lopf.draw_graph() - Code Metrics - Inspection of "Add examples from oemof-examples" - oemof/oemof-solph - Measure and Improve Code Quality continuously with Scrutinizer

Passed

Pull Request — dev (#850)

by Uwe

created 2022-11-10 14:13 UTC

lopf.draw_graph() B

↳ Parent: lopf

Complexity

Conditions

Size

Total Lines	68
Code Lines	25

Duplication

Lines	68
Ratio	100 %

Importance

Changes

Metric	Value
eloc	25
dl	68
loc	68
rs	8.8133
c	0
b	0
f	0
cc	5
nop	9

How to fix Long Method Many Parameters

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

"""
General description
-------------------
This script shows how to do a linear optimal powerflow (lopf) calculation
based on custom oemof components. The example is based on the PyPSA
simple lopf example.

Note: As oemof currently does not support models with one timesteps, therefore
there are two.

Installation requirements
-------------------------
This example requires oemof.solph (v0.5.x), install by:

    pip install oemof.solph[examples]

To draw the graph pygraphviz is required, installed by:

    pip install pygraphviz

License
-------
Simon Hilpert - 12.12.2017 - [email protected]

`MIT license <https://github.com/oemof/oemof-solph/blob/dev/LICENSE>`_

"""
import networkx as nx
import pandas as pd
from matplotlib import pyplot as plt
from oemof.network.graph import create_nx_graph
from oemof.solph import EnergySystem, Investment, Model, processing, views
from oemof.solph.components import Sink, Source
from oemof.solph.buses.experimental import ElectricalBus
from oemof.solph.flows.experimental import ElectricalLine
from oemof.solph.flows import Flow

try:
    import pygraphviz as pygz
except ModuleNotFoundError:
    pygz = None


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",
):
    """
    Draw a graph. This function will be removed in future versions.

    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 isinstance(node_color, 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,
    }

    # draw graph
    pos = nx.drawing.nx_agraph.graphviz_layout(grph, prog=layout)

    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()


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

es = EnergySystem(timeindex=datetimeindex)

b_el0 = ElectricalBus(label="b_0", v_min=-1, v_max=1)

b_el1 = ElectricalBus(label="b_1", v_min=-1, v_max=1)

b_el2 = ElectricalBus(label="b_2", v_min=-1, v_max=1)

es.add(b_el0, b_el1, b_el2)

es.add(
    ElectricalLine(
        input=b_el0,
        output=b_el1,
        reactance=0.0001,
        investment=Investment(ep_costs=10),
        min=-1,
        max=1,
    )
)

es.add(
    ElectricalLine(
        input=b_el1,
        output=b_el2,
        reactance=0.0001,
        nominal_value=60,
        min=-1,
        max=1,
    )
)

es.add(
    ElectricalLine(
        input=b_el2,
        output=b_el0,
        reactance=0.0001,
        nominal_value=60,
        min=-1,
        max=1,
    )
)

es.add(
    Source(
        label="gen_0",
        outputs={b_el0: Flow(nominal_value=100, variable_costs=50)},
    )
)

es.add(
    Source(
        label="gen_1",
        outputs={b_el1: Flow(nominal_value=100, variable_costs=25)},
    )
)

es.add(Sink(label="load", inputs={b_el2: Flow(nominal_value=100, fix=[1, 1])}))

m = Model(energysystem=es)

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

m.solve(solver="cbc", solve_kwargs={"tee": True, "keepfiles": False})


m.results()

graph = create_nx_graph(es)

if pygz is not None:
    draw_graph(
        graph,
        plot=True,
        layout="neato",
        node_size=3000,
        node_color={"b_0": "#cd3333", "b_1": "#7EC0EE", "b_2": "#eeac7e"},
    )


results = processing.results(m)

print(views.node(results, "gen_0")["sequences"])
print(views.node(results, "gen_1")["sequences"])
print(views.node(results, "load")["sequences"])


