Broke the code out into separate functions and added capacity constraint

@constraint()

def same_converter_constraint(hubs):

    pass

def same_converter_constraint(converter, hubs):

    """

    Constraint to ensure the capacities are kept constant across all the subproblems. 

    """

    first = True

    for i in enumerate(hubs):

        if not first:

            yield hubs[i-1].capacities[converter] == hubs[i].capacities[converter]

            first = False

def periodic_subproblem(excel=None, request=None, output_filename=None, max_carbon=None, num_periods=1, len_periods=24, solver='glpk'):

def split_hubs(excel=None, request=None, max_carbon=None, num_periods=1, len_periods=24):

    """

    Core function for splitting a PyEHub model into smaller problems to solve together.

    :param: excel

    Splits a PyEHub into a series of smaller hubs with a given period.

    """

    if excel:

        request = excel_to_request_format.convert(excel)

    hubs = []

    if ((num_periods*len_periods) > len(request['time_series'][0]['data'])):

        raise IndexError("Not enough data to cover all the periods.")

    for i in range(0, num_periods):

        temp_request = copy.deepcopy(request)

        for stream in temp_request['time_series']:

            stream['data'] = stream['data'][i*len_periods:(i+1)*len_periods]

        hub = EHubModel(request=temp_request, max_carbon=max_carbon)

        hubs.append(hub)

    return hubs

def merge_hubs(hubs):

    """

    Compiles and combines

    """

    constraints = []

    for hub in hubs:

        hub.recompile()

        for constr in hub.constraints:

            constraints.append(constr)

    for converter in hubs[0]._data.converter_names:

        for c in same_converter_constraint(converter, hubs):

            constraints.append(c)

    return constraints

def run_split_period(excel=None, request=None, output_filename=None, max_carbon=None, num_periods=1, len_periods=24, solver='glpk'):

    """

    Core function for splitting a PyEHub model into smaller problems to solve together.

    """

    hubs = split_hubs(excel, request, max_carbon, num_periods, len_periods)

    constraints = merge_hubs(hubs)

    #TODO: Make sure storage looping is working for each sub_hub

    #FIXME: Ralph had specific instructions for how to handle the objective (wanting a single one or something)

    for hub in hubs[1:]:

        objective += hub.objective

    status = pylp.solve(objective=objective, constraints=constraints, minimize=True, solver=solver)

    #TODO: Figure out setting up the output

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