Tasks Assessment Module

Core module

class troppo.tasks.core.Task(**kwargs)[source]

Bases: object

A task is a set of constraints that can be applied to a model. It is defined by a set of reactions, a set of constraints on the fluxes of these reactions, a set of constraints on the inflow and outflow of metabolites, and a set of mandatory activities that must be present in the solution. A task can be evaluated on a model to determine if the model satisfies the task.

property annotations

apply_evaluate(model: ~cobamp.core.models.ConstraintBasedModel) -> (<class 'bool'>, <class 'dict'>)[source]

Apply the task to the model and evaluate the solution

Parameters

model: ConstraintBasedModel: The model to apply the task to

Returns

bool, dict: Whether the task was satisfied, and the expected activity of the mandatory reactions

combine(other, add: bool = True)[source]

Combine two tasks into a single task. The resulting task will have the same failure criteria as the original

Parameters

other: Task: The task to combine with
add: bool: If True, the resulting task will be the sum of the two tasks. If False, the resulting task will be the

Returns

Task: The combined task

combine_inplace(other, add: bool = True)[source]

Combine two tasks into a single task. The resulting task will have the same failure criteria as the original

Parameters

other: Task: The task to combine with
add: bool: If True, the resulting task will be the sum of the two tasks. If False, the resulting task will be the

Returns

Task: The combined task

evaluate_solution(sol: ~cobamp.core.optimization.Solution, ftol: float = 1e-06) -> (<class 'bool'>, <class 'dict'>)[source]

Evaluate the solution to the task

Parameters

sol: Solution: The solution to evaluate
ftol: float: The tolerance for the fluxes

Returns

bool, dict: Whether the task was satisfied, and the expected activity of the mandatory reactions

property flux_constraints

get_add_reaction_args(model: ~cobamp.core.models.ConstraintBasedModel, closed: bool = False) -> (<class 'dict'>, <class 'set'>)[source]

Get the arguments to add the reactions to the model

Parameters

model: ConstraintBasedModel: The model to add the reactions to
closed: bool: Whether to add the reactions as closed or open

Returns

dict, set: The arguments to add the reactions to the model, and the set of reactions that were added

get_add_reaction_cmds(model: ~cobamp.core.models.ConstraintBasedModel, closed: bool = False) -> (<class 'cobamp.utilities.context.CommandHistory'>, <class 'set'>)[source]

Get the commands to add the reactions to the model

Parameters

model: ConstraintBasedModel: The model to add the reactions to
closed: bool: Whether to add the reactions as closed or open

Returns

CommandHistory, set: The commands to add the reactions to the model, and the set of reactions that were added

get_task_bounds() → dict[source]: Get the bounds for the task

Returns

dict: The bounds for the task

id_replace(func)[source]

Replace the identifiers in the task with the result of a function applied to the identifiers

Parameters

func: function: The function to apply to the identifiers

property inflow_dict

property involved_reactions: set: Get the set of reactions involved in the task

Returns

set: The set of reactions involved in the task

property mandatory_activity

property name

property outflow_dict

property reaction_dict

property should_fail

class troppo.tasks.core.TaskEvaluator(**kwargs)[source]

Bases: object

A task evaluator is a wrapper around a model that allows the evaluation of tasks on the model. It can be used to evaluate a single task, or to evaluate a batch of tasks on a batch of models.

Parameters

model: ConstraintBasedModel: The model to evaluate tasks on
tasks: Iterable[Task]: The tasks to evaluate on the model
solver: str: The solver to use for the model
S: np.ndarray: The stoichiometric matrix
lb: np.ndarray: The lower bounds for the reactions
ub: np.ndarray: The upper bounds for the reactions
rxn: np.ndarray: The reaction names
mtn: np.ndarray: The metabolite names

batch_evaluate(bound_changes: dict, threads: int = 2, output_sol: bool = False, mp_batch_size: int = 5000) → dict[source]

Evaluate a batch of tasks on the model

Parameters

bound_changes: dict: The changes to apply to the model
threads: int: The number of threads to use
output_sol: bool: Whether to output the solution
mp_batch_size: int: The batch size for multiprocessing

Returns

dict: The results of the evaluation

static batch_function(task: ~troppo.tasks.core.Task, params: dict) -> (<class 'bool'>, <class 'cobamp.core.optimization.Solution'>)[source]

Evaluate a task on a model

Parameters

task: Task: The task to evaluate
params: dict: The parameters to use for evaluation

Returns

bool, Solution: Whether the task was satisfied, and the solution to the model

property current_task

evaluate(context_function=None, flux_distribution_func=None) -> (<class 'bool'>, <class 'cobamp.core.optimization.Solution'>)[source]

Evaluate the current task on the model

Parameters

context_function: function: A function to apply to the model prior to evaluation
flux_distribution_func: function: A function to apply to the model to get the flux distribution

Returns

bool, Solution: Whether the task was satisfied, and the solution to the model

property tasks: Iterable[Task]: Get the tasks

Returns

list: The tasks

Task-io module

class troppo.tasks.task_io.ExcelTaskIO[source]

Bases: TaskIO

ExcelTaskIO is a TaskIO subclass that reads and writes tasks to and from Excel files.

read_from_string(string: str) → list[source]: Reads a task from an Excel string. The string must be in the format specified by the subclass.

Parameters

string: str

Returns

list of Task objects

read_task(buffer_or_path: str, binary_mode: bool = True) → list[source]

Reads a task from an Excel file or buffer. The file or buffer must be in the format specified by the subclass.

Parameters

buffer_or_path: str or TextIOBase: The path to the file or a buffer containing the task
binary_mode: bool: Whether to open the file in binary mode. Only relevant for file paths.

Returns

list of Task objects

write_to_string(task: Task) → str[source]

Writes a task to an Excel string. The string will be in the format specified by the subclass.

Parameters

task: Task or list of Task

Returns

str: The Excel string

class troppo.tasks.task_io.JSONTaskIO[source]

Bases: TaskIO

JSONTaskIO is a TaskIO subclass that reads and writes tasks to and from JSON files.

read_from_string(string: str) → list[source]: Reads a task from a JSON string. The string must be in the format specified by the subclass.

Parameters

string: str

Returns

list of Task objects

write_to_string(task_arg: Task) → str[source]

Writes a task to a JSON string. The string will be in the format specified by the subclass.

Parameters

task_arg: Task or list of Task

Returns

str: The JSON string

class troppo.tasks.task_io.TaskIO[source]

Bases: object

Abstract class for reading and writing tasks to and from files.

abstract read_from_string(string)[source]

read_task(buffer_or_path: str, binary_mode: bool = False) → list[source]

Reads a task from a file or buffer. The file or buffer must be in the format specified by the subclass.

Parameters

buffer_or_path: str or TextIOBase: The path to the file or a buffer containing the task
binary_mode: bool: Whether to open the file in binary mode. Only relevant for file paths.

Returns

list of Task objects

write_task(buffer_or_path: str, task_arg: Task, binary_mode: bool = False) → int[source]

Writes a task to a file or buffer. The file or buffer will be in the format specified by the subclass.

Parameters

buffer_or_path: str or TextIOBase: The path to the file or a buffer containing the task
task_arg: Task or list of Task: The task or tasks to write
binary_mode: bool: Whether to open the file in binary mode. Only relevant for file paths.

Returns

int or None: The number of bytes written to the file or buffer. Only relevant for file paths.

abstract write_to_string(task)[source]