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Plot M vs N

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This commit is contained in:
Piotr Mikołajczyk
2024-10-15 15:21:52 +02:00
parent f592c45a6f
commit bb00087151
1 changed files with 43 additions and 0 deletions
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analysis.py
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@@ -1,4 +1,8 @@
import json import json
import re
import matplotlib.pyplot as plt
import numpy as np
# Function to convert time units to seconds # Function to convert time units to seconds
@@ -18,6 +22,7 @@ def report(operation, time):
scenarios = {} scenarios = {}
free_logs = [] free_logs = []
hypernova = [[None] * 7 for _ in range(7)]
def process_logline(log): def process_logline(log):
@@ -36,6 +41,10 @@ def process_logline(log):
folding_scheme = span.get("folding_scheme") folding_scheme = span.get("folding_scheme")
if folding_scheme is not None: if folding_scheme is not None:
free_logs.append(report(f"{folding_scheme} total time", time_seconds)) free_logs.append(report(f"{folding_scheme} total time", time_seconds))
hypernova_params = re.fullmatch(r"HyperNova<(\d),(\d)>", folding_scheme)
if hypernova_params:
hypernova[int(hypernova_params.groups()[0])][int(hypernova_params.groups()[1])] = time_seconds
else: else:
free_logs.append(report(span["name"], time_seconds)) free_logs.append(report(span["name"], time_seconds))
return return
@@ -90,5 +99,39 @@ def print_results():
print(report(" Max", max(proving_steps))) print(report(" Max", max(proving_steps)))
def draw_hn_plot():
data_np = np.array(hypernova, dtype=np.float64)
data_np = np.where(np.isnan(data_np), 0, data_np) # Replace None with 0 for better visualization
cmap = plt.cm.viridis
cmap.set_under('white') # Set background color for None
fig, ax = plt.subplots()
cax = ax.matshow(data_np, cmap=cmap, vmin=0.01)
fig.colorbar(cax)
for i in range(len(hypernova)):
for j in range(len(hypernova[i])):
if hypernova[i][j] is not None:
ax.text(j, i, f'{hypernova[i][j]:.2f}', va='center', ha='center', color='black')
# Set axis labels and title
ax.set_xlabel('ν (number of incoming CCCS instances)')
ax.set_ylabel('μ (number of running LCCCS instances)')
ax.set_xticks(np.arange(len(hypernova[0])))
ax.set_yticks(np.arange(len(hypernova)))
ax.set_xticklabels([f'{i}' for i in range(len(hypernova[0]))])
ax.set_yticklabels([f'{i}' for i in range(len(hypernova))])
plt.title("HyperNova multifold times")
# Show the plot
plt.show()
process_logs('out.log') process_logs('out.log')
print_results() print_results()
draw_hn_plot()