tritium_consumption_plot.py

import matplotlib.pyplot as plt
import squarify
import pandas as pd
from pypalettes import load_cmap
from highlight_text import fig_text


dark_mode = True

cmap = load_cmap("Acadia")

# data from https://doi.org/10.1016/j.fusengdes.2018.04.090
df = pd.DataFrame(
    {
        "rate": [2.5, 34, 50],
        "label": [
            "Average tritium production (1 year)",
            "Available tritium reserves (2018)",
            "Consuption of a 1 GWth \n fusion reactor (1 year)",
        ],
    }
)

labels = [f"{name} \n{value} kg" for name, value in zip(df["label"], df["rate"])]
colours = [cmap(i + 2) for i, _ in enumerate(df["rate"])]

plt.figure(figsize=(10, 8))
squarify.plot(
    sizes=df["rate"],
    label=labels,
    pad=True,
    color=colours,
    text_kwargs={"color": "white", "fontsize": 9, "fontweight": "bold"},
)
plt.axis("off")

if dark_mode:
    title_color = "white"
    text_color = "white"
else:
    title_color = "black"
    text_color = "gray"

text = """<The tritium issue>
<Data source: Pearson et al, Fusion Engineering and Design 136 (2018) 1140–1148>
"""
fig_text(
    x=0.133,
    y=0.98,
    s=text,
    color="black",
    highlight_textprops=[
        {"fontsize": 20, "fontweight": "bold", "color": title_color},
        {"fontsize": 9, "color": text_color},
    ],
    fontsize=14,
    ha="left",
)

plt.savefig("tritium_consumption.svg", bbox_inches="tight", transparent=True)

plt.show()