plots_grids.plot_dispatch_invest() - Code Metrics - Inspection of "Revision/cleanup ci" - oemof/oemof-solph - Measure and Improve Code Quality continuously with Scrutinizer

Passed

Pull Request — dev (#1208)

by Patrik

created 2025-08-20 07:01 UTC

plots_grids.plot_dispatch_invest() C

↳ Parent: plots_grids

Complexity

Conditions

Size

Total Lines	85
Code Lines	56

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	56
dl	0
loc	85
rs	6.1066
c	0
b	0
f	0
cc	9
nop	2

How to fix Long Method

import os
import matplotlib.colors as mcolors
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# creates the icons in the grid view of the documentation


def hex_from_rgb(rgb):
    """makes rgb to hex"""
    return "#{:02X}{:02X}{:02X}".format(
        int(rgb[0] * 255), int(rgb[1] * 255), int(rgb[2] * 255)
    )


# colors of the color palette
dark_palette = {
    "color1": "#1F567D",
    "color2": "#8AA8A1",
    "color3": "#FA8334",
    "color4": "#FF006E",
    "color5": "#FFFD77",
}

# crates light mode color palet
light_palette = {"color1": dark_palette["color1"]}
for key in ["color2", "color3", "color4", "color5"]:
    rgb = mcolors.to_rgb(dark_palette[key])
    new_rgb = [0.7 * c + 0.3 for c in rgb]
    light_palette[key] = hex_from_rgb(new_rgb)


def draw_lin_vs_mixed_int(mode="dark"):
    """
    draws plot for the linear optimization vs. Mix Integer section
    """
    if mode == "dark":
        palette = dark_palette
        bg_color = "#121212"
        text_color = "#FFFFFF"
    else:
        palette = light_palette
        bg_color = "#FFFFFF"
        text_color = "#000000"

    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))
    fig.patch.set_facecolor(bg_color)

    for ax in [ax1, ax2]:
        ax.set_facecolor(bg_color)
        ax.tick_params(colors=text_color)
        for spine in ax.spines.values():
            spine.set_color(text_color)

    # linear function
    x = np.linspace(-10, 10, 400)
    y = 2 * x + 1
    ax1.plot(x, y, color=palette["color1"], linewidth=2)
    ax1.set_title("Linear Programming", color=text_color, fontsize=14)
    ax1.set_xticks([])
    ax1.set_yticks([])

    # function including a jump
    x_left = np.linspace(-10, -0.01, 200)
    x_right = np.linspace(0, 10, 200)
    y_left = 2 * x_left + 1
    y_right = 2 * x_right + 1 + 5

    ax2.plot(x_left, y_left, color=palette["color1"], linewidth=2)
    ax2.plot(x_right, y_right, color=palette["color3"], linewidth=2)

    # setting maker for the jump
    ax2.plot(
        x_left[-1],
        y_left[-1],
        marker="o",
        markersize=8,
        markerfacecolor=bg_color,
        markeredgecolor=palette["color4"],
        markeredgewidth=2,
    )
    ax2.plot(
        x_right[0],
        y_right[0],
        marker="o",
        markersize=8,
        markerfacecolor=palette["color4"],
        markeredgecolor=palette["color4"],
    )

    ax2.set_title("Mixed-Integer Problem", color=text_color, fontsize=14)
    ax2.set_xticks([])
    ax2.set_yticks([])

    plt.tight_layout()

    # save the plot
    if mode == "dark":

        plt.savefig("lin_vs_mixed_int_plot_dark.png")
    if mode == "light":

        plt.savefig("lin_vs_mixed_int_plot_light.png")


def draw_timeline(mode="dark", savefig_filename=None):
    """
    draws timeline for the multiperiod icon
    """
    if mode == "dark":
        palette = dark_palette
        bg_color = "#121212"
        text_color = "#FFFFFF"
    else:
        palette = light_palette
        bg_color = "#FFFFFF"
        text_color = "#000000"

    fig, ax = plt.subplots(figsize=(10, 3))
    fig.patch.set_facecolor(bg_color)
    ax.set_facecolor(bg_color)

    for spine in ax.spines.values():
        spine.set_visible(False)
    ax.tick_params(
        left=False, bottom=False, labelbottom=False, labelleft=False
    )

    years = list(range(2020, 2031))

