#!/usr/bin/env python3
from matplotlib import pyplot as plt

# (name, MJ/kg, MJ/L, [label position, default = 'right'])
data = (
    ('Aluminum', 31.0, 83.8),
    ('Anthracite', 32.5, 72.4),
    ('Bituminous', 24, 20),
    ('Butanol', 36.6, 29.2, 'left'),
    ('Diesel', 46.2, 37.3),
    ('Ethanol', 30, 24, 'left'),
    ('Fat\nmetabolism\n', 38, 35, 'top'),
    ('Gasoline', 46.4, 34.2),
    ('Gasohol E85', 33.1, 25.65),
    ('Glucose', 15.55, 23.9, 'left'),
    ('Hydrazine', 19.5, 19.3, 'left'),
    ('Hydrogen gas', 143, 0.01079, 'top'),
    ('Hydrogen gas (700 bar)', 143, 5.6, 'top'),
    ('Iron', 5.2, 40.68),  # (burned to Fe2O3)
    ('Kerosene', 42.8, 33, 'bottom'),
    ('Liquid ammonia', 18.6, 11.5),
    ('Liquid hydrogen', 143, 10.1, 'top'),
    ('Liquid natural gas', 53.6, 22.2),
    ('Lithium', 43.1, 23.0, 'bottom'),
    ('Lithium borohydride', 65.2, 43.4),
    ('LPG propane', 49.6, 25.3),
    ('LPG butane', 49.1, 27.7),
    ('Magnesium', 24.7, 43.0),
    ('Methanol', 19.7, 15.6),
    ('Natural gas', 53.6, 0.0364, 'top'),
    ('Natural gas (250 bar)', 53.6, 9),
    ('Polyester', 26.0, 35.6, 'bottom'),
    ('Polyethylene', 46.3, 42.6),
    ('Polystyrene', 41.4, 43.5, 'top'),
    ('Silicon', 32.6, 75.9),
    ('Sodium', 13.3, 12.8, 'left'),  # (burned to wet NaOH)
    ('Sugar\nmetabolism\n', 17, 26.2, 'top'),
    ('Zinc', 5.3, 38.0),
    ('Zinc–air battery', 1.59, 6.02),

    # Highest energy density available from commercial 18650 cells as of February 2026
    # Sources: Far East Battery 18650-4000
    # * Specific energy: 300 Wh/kg, listed in the first party datasheet: https://en.febbattery.com/Uploads/keditor/file/20231123/20231123131924_57703.pdf
    # * Energy density: 842 Wh/L, calculated from a third party test: https://news.qq.com/rain/a/20231025A05JQ400
    #     * Calculation: 14.26/(((1.82/2)^2*3.14159*6.51)/1000) = 841.989 Wh/L
    ('Lithium-ion battery', 1.080, 3.031),
)

# arguments for label positions
pos_args = {
    'top': {'ha': 'center', 'xytext': (0, 1)},
    'bottom': {'ha': 'center', 'xytext': (0, -1)},
    'left': {'ha': 'right', 'xytext': (-0.5, 0)},
    'right': {'ha': 'left', 'xytext': (0.5, 0)}
}

plt.figure(figsize=(12, 7.5))

plt.xlabel('MJ/kg')
plt.xlim(0, 160)

plt.ylabel('MJ/L')
plt.ylim(0, 90)

plt.grid(c='lightgray')
plt.gca().set_axisbelow(True)

for name, x, y, *pos in data:
    plt.scatter(x=[x], y=[y], c='k')
    pos = 'right' if pos == [] else pos[0]
    plt.annotate(name, (x, y),
                 textcoords='offset fontsize', va='center', **pos_args[pos])

plt.tight_layout()
plt.savefig('energy_density.svg', transparent=True)