import matplotlib.pyplot as plt

import numpy as np

# Simulated data

time = np.arange(0, 10, 0.5)

hydrogen_rate = np.random.normal(loc=2.0, scale=0.2, size=len(time))

energy_consumption = np.random.normal(loc=50, scale=5, size=len(time))

voltage = np.random.normal(loc=1.8, scale=0.05, size=len(time))

efficiency = 100 / energy_consumption # Simplified efficiency metric

# Create subplots

fig, axs = plt.subplots(2, 2, figsize=(12, 8))

fig.suptitle('Hydrogen Production Data Overview')

# Chart 1: Hydrogen Production Rate Over Time

axs[0, 0].plot(time, hydrogen_rate, marker='o', color='green')

axs[0, 0].set_title('Hydrogen Production Rate Over Time')

axs[0, 0].set_xlabel('Time (hours)')

axs[0, 0].set_ylabel('H₂ Rate (Nm³/h)')

# Chart 2: Energy Consumption per kg of H₂

axs[0, 1].plot(time, energy_consumption, marker='s', color='blue')

axs[0, 1].set_title('Energy Consumption per kg H₂')

axs[0, 1].set_xlabel('Time (hours)')

axs[0, 1].set_ylabel('Energy (kWh/kg)')

# Chart 3: Voltage vs Time

axs[1, 0].plot(time, voltage, marker='x', color='red')

axs[1, 0].set_title('Cell Voltage Over Time')

axs[1, 0].set_xlabel('Time (hours)')

axs[1, 0].set_ylabel('Voltage (V)')

# Chart 4: Efficiency Over Time

axs[1, 1].plot(time, efficiency, marker='^', color='purple')

axs[1, 1].set_title('Efficiency Over Time')

axs[1, 1].set_xlabel('Time (hours)')

axs[1, 1].set_ylabel('Efficiency (kg H₂/kWh)')

plt.tight_layout(rect=[0, 0.03, 1, 0.95])

plt.show()