    # draw line
    ax.plot(
        [years[0], years[-1]], [0, 0], color=palette["color1"], linewidth=2
    )

    # set markings for every year
    for i, year in enumerate(years):
        ax.plot(year, 0, marker="o", markersize=8, color=palette["color3"])
        ax.text(
            year,
            -0.3,
            str(year),
            ha="center",
            va="top",
            color=text_color,
            fontsize=10,
        )
        ax.text(
            year,
            0.3,
            f"Period {i+1}",
            ha="center",
            va="bottom",
            color=text_color,
            fontsize=10,
        )

    # Set title
    ax.text(
        (years[0] + years[-1]) / 2,
        0.8,
        "Multi-period Optimization",
        ha="center",
        va="bottom",
        color=text_color,
        fontsize=14,
        fontweight="bold",
    )

    ax.set_xlim(years[0] - 1, years[-1] + 1)
    ax.set_ylim(-1, 1)

    plt.tight_layout()

    # save png
    if mode == "dark":

        plt.savefig("timeline_dark.png")
    if mode == "light":

        plt.savefig("timeline_light.png")


def plot_dispatch_invest(csv_path, mode="dark"):
    """
    draws a demand timeseries next to an bar plot symbolizing the investment decisions
    """

    df = pd.read_csv(csv_path)

    if "Time" not in df.columns:
        df["Time"] = pd.date_range(
            start="2020-01-01", periods=len(df), freq="H"
        )

    if mode.lower() == "dark":
        palette = dark_palette
        bg_color = "#121212"
        text_color = "#FFFFFF"
    else:
        palette = light_palette
        bg_color = "#FFFFFF"
        text_color = "#000000"

    # create two subplots
    fig, axs = plt.subplots(1, 2, figsize=(16, 6))
    fig.patch.set_facecolor(bg_color)

    ax1 = axs[0]
    ax1.set_facecolor(bg_color)
    for spine in ax1.spines.values():
        spine.set_color(text_color)
    ax1.tick_params(colors=text_color, labelleft=False)

    # draw dispatch timeseries
    ax1.plot(
        df["Time"],
        df["demand_th"],
        marker="o",
        linestyle="-",
        color=palette["color1"],
        linewidth=2,
    )
    ax1.set_title("Dispatch Time Series (kW)", color=text_color, fontsize=14)
    ax1.set_xlabel("Time", color=text_color)
    ax1.set_ylabel("kW", color=text_color)

    avg_pv = df["pv"].mean() if "pv" in df.columns else 0
    avg_wind = df["wind"].mean() if "wind" in df.columns else 0
    avg_heatpump = 0.3
    avg_solarthermie = 0.09

    labels = ["PV", "Wind", "Heat Pump", "Solarthermie"]
    values = [avg_pv, avg_wind, avg_heatpump, avg_solarthermie]

    bar_colors = [
        palette["color3"],
        palette["color4"],
        palette["color2"],
        palette["color5"],
    ]

    ax2 = axs[1]
    ax2.set_facecolor(bg_color)
    for spine in ax2.spines.values():
        spine.set_color(text_color)
    ax2.tick_params(colors=text_color, labelleft=False)

    bars = ax2.bar(
        labels, values, color=bar_colors, edgecolor=text_color, linewidth=1.5
    )

    ax2.set_title("Investment Technology Sizes", color=text_color, fontsize=14)
    ax2.set_ylabel("Average Value", color=text_color, fontsize=14)

    fig.suptitle(
        "Dispatch vs. Invest-Optimization", color=text_color, fontsize=16
    )

    plt.tight_layout(rect=[0, 0, 1, 0.95])

    # save plots
    if mode == "dark":

        plt.savefig("plot_dispatch_invest_dark.png")
    if mode == "light":

        plt.savefig("plot_dispatch_invest_light.png")


# uncomment he needed funczion to redraw the icons

# draw_lin_vs_mixed_int('light')
# draw_lin_vs_mixed_int('dark')

# draw_timeline("dark")  # Speichert als "timeline_dark.png"
# draw_timeline("light")  # Speichert als "timeline_light.png"

file_name = os.path.realpath(
    os.path.join(
        __file__,
        "..",
        "..",
        "..",
        "..",
        "tests/test_outputlib/input_data.csv",
    )
)
plot_dispatch_invest(file_name, mode="light")
plot_dispatch_invest(file_name, mode="dark")


