import plotly.graph_objects as go
from plotly.subplots import make_subplots
import hashlib

def get_color(name):
    hash_object = hashlib.md5(name.encode())
    color_index = int(hash_object.hexdigest(), 16) % 360
    return f'hsl({color_index}, 100%, 50%)'

def plot_results(results, filename):
    fig = make_subplots(rows=3, cols=1)

    for i, (coro_name, x_values) in enumerate(results.items(), start=1):
        x_list = []
        y_latency_list = []
        y_throughput_list = []
        y_max_latency_list = []

        for speedup, experiments in x_values.items():
            for experiment in experiments:

                completed_callbacks = experiment["latency"]
                virtual_run_time = experiment["virtual_run_time"][0]

                x_list.append(speedup * 100)

                num_callbacks = len(completed_callbacks)

                # handle average latency graph
                if num_callbacks > 0:

                    total_wait = sum([cb[1] for cb in completed_callbacks])
                    max_wait = max([cb[1] for cb in completed_callbacks])
                    latency = total_wait / num_callbacks

                    y_max_latency_list.append(max_wait)
                    y_latency_list.append(latency)
                else:
                    y_latency_list.append(0)

                # handle throughput graph
                throughput = num_callbacks / virtual_run_time
                y_throughput_list.append(throughput)

        fig.add_trace(go.Scatter(
            x=x_list,
            y=y_latency_list,
            mode='markers',
            name=coro_name,
            marker=dict(color=get_color(coro_name)),
            showlegend=True,
        ), row=1, col=1)

        fig.add_trace(go.Scatter(
            x=x_list,
            y=y_throughput_list,
            mode='markers',
            name=coro_name,
            marker=dict(color=get_color(coro_name)),
            showlegend=False,
        ), row=2, col=1)

        fig.add_trace(go.Scatter(
            x=x_list,
            y=y_max_latency_list,
            mode='markers',
            name=coro_name,
            marker=dict(color=get_color(coro_name)),
            showlegend=False,
        ), row=3, col=1)

    fig.update_xaxes(title_text="Speedup (% optimized away)", row=3, col=1)
    fig.update_yaxes(title_text="Average Handle Latency (seconds)", row=1, col=1)
    fig.update_yaxes(title_text="Throughput (callbacks per second)", row=2, col=1)
    fig.update_yaxes(title_text="Maximum Handle Latency (seconds)", row=3, col=1)

    fig.write_html(filename)