mirror of
https://github.com/arnaucube/sonobe-playground.git
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138 lines
4.1 KiB
Python
138 lines
4.1 KiB
Python
import json
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import re
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import matplotlib.pyplot as plt
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import numpy as np
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# Function to convert time units to seconds
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def convert_to_seconds(time_str):
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if time_str.endswith('µs'):
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return float(time_str[:-2]) * 1e-6
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elif time_str.endswith('ms'):
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return float(time_str[:-2]) * 1e-3
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elif time_str.endswith('s'):
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return float(time_str[:-1])
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return 0
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def report(operation, time):
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return f"{operation}: {time:.6f} seconds"
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scenarios = {}
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free_logs = []
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hypernova = [[None] * 7 for _ in range(7)]
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def process_logline(log):
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fields = log.get("fields", {})
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span = log.get("span", {})
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scenario_name = None
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time_seconds = convert_to_seconds(fields["time.busy"])
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# A folding scheme scenario is one of our ancestors
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for s in log.get("spans", []):
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if s.get("name") == "scenario":
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scenario_name = s.get("folding_scheme")
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# Top level span
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if not scenario_name:
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folding_scheme = span.get("folding_scheme")
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if folding_scheme is not None:
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free_logs.append(report(f"{folding_scheme} total time", time_seconds))
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hypernova_params = re.fullmatch(r"HyperNova<(\d),(\d)>", folding_scheme)
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if hypernova_params:
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hypernova[int(hypernova_params.groups()[0])][int(hypernova_params.groups()[1])] = time_seconds
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else:
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free_logs.append(report(span["name"], time_seconds))
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return
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# Within a folding scheme scenario
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if scenario_name not in scenarios:
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scenarios[scenario_name] = {
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"Prepare folding": 0,
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"Transform input": 0,
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"Folding verification": 0,
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"Proving": [],
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"Input prep": [],
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}
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span_name = span.get("name")
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if span_name == "Proving":
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scenarios[scenario_name]["Proving"].append(time_seconds)
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elif span_name == "Input prep":
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scenarios[scenario_name]["Input prep"].append(time_seconds)
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else:
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scenarios[scenario_name][span_name] = time_seconds
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def process_logs(file_path):
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with open(file_path, 'r') as f:
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for line in f:
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process_logline(json.loads(line))
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def print_results():
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for log in free_logs:
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print(log)
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print()
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for scenario_name, data in scenarios.items():
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print("-" * 80)
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print(f"Scenario: {scenario_name}")
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print(report(" Prepare folding", data["Prepare folding"]))
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print(report(" Transform input", data["Transform input"]))
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print(report(" Folding verification", data["Folding verification"]))
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print(f" Folding Steps:")
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input_trans = data["Input prep"]
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print(" Input preparation")
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print(report(" Avg", sum(input_trans) / len(input_trans)))
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print(report(" Min", min(input_trans)))
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print(report(" Max", max(input_trans)))
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proving_steps = data["Proving"]
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print(" Proving")
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print(report(" Avg", sum(proving_steps) / len(proving_steps)))
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print(report(" Min", min(proving_steps)))
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print(report(" Max", max(proving_steps)))
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def draw_hn_plot():
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data_np = np.array(hypernova, dtype=np.float64)
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data_np = np.where(np.isnan(data_np), 0, data_np) # Replace None with 0 for better visualization
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cmap = plt.cm.viridis
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cmap.set_under('white') # Set background color for None
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fig, ax = plt.subplots()
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cax = ax.matshow(data_np, cmap=cmap, vmin=0.01)
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fig.colorbar(cax)
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for i in range(len(hypernova)):
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for j in range(len(hypernova[i])):
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if hypernova[i][j] is not None:
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ax.text(j, i, f'{hypernova[i][j]:.2f}', va='center', ha='center', color='black')
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# Set axis labels and title
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ax.set_xlabel('ν (number of incoming CCCS instances)')
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ax.set_ylabel('μ (number of running LCCCS instances)')
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ax.set_xticks(np.arange(len(hypernova[0])))
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ax.set_yticks(np.arange(len(hypernova)))
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ax.set_xticklabels([f'{i}' for i in range(len(hypernova[0]))])
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ax.set_yticklabels([f'{i}' for i in range(len(hypernova))])
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plt.title("HyperNova multifold times")
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# Show the plot
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plt.show()
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process_logs('out.log')
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print_results()
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draw_hn_plot()
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