1			import os
2			import matplotlib.colors as mcolors
3			import matplotlib.pyplot as plt
4			import numpy as np
5			import pandas as pd
6
7			# creates the icons in the grid view of the documentation
8
9
10			def hex_from_rgb(rgb):
11			"""makes rgb to hex"""
12			return "#{:02X}{:02X}{:02X}".format(
13			int(rgb[0] * 255), int(rgb[1] * 255), int(rgb[2] * 255)
14			)
15
16
17			# colors of the color palette
18			dark_palette = {
19			"color1": "#1F567D",
20			"color2": "#8AA8A1",
21			"color3": "#FA8334",
22			"color4": "#FF006E",
23			"color5": "#FFFD77",
24			}
25
26			# crates light mode color palet
27			light_palette = {"color1": dark_palette["color1"]}
28			for key in ["color2", "color3", "color4", "color5"]:
29			rgb = mcolors.to_rgb(dark_palette[key])
30			new_rgb = [0.7 * c + 0.3 for c in rgb]
31			light_palette[key] = hex_from_rgb(new_rgb)
32
33
34			def draw_lin_vs_mixed_int(mode="dark"):
35			"""
36			draws plot for the linear optimization vs. Mix Integer section
37			"""
38			if mode == "dark":
39			palette = dark_palette
40			bg_color = "#121212"
41			text_color = "#FFFFFF"
42			else:
43			palette = light_palette
44			bg_color = "#FFFFFF"
45			text_color = "#000000"
46
47			fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))
48			fig.patch.set_facecolor(bg_color)
49
50			for ax in [ax1, ax2]:
51			ax.set_facecolor(bg_color)
52			ax.tick_params(colors=text_color)
53			for spine in ax.spines.values():
54			spine.set_color(text_color)
55
56			# linear function
57			x = np.linspace(-10, 10, 400)
58			y = 2 * x + 1
59			ax1.plot(x, y, color=palette["color1"], linewidth=2)
60			ax1.set_title("Linear Programming", color=text_color, fontsize=14)
61			ax1.set_xticks([])
62			ax1.set_yticks([])
63
64			# function including a jump
65			x_left = np.linspace(-10, -0.01, 200)
66			x_right = np.linspace(0, 10, 200)
67			y_left = 2 * x_left + 1
68			y_right = 2 * x_right + 1 + 5
69
70			ax2.plot(x_left, y_left, color=palette["color1"], linewidth=2)
71			ax2.plot(x_right, y_right, color=palette["color3"], linewidth=2)
72
73			# setting maker for the jump
74			ax2.plot(
75			x_left[-1],
76			y_left[-1],
77			marker="o",
78			markersize=8,
79			markerfacecolor=bg_color,
80			markeredgecolor=palette["color4"],
81			markeredgewidth=2,
82			)
83			ax2.plot(
84			x_right[0],
85			y_right[0],
86			marker="o",
87			markersize=8,
88			markerfacecolor=palette["color4"],
89			markeredgecolor=palette["color4"],
90			)
91
92			ax2.set_title("Mixed-Integer Problem", color=text_color, fontsize=14)
93			ax2.set_xticks([])
94			ax2.set_yticks([])
95
96			plt.tight_layout()
97
98			# save the plot
99			if mode == "dark":
100
101			plt.savefig("lin_vs_mixed_int_plot_dark.png")
102			if mode == "light":
103
104			plt.savefig("lin_vs_mixed_int_plot_light.png")
105
106
107			def draw_timeline(mode="dark", savefig_filename=None):
108			"""
109			draws timeline for the multiperiod icon
110			"""
111			if mode == "dark":
112			palette = dark_palette
113			bg_color = "#121212"
114			text_color = "#FFFFFF"
115			else:
116			palette = light_palette
117			bg_color = "#FFFFFF"
118			text_color = "#000000"
119
120			fig, ax = plt.subplots(figsize=(10, 3))
121			fig.patch.set_facecolor(bg_color)
122			ax.set_facecolor(bg_color)
123
124			for spine in ax.spines.values():
125			spine.set_visible(False)
126			ax.tick_params(
127			left=False, bottom=False, labelbottom=False, labelleft=False
128			)
129
130			years = list(range(2020, 2031))
131
132			# draw line
133			ax.plot(
134			[years[0], years[-1]], [0, 0], color=palette["color1"], linewidth=2
135			)
136
137			# set markings for every year
138			for i, year in enumerate(years):
139			ax.plot(year, 0, marker="o", markersize=8, color=palette["color3"])
140			ax.text(
141			year,
142			-0.3,
143			str(year),
144			ha="center",
145			va="top",
146			color=text_color,
147			fontsize=10,
148			)
149			ax.text(
