def set_objective(model, value, additive=False):
    """Set the model objective.

    Parameters
    ----------
    model : cobra model
       The model to set the objective for
    value : model.problem.Objective,
            e.g. optlang.glpk_interface.Objective, sympy.Basic or dict

        If the model objective is linear, the value can be a new Objective
        object or a dictionary with linear coefficients where each key is a
        reaction and the element the new coefficient (float).

        If the objective is not linear and `additive` is true, only values
        of class Objective.

    additive : boolmodel.reactions.Biomass_Ecoli_core.bounds = (0.1, 0.1)
        If true, add the terms to the current objective, otherwise start with
        an empty objective.
    """
    interface = model.problem
    reverse_value = model.solver.objective.expression
    reverse_value = interface.Objective(
        reverse_value, direction=model.solver.objective.direction,
        sloppy=True)

    if isinstance(value, dict):
        if not model.objective.is_Linear:
            raise ValueError('can only update non-linear objectives '
                             'additively using object of class '
                             'model.problem.Objective, not %s' %
                             type(value))

        if not additive:
            model.solver.objective = interface.Objective(
                Zero, direction=model.solver.objective.direction)
        for reaction, coef in value.items():
            model.solver.objective.set_linear_coefficients(
                {reaction.forward_variable: coef,
                 reaction.reverse_variable: -coef})

    elif isinstance(value, (Basic, optlang.interface.Objective)):
        if isinstance(value, Basic):
            value = interface.Objective(
                value, direction=model.solver.objective.direction,
                sloppy=False)
        # Check whether expression only uses variables from current model
        # clone the objective if not, faster than cloning without checking
        if not _valid_atoms(model, value.expression):
            value = interface.Objective.clone(value, model=model.solver)

        if not additive:
            model.solver.objective = value
        else:
            model.solver.objective += value.expression
    else:
        raise TypeError(
            '%r is not a valid objective for %r.' % (value, model.solver))

    context = get_context(model)
    if context:
        def reset():
            model.solver.objective = reverse_value
            model.solver.objective.direction = reverse_value.direction

        context(reset)
def set_objective(model, value, additive=False):
    """Set the model objective.

    Parameters
    ----------
    model : cobra model
       The model to set the objective for
    value : model.problem.Objective,
            e.g. optlang.glpk_interface.Objective, sympy.Basic or dict

        If the model objective is linear, the value can be a new Objective
        object or a dictionary with linear coefficients where each key is a
        reaction and the element the new coefficient (float).

        If the objective is not linear and `additive` is true, only values
        of class Objective.

    additive : boolmodel.reactions.Biomass_Ecoli_core.bounds = (0.1, 0.1)
        If true, add the terms to the current objective, otherwise start with
        an empty objective.
    """
    interface = model.problem
    reverse_value = model.solver.objective.expression
    reverse_value = interface.Objective(
        reverse_value, direction=model.solver.objective.direction,
        sloppy=True)

    if isinstance(value, dict):
        if not model.objective.is_Linear:
            raise ValueError('can only update non-linear objectives '
                             'additively using object of class '
                             'model.problem.Objective, not %s' %
                             type(value))

        if not additive:
            model.solver.objective = interface.Objective(
                Zero, direction=model.solver.objective.direction)
        for reaction, coef in value.items():
            model.solver.objective.set_linear_coefficients(
                {reaction.forward_variable: coef,
                 reaction.reverse_variable: -coef})

    elif isinstance(value, (Basic, optlang.interface.Objective)):
        if isinstance(value, Basic):
            value = interface.Objective(
                value, direction=model.solver.objective.direction,
                sloppy=False)
        # Check whether expression only uses variables from current model
        # clone the objective if not, faster than cloning without checking
        if not _valid_atoms(model, value.expression):
            value = interface.Objective.clone(value, model=model.solver)

        if not additive:
            model.solver.objective = value
        else:
            model.solver.objective += value.expression
    else:
        raise TypeError(
            '%r is not a valid objective for %r.' % (value, model.solver))

    context = get_context(model)
    if context:
        def reset():
            model.solver.objective = reverse_value
            model.solver.objective.direction = reverse_value.direction

        context(reset)
def set_objective ( model , value , additive = False ) : interface = model . problem reverse_value = model . solver . objective . expression reverse_value = interface . Objective ( reverse_value , direction = model . solver . objective . direction , sloppy = True ) if isinstance ( value , dict ) : if not model . objective . is_Linear : raise ValueError ( 'can only update non-linear objectives ' 'additively using object of class ' 'model.problem.Objective, not %s' % type ( value ) ) if not additive : model . solver . objective = interface . Objective ( Zero , direction = model . solver . objective . direction ) for reaction , coef in value . items ( ) : model . solver . objective . set_linear_coefficients ( { reaction . forward_variable : coef , reaction . reverse_variable : - coef } ) elif isinstance ( value , ( Basic , optlang . interface . Objective ) ) : if isinstance ( value , Basic ) : value = interface . Objective ( value , direction = model . solver . objective . direction , sloppy = False ) # Check whether expression only uses variables from current model # clone the objective if not, faster than cloning without checking if not _valid_atoms ( model , value . expression ) : value = interface . Objective . clone ( value , model = model . solver ) if not additive : model . solver . objective = value else : model . solver . objective += value . expression else : raise TypeError ( '%r is not a valid objective for %r.' % ( value , model . solver ) ) context = get_context ( model ) if context : def reset ( ) : model . solver . objective = reverse_value model . solver . objective . direction = reverse_value . direction context ( reset )
Set the model objective.

    Parameters
    ----------
    model : cobra model
       The model to set the objective for
    value : model.problem.Objective,
            e.g. optlang.glpk_interface.Objective, sympy.Basic or dict

        If the model objective is linear, the value can be a new Objective
        object or a dictionary with linear coefficients where each key is a
        reaction and the element the new coefficient (float).

        If the objective is not linear and `additive` is true, only values
        of class Objective.

    additive : boolmodel.reactions.Biomass_Ecoli_core.bounds = (0.1, 0.1)
        If true, add the terms to the current objective, otherwise start with
        an empty objective.
Set the model objective .