1		# -- coding: utf-8 --
2
3		"""
4		General description
5		-------------------
6		This script shows how to do a linear optimal powerflow (lopf) calculation
7		based on custom oemof components. The example is based on the PyPSA
8		simple lopf example.
9
10		Note: As oemof currently does not support models with one timesteps, therefore
11		there are two.
12
13		Installation requirements
14		-------------------------
15		This example requires oemof.solph (v0.5.x), install by:
16
17		pip install oemof.solph[examples]
18
19		To draw the graph pygraphviz is required, installed by:
20
21		pip install pygraphviz
22
23		License
24		-------
25		Simon Hilpert - 12.12.2017 - [email protected]
26
27		`MIT license <https://github.com/oemof/oemof-solph/blob/dev/LICENSE>`_
28
29		"""
30		import networkx as nx
31		import pandas as pd
32		from matplotlib import pyplot as plt
33		from oemof.network.graph import create_nx_graph
34		from oemof.solph import EnergySystem, Investment, Model, processing, views
35		from oemof.solph.components import Sink, Source
36		from oemof.solph.buses.experimental import ElectricalBus
37		from oemof.solph.flows.experimental import ElectricalLine
38		from oemof.solph.flows import Flow
39
40		try:
41		import pygraphviz as pygz
42		except ModuleNotFoundError:
43		pygz = None
44
45
46	View Code Duplication	def draw_graph(
		0 ignored issues – show Duplication introduced 2022-06-24 10:10 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
47		grph,
48		edge_labels=True,
49		node_color="#AFAFAF",
50		edge_color="#CFCFCF",
51		plot=True,
52		node_size=2000,
53		with_labels=True,
54		arrows=True,
55		layout="neato",
56		):
57		"""
58		Draw a graph. This function will be removed in future versions.
59
60		Parameters
61		----------
62		grph : networkxGraph
63		A graph to draw.
64		edge_labels : boolean
65		Use nominal values of flow as edge label
66		node_color : dict or string
67		Hex color code oder matplotlib color for each node. If string, all
68		colors are the same.
69
70		edge_color : string
71		Hex color code oder matplotlib color for edge color.
72
73		plot : boolean
74		Show matplotlib plot.
75
76		node_size : integer
77		Size of nodes.
78
79		with_labels : boolean
80		Draw node labels.
81
82		arrows : boolean
83		Draw arrows on directed edges. Works only if an optimization_model has
84		been passed.
85		layout : string
86		networkx graph layout, one of: neato, dot, twopi, circo, fdp, sfdp.
87		"""
88		if isinstance(node_color, dict):
89		node_color = [node_color.get(g, "#AFAFAF") for g in grph.nodes()]
90
91		# set drawing options
92		options = {
93		# "prog": "dot",
94		"with_labels": with_labels,
95		"node_color": node_color,
96		"edge_color": edge_color,
97		"node_size": node_size,
98		"arrows": arrows,
99		}
100
101		# draw graph
102		pos = nx.drawing.nx_agraph.graphviz_layout(grph, prog=layout)
103
104		nx.draw(grph, pos=pos, **options)
105
106		# add edge labels for all edges
107		if edge_labels is True and plt:
108		labels = nx.get_edge_attributes(grph, "weight")
109		nx.draw_networkx_edge_labels(grph, pos=pos, edge_labels=labels)
110
111		# show output
112		if plot is True:
113		plt.show()
114
115
116		datetimeindex = pd.date_range("1/1/2017", periods=2, freq="H")
117
118		es = EnergySystem(timeindex=datetimeindex)
119
120		b_el0 = ElectricalBus(label="b_0", v_min=-1, v_max=1)
121
122		b_el1 = ElectricalBus(label="b_1", v_min=-1, v_max=1)
123
124		b_el2 = ElectricalBus(label="b_2", v_min=-1, v_max=1)
125
126		es.add(b_el0, b_el1, b_el2)
127
128		es.add(
129		ElectricalLine(
130		input=b_el0,
131		output=b_el1,
132		reactance=0.0001,
133		investment=Investment(ep_costs=10),
134		min=-1,
135		max=1,
136		)
137		)
138
139		es.add(
140		ElectricalLine(
141		input=b_el1,
142		output=b_el2,
143		reactance=0.0001,
144		nominal_value=60,
145		min=-1,
146		max=1,
147		)
148		)
149
150		es.add(
151		ElectricalLine(
152		input=b_el2,
153		output=b_el0,
154		reactance=0.0001,
155		nominal_value=60,
156		min=-1,
157		max=1,
158		)
159		)
160
161		es.add(
162		Source(
163		label="gen_0",
164		outputs={b_el0: Flow(nominal_value=100, variable_costs=50)},
165		)
166		)
167
168		es.add(
169		Source(
170		label="gen_1",
171		outputs={b_el1: Flow(nominal_value=100, variable_costs=25)},
172		)
173		)
174
175		es.add(Sink(label="load", inputs={b_el2: Flow(nominal_value=100, fix=[1, 1])}))
176
177		m = Model(energysystem=es)
178
179		# m.write('lopf.lp', io_options={'symbolic_solver_labels': True})
180
181		m.solve(solver="cbc", solve_kwargs={"tee": True, "keepfiles": False})
182
183
184		m.results()
185
186		graph = create_nx_graph(es)
187
188		if pygz is not None:
189		draw_graph(
190		graph,
191		plot=True,
192		layout="neato",
193		node_size=3000,
194		node_color={"b_0": "#cd3333", "b_1": "#7EC0EE", "b_2": "#eeac7e"},
195		)
196
197
198		results = processing.results(m)
199
200		print(views.node(results, "gen_0")["sequences"])
201		print(views.node(results, "gen_1")["sequences"])
202		print(views.node(results, "load")["sequences"])
203

oemof / oemof-solph

Pull Request — dev (#850)

lopf.draw_graph() B

Complexity

Size

Duplication

Importance

How to fix Long Method Many Parameters

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