150			year,
151			0.3,
152			f"Period {i+1}",
153			ha="center",
154			va="bottom",
155			color=text_color,
156			fontsize=10,
157			)
158
159			# Set title
160			ax.text(
161			(years[0] + years[-1]) / 2,
162			0.8,
163			"Multi-period Optimization",
164			ha="center",
165			va="bottom",
166			color=text_color,
167			fontsize=14,
168			fontweight="bold",
169			)
170
171			ax.set_xlim(years[0] - 1, years[-1] + 1)
172			ax.set_ylim(-1, 1)
173
174			plt.tight_layout()
175
176			# save png
177			if mode == "dark":
178
179			plt.savefig("timeline_dark.png")
180			if mode == "light":
181
182			plt.savefig("timeline_light.png")
183
184
185			def plot_dispatch_invest(csv_path, mode="dark"):
186			"""
187			draws a demand timeseries next to an bar plot symbolizing the investment decisions
188			"""
189
190			df = pd.read_csv(csv_path)
191
192			if "Time" not in df.columns:
193			df["Time"] = pd.date_range(
194			start="2020-01-01", periods=len(df), freq="H"
195			)
196
197			if mode.lower() == "dark":
198			palette = dark_palette
199			bg_color = "#121212"
200			text_color = "#FFFFFF"
201			else:
202			palette = light_palette
203			bg_color = "#FFFFFF"
204			text_color = "#000000"
205
206			# create two subplots
207			fig, axs = plt.subplots(1, 2, figsize=(16, 6))
208			fig.patch.set_facecolor(bg_color)
209
210			ax1 = axs[0]
211			ax1.set_facecolor(bg_color)
212			for spine in ax1.spines.values():
213			spine.set_color(text_color)
214			ax1.tick_params(colors=text_color, labelleft=False)
215
216			# draw dispatch timeseries
217			ax1.plot(
218			df["Time"],
219			df["demand_th"],
220			marker="o",
221			linestyle="-",
222			color=palette["color1"],
223			linewidth=2,
224			)
225			ax1.set_title("Dispatch Time Series (kW)", color=text_color, fontsize=14)
226			ax1.set_xlabel("Time", color=text_color)
227			ax1.set_ylabel("kW", color=text_color)
228
229			avg_pv = df["pv"].mean() if "pv" in df.columns else 0
230			avg_wind = df["wind"].mean() if "wind" in df.columns else 0
231			avg_heatpump = 0.3
232			avg_solarthermie = 0.09
233
234			labels = ["PV", "Wind", "Heat Pump", "Solarthermie"]
235			values = [avg_pv, avg_wind, avg_heatpump, avg_solarthermie]
236
237			bar_colors = [
238			palette["color3"],
239			palette["color4"],
240			palette["color2"],
241			palette["color5"],
242			]
243
244			ax2 = axs[1]
245			ax2.set_facecolor(bg_color)
246			for spine in ax2.spines.values():
247			spine.set_color(text_color)
248			ax2.tick_params(colors=text_color, labelleft=False)
249
250			bars = ax2.bar(
251			labels, values, color=bar_colors, edgecolor=text_color, linewidth=1.5
252			)
253
254			ax2.set_title("Investment Technology Sizes", color=text_color, fontsize=14)
255			ax2.set_ylabel("Average Value", color=text_color, fontsize=14)
256
257			fig.suptitle(
258			"Dispatch vs. Invest-Optimization", color=text_color, fontsize=16
259			)
260
261			plt.tight_layout(rect=[0, 0, 1, 0.95])
262
263			# save plots
264			if mode == "dark":
265
266			plt.savefig("plot_dispatch_invest_dark.png")
267			if mode == "light":
268
269			plt.savefig("plot_dispatch_invest_light.png")
270
271
272			# uncomment he needed funczion to redraw the icons
273
274			# draw_lin_vs_mixed_int('light')
275			# draw_lin_vs_mixed_int('dark')
276
277			# draw_timeline("dark") # Speichert als "timeline_dark.png"
278			# draw_timeline("light") # Speichert als "timeline_light.png"
279
280			file_name = os.path.realpath(
281			os.path.join(
282			__file__,
283			"..",
284			"..",
285			"..",
286			"..",
287			"tests/test_outputlib/input_data.csv",
288			)
289			)
290			plot_dispatch_invest(file_name, mode="light")
291			plot_dispatch_invest(file_name, mode="dark")
292

oemof / oemof-solph

Pull Request — dev (#1208)

plots_grids.plot_dispatch_invest() C

Complexity

Size

Duplication

Importance

How to fix Long Method

Long Method

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