in the solution, fixing the fluxes of exchange reactions and minimizing the remaining flux values. This approach is adapted from CycleFreeFLux and its implementation in COBRApy.

Parameters:

• pycomo_model – A pycomo community metabolic model

• reactions – A list of reactions that should be analysed

• fraction_of_optimum – The fraction of the optimal objective flux that needs to be reached

• use_loop_reactions_for_ko – Find loops in the model and use these reactions as ko_candidates. Overwrites value in ko_candidates

• ko_candidate_ids – Reactions to be constrained and used in the objective (as set of reaction ids)

• verbose – Prints progress messages

• processes – The number of processes to use for the calculation

• time_out – The time in seconds to wait for a result (default=30)

• max_time_out – The maximum time in seconds to wait for a result (default=300)

• restart_on_timeout – If set True, the process pool restarts all unfinished jobs and increases the time_out (up to a max_time_out). Default is False

Returns:

A dataframe of reaction flux solution ranges. Contains the columns minimum and maximum with index of reaction IDs