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finish all analysis

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seung6lee
2026-04-20 00:36:28 +09:00
parent 009bf59ff0
commit 31219c4618
26 changed files with 1130 additions and 483 deletions
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codes/experiments/real_data/analysis/graph_distribution.py
+63 -29
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@@ -2,7 +2,8 @@ import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import random
import scipy.stats as stats
from scipy.stats import shapiro
def read_dimacs(file):
@@ -14,24 +15,38 @@ def read_dimacs(file):
continue
elif line.startswith("p"):
_, _, n, e = line.split()
nodes = int(n)
edges = int(e)
data = [0] * edges
elif line.startswith("a"):
_, u, v, w = line.split()
data[idx] = int(w)
idx += 1
return data
return ((nodes, edges), data)
def visualize_weights(file):
data = read_dimacs(file)
sample = np.array(data)
(nodes, edges), data = read_dimacs(file)
data = np.array(data)
log_data = np.log(data)
skew = stats.skew(data)
skew_log = stats.skew(log_data)
kurt = stats.kurtosis(data) # excess kurtosis (정규=0)
kurt_log = stats.kurtosis(log_data)
print(f'\n--- Skewness / Kurtosis ---')
print(f'Skewness (original): {skew:.4f} (정규 기준: 0)')
print(f'Skewness (log): {skew_log:.4f} (정규 기준: 0)')
print(f'Kurtosis (original): {kurt:.4f} (정규 기준: 0, excess)')
print(f'Kurtosis (log): {kurt_log:.4f} (정규 기준: 0, excess)')
return
save_folder = f"{res_folder}/{file}"
os.makedirs(save_folder, exist_ok=True)
plt.figure(figsize=(8, 5))
plt.hist(sample, bins=100)
plt.hist(data, bins=100)
plt.title("Edge Weight Distribution (Original Scale)")
plt.xlabel("Weight")
plt.ylabel("Frequency")
@@ -39,10 +54,16 @@ def visualize_weights(file):
plt.savefig(f"{save_folder}/hist_original.png")
plt.close()
log_sample = np.log(sample[sample > 0])
plt.figure(figsize=(8, 5))
stats.probplot(data, dist="norm", plot=plt)
plt.title("Q-Q Plot (Original Scale)")
plt.xlabel("Theoretical Quantiles (Normal)")
plt.ylabel("Sample Quantiles (Weight)")
plt.savefig(f"{save_folder}/Q-Q_original.png")
plt.close()
plt.figure(figsize=(8, 5))
plt.hist(log_sample, bins=100)
plt.hist(log_data, bins=100)
plt.title("Log(Weight) Distribution")
plt.xlabel("log(Weight)")
plt.ylabel("Frequency")
@@ -51,37 +72,50 @@ def visualize_weights(file):
plt.close()
plt.figure(figsize=(8, 5))
plt.hist(log_sample, bins=100, density=True)
plt.title("Log(Weight) Density")
plt.xlabel("log(Weight)")
plt.ylabel("Density")
plt.tight_layout()
plt.savefig(f"{save_folder}/hist_log_density.png")
stats.probplot(log_data, dist="norm", plot=plt)
plt.title("Q-Q Plot (Log Weight)")
plt.xlabel("Theoretical Quantiles (Normal)")
plt.ylabel("Sample Quantiles (Weight)")
plt.savefig(f"{save_folder}/Q-Q_log.png")
plt.close()
# plt.figure(figsize=(8, 5))
# plt.hist(log_data, bins=100, density=True)
# plt.title("Log(Weight) Density")
# plt.xlabel("log(Weight)")
# plt.ylabel("Density")
# plt.tight_layout()
# plt.savefig(f"{save_folder}/hist_log_density.png")
# plt.close()
print(f"finish {file}")
return {
"file": file,
"edges": len(sample),
"mean": np.mean(sample),
"std": np.std(sample),
"min": np.min(sample),
"max": np.max(sample)
"nodes": nodes,
"edges": edges,
"density": edges / (nodes * (nodes - 1)),
"mean": np.mean(data),
"std": np.std(data),
"min": np.min(data),
"max": np.max(data),
"skew": stats.skew(data),
"skew_log": stats.skew(log_data),
}
folder = "experiments/real_data/data/dimacs_data"
files = [
"USA-road-d.BAY.gr",
"USA-road-d.CAL.gr",
"USA-road-d.COL.gr",
"USA-road-d.CTR.gr",
"USA-road-d.E.gr",
"USA-road-d.FLA.gr",
"USA-road-d.LKS.gr",
"USA-road-d.NE.gr",
"USA-road-d.NW.gr",
"USA-road-d.NY.gr",
# "USA-road-d.BAY.gr",
# "USA-road-d.CAL.gr",
# "USA-road-d.COL.gr",
# "USA-road-d.CTR.gr",
# "USA-road-d.E.gr",
# "USA-road-d.FLA.gr",
# "USA-road-d.LKS.gr",
# "USA-road-d.NE.gr",
# "USA-road-d.NW.gr",
# "USA-road-d.NY.gr",
"USA-road-d.USA.gr",
"USA-road-d.W.gr"
# "USA-road-d.W.gr"
]
res_folder = "results/real_data/derived/dimacs_graph_distribution"