test_status.test_non_convex_status_variables() - Code Metrics - Inspection of "Fix/multi place variables" - oemof/oemof-solph - Measure and Improve Code Quality continuously with Scrutinizer

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Pull Request — dev (#1221)

by Patrik

created 2025-10-28 10:44 UTC

test_status.test_non_convex_status_variables() B

↳ Parent: test_status

Complexity

Conditions

Size

Total Lines	64
Code Lines	38

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	38
dl	0
loc	64
rs	8.968
c	0
b	0
f	0
cc	1
nop	0

How to fix Long Method

"""
This integration test validates that the Results object properly merges
status variables from NonConvexFlowBlock and InvestNonConvexFlowBlock
into one DataFrame.

The test scenario is using the following components:
* Gas boiler with insufficient minimal part load to supply heat in time step 2.
* Electrical heater without constraint but high operational costs.
* Heat pump (with extremely low investment costs) but a rather low power limit.
  It can only supply part of the heat. As the electrical heater is always
  needed as a complement, it is only run if the boiler cannot.

SPDX-FileCopyrightText: Patrik Schönfeldt

SPDX-License-Identifier: MIT
"""

import pandas as pd

from oemof import solph


def test_non_convex_status_variables():
    # Energy System
    energy_system = solph.EnergySystem(
        timeindex=pd.date_range(start="2025-01-01 12:00", freq="h", periods=3),
        infer_last_interval=False,
    )

    # Buses
    bus_heat = solph.Bus("heat")

    energy_system.add(bus_heat)

    demand_heat = solph.components.Sink(
        label="demand",
        inputs={bus_heat: solph.Flow(nominal_capacity=5, fix=[0.5, 0.3])},
    )
    energy_system.add(demand_heat)

    # gas boiler with minimal load
    boiler = solph.components.Source(
        label="gb",
        outputs={
            bus_heat: solph.Flow(
                nonconvex=solph.NonConvex(),
                nominal_capacity=5,
                min=0.5,
                variable_costs=0.15,
            ),
        },
    )
    energy_system.add(boiler)

    # heat pump with limited size
    heat_pump = solph.components.Source(
        label="hp",
        outputs={
            bus_heat: solph.Flow(
                nominal_capacity=solph.Investment(maximum=1, ep_costs=0.1),
                min=0.5,
                nonconvex=solph.NonConvex(),
                variable_costs=0.1,
            )
        },
    )
    energy_system.add(heat_pump)

    el_heater = solph.components.Source(
        label="rh",
        outputs={bus_heat: solph.Flow(variable_costs=0.3)},
    )
    energy_system.add(el_heater)

    # Model
    model = solph.Model(energy_system)

    # Optimization
    model.solve(solver="cbc", solve_kwargs={"tee": False})

    results = solph.Results(model)

    assert (results.status[(boiler, bus_heat)] == [1, 0]).all()
    assert (results.status[(heat_pump, bus_heat)] == [0, 1]).all()

    print(results.flow)


if __name__ == "__main__":
    test_non_convex_status_variables()


1			"""
2			This integration test validates that the Results object properly merges
3			status variables from NonConvexFlowBlock and InvestNonConvexFlowBlock
4			into one DataFrame.
5
6			The test scenario is using the following components:
7			* Gas boiler with insufficient minimal part load to supply heat in time step 2.
8			* Electrical heater without constraint but high operational costs.
9			* Heat pump (with extremely low investment costs) but a rather low power limit.
10			It can only supply part of the heat. As the electrical heater is always
11			needed as a complement, it is only run if the boiler cannot.
12
13			SPDX-FileCopyrightText: Patrik Schönfeldt
14
15			SPDX-License-Identifier: MIT
16			"""
17
18			import pandas as pd
19
20			from oemof import solph
21
22
23			def test_non_convex_status_variables():
24			# Energy System
25			energy_system = solph.EnergySystem(
26			timeindex=pd.date_range(start="2025-01-01 12:00", freq="h", periods=3),
27			infer_last_interval=False,
28			)
29
30			# Buses
31			bus_heat = solph.Bus("heat")
32
33			energy_system.add(bus_heat)
34
35			demand_heat = solph.components.Sink(
36			label="demand",
37			inputs={bus_heat: solph.Flow(nominal_capacity=5, fix=[0.5, 0.3])},
38			)
39			energy_system.add(demand_heat)
40
41			# gas boiler with minimal load
42			boiler = solph.components.Source(
43			label="gb",
44			outputs={
45			bus_heat: solph.Flow(
46			nonconvex=solph.NonConvex(),
47			nominal_capacity=5,
48			min=0.5,
49			variable_costs=0.15,
50			),
51			},
52			)
53			energy_system.add(boiler)
54
55			# heat pump with limited size
56			heat_pump = solph.components.Source(
57			label="hp",
58			outputs={
59			bus_heat: solph.Flow(
60			nominal_capacity=solph.Investment(maximum=1, ep_costs=0.1),
61			min=0.5,
62			nonconvex=solph.NonConvex(),
63			variable_costs=0.1,
64			)
65			},
66			)
67			energy_system.add(heat_pump)
68
69			el_heater = solph.components.Source(
70			label="rh",
71			outputs={bus_heat: solph.Flow(variable_costs=0.3)},
72			)
73			energy_system.add(el_heater)
74
75			# Model
76			model = solph.Model(energy_system)
77
78			# Optimization
79			model.solve(solver="cbc", solve_kwargs={"tee": False})
80
81			results = solph.Results(model)
82
83			assert (results.status[(boiler, bus_heat)] == [1, 0]).all()
84			assert (results.status[(heat_pump, bus_heat)] == [0, 1]).all()
85
86			print(results.flow)
87
88
89			if __name__ == "__main__":
90			test_non_convex_status_variables()
91

oemof / oemof-solph

Pull Request — dev (#1221)

test_status.test_non_convex_status_variables() B

Complexity

Size

Duplication

Importance

How to fix Long Method

Long Method

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