# -*- coding: utf-8 -*-

import pandas as pd
import networkx as nx
from matplotlib import pyplot as plt

# solph imports
from oemof.solph.exnet import *
from oemof.solph import *
from oemof.outputlib import processing, views
from oemof.graph import create_nx_graph
from collections import namedtuple
from oemof.solph.exnet import *
# from oemof.network_graph import *
from oemof.graph import create_nx_graph

def draw_graph(grph, edge_labels=True, node_color='#AFAFAF',
               edge_color='#CFCFCF', plot=True, node_size=2000,
               with_labels=True, arrows=True, layout='neato'):
    """
    Parameters
    ----------
    grph : networkxGraph
        A graph to draw.
    edge_labels : boolean
        Use nominal values of flow as edge label
    node_color : dict or string
        Hex color code oder matplotlib color for each node. If string, all
        colors are the same.

    edge_color : string
        Hex color code oder matplotlib color for edge color.

    plot : boolean
        Show matplotlib plot.

    node_size : integer
        Size of nodes.

    with_labels : boolean
        Draw node labels.

    arrows : boolean
        Draw arrows on directed edges. Works only if an optimization_model has
        been passed.
    layout : string
        networkx graph layout, one of: neato, dot, twopi, circo, fdp, sfdp.
    """
    if type(node_color) is dict:
        node_color = [node_color.get(g, '#AFAFAF') for g in grph.nodes()]

    # set drawing options
    options = {
        'prog': 'dot',
        'with_labels': with_labels,
        'node_color': node_color,
        'edge_color': edge_color,
        'node_size': node_size,
        'arrows': arrows,
        'font_size': 6
    }

    # try to use pygraphviz for graph layout
    try:
        import pygraphviz
        pos = nx.drawing.nx_agraph.graphviz_layout(grph, prog=layout)
    except ImportError:
        logging.error('Module pygraphviz not found, I won\'t plot the graph.')
        return

    # draw graph
    nx.draw(grph, pos=pos, **options)

    # add edge labels for all edges
    if edge_labels is True and plt:
        labels = nx.get_edge_attributes(grph, 'weight')
        nx.draw_networkx_edge_labels(grph, pos=pos, edge_labels=labels)

    # show output
    if plot is True:
        plt.show()






class Label(namedtuple('label', ['location','name', 'energy_carrier'])):
    __slots__ = ()
    def __str__(self):
        return '_'.join(map(str, self._asdict().values()))

datetimeindex = pd.date_range('1/1/2017', periods=2, freq='H')

es = EnergySystem(timeindex=datetimeindex)

b_Electrical1 = ElectricalBus(label=Label(name='b_Electrical1', location='C1', energy_carrier=''), v_min=-0.12, v_max=1)

b_Electrical2 = ElectricalBus(label=Label(name='b_Electrical2', location='C2', energy_carrier=''), v_min=-0.12, v_max=1)

b_Electrical3 = ElectricalBus(label=Label(name='b_Electrical3', location='C2', energy_carrier=''), v_min=-0.12, v_max=1)

b_Electrical4 = ElectricalBus(label=Label(name='b_Electrical4', location='C1', energy_carrier=''), v_min=-0.12, v_max=1)

source_1 = Source(label="source_1", outputs={b_Electrical1: Flow(nominal_value=100,variable_costs=25)})

sink_1 = Sink(label="load", inputs={b_Electrical4: Flow(nominal_value=25, actual_value=[1, 1], fixed=True)})

Electricallline_1=ElectricalLine(label="line1",
                      inputs={b_Electrical1: Flow()},
                      outputs={b_Electrical2: Flow(nominal_value=100,variable_costs=0, min=0, max=1)},
                      reactance=0.01)

Electricallline_2=ElectricalLine(label="line2",
                      inputs={b_Electrical1: Flow()},
                      outputs={b_Electrical3: Flow(nominal_value=100,variable_costs=25,min=0, max=1)},
                      reactance=0.01)

Electricallline_3=ElectricalLine(label="line3",
                      inputs={b_Electrical2: Flow()},
                      outputs={b_Electrical4: Flow(nominal_value=100,variable_costs=25,min=0, max=1)},
                      reactance=0.01)

Electricallline_4=ElectricalLine(label="line4",
                      inputs={b_Electrical3: Flow()},
                      outputs={b_Electrical4: Flow(nominal_value=100,variable_costs=25,min=0, max=1)},
                      reactance=0.01)

es.add(b_Electrical1)
es.add(b_Electrical2)
es.add(b_Electrical3)
es.add(b_Electrical4)
es.add(Electricallline_1)
es.add(Electricallline_2)
es.add(Electricallline_3)
es.add(Electricallline_4)
es.add(source_1)
es.add(sink_1)


model=Model(es)

model.x=variable()

graph=create_nx_graph(es)
# #draw_graph(g)



model.write('lopf.lp', io_options={'symbolic_solver_labels': True})

model.solve(solver='gurobi', solve_kwargs={'tee': True, 'keepfiles': False})


model.results()
results = processing.results(model)


draw_graph(grph=graph, plot=True, layout='neato', node_size=500)