import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

data = pd.read_csv("sensors_log.csv")

data['timestamp'] = pd.to_datetime(data['timestamp'])

data.set_index('timestamp', inplace=True)

plt.style.use('dark_background')

columns_to_plot = {
    'CPU (°C)': 1,
    'Vcore (V)': 0.01,
    'VSOC (V)': 0.01,
    'VDDP (mV)': 5,
    'DRAM (V)': 0.01,
}

for column, threshold in columns_to_plot.items():
    plt.figure(figsize=(12, 6))
    plt.plot(data.index, data[column], label=column, color='cyan', linewidth=2)

    last_labeled_value = None
    for x, y in zip(data.index, data[column]):
        if last_labeled_value is None or abs(y - last_labeled_value) > threshold:
            plt.text(x, y, f"{y:.2f}", fontsize=9, ha='center', va='bottom', color='white')
            last_labeled_value = y

    plt.xlabel("Timestamp", fontsize=12, color='white')
    plt.ylabel("Value", fontsize=12, color='white')
    plt.title(f"{column} Over Time", fontsize=14, color='white')
    plt.legend(loc='upper left')
    plt.grid(visible=True, color='gray', linestyle='--', alpha=0.7)
    plt.tight_layout()

    plt.savefig(f"{column}_graph_no_points_dark.png", dpi=300)
    plt.show()