Script to visualize gas consumption traces

plot_gas_consumption.py

import sys
import json
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages

def plot_gas_consumption(trace, color_map):
    gas_readings = trace['readings']
    descriptions = [reading['description'] for reading in gas_readings]
    gas_values = [reading['amount'] for reading in gas_readings]
    cumulative_gas = [sum(gas_values[:i+1]) for i in range(len(gas_values))]

    plt.figure(figsize=(18, 6))  # Set the figure size to accommodate both charts
    plt.subplot(1, 2, 1)  # First subplot for the line chart
    for description in color_map:
        mask = [desc == description for desc in descriptions]
        plt.plot([cumulative_gas[j] for j in range(len(mask)) if mask[j]],
                 [gas_values[j] for j in range(len(mask)) if mask[j]],
                 marker='o', linestyle='', label=description, color=color_map[description])

    title = "Gas Consumption Trace:" + trace["msg_names"][0]
    plt.xlabel("Cumulative Gas Consumption")
    plt.ylabel('Gas Amount')
    plt.title(title)
    plt.grid(True)
    # Move the legend outside the chart
    plt.legend(loc='upper left', bbox_to_anchor=(1.05, 1))

    # Adjust the layout to prevent overlapping of elements
    plt.tight_layout()

    # Calculate the percentage of gas used by each description for the pie chart
    gas_total = sum(gas_values)
    gas_totals = {}
    for val in gas_readings:
        description = val['description']
        try:
            gas_totals[description] += val['amount']
        except KeyError:
            gas_totals[description] = val['amount']

    plt.subplot(1, 2, 2)  # Second subplot for the pie chart
    values = [gas_totals[desc] for desc in gas_totals]
    keys = [desc for desc in gas_totals]
    plt.pie(values, labels=keys, colors=[color_map[desc] for desc in gas_totals],
            autopct='%1.1f%%', startangle=90)
    plt.title('Gas Usage by Description')

if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage: python script.py <json_file_path>")
        sys.exit(1)

    json_file = sys.argv[1]

    with open(json_file, 'r') as file:
        json_data = json.load(file)

    # Create a color mapping dictionary
    unique_descriptions = list(set(reading['description'] for trace in json_data for reading in trace['readings']))
    num_unique_descriptions = len(unique_descriptions)
    color_map = {description: plt.get_cmap('tab20')(i / num_unique_descriptions) for i, description in enumerate(unique_descriptions)}

    # Create a PDF file to save the plots
    with PdfPages('gas_consumption_plots.pdf') as pdf:
        for trace in json_data:
            if trace['readings']:
                plot_gas_consumption(trace, color_map)
                pdf.savefig()  # Save the current plot to the PDF file

    print("Plots have been saved to 'gas_consumption_plots.pdf'.")

I will not be maintaining this lol

it is purely a quick and dirty chatgpt barfed script to plot a gas consumption script per https://github.com/celestiaorg/celestia-app/blob/2a4ef9c9f3c276dfc514466bce9be24434d53189/specs/src/specs/resource_pricing.md