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#!/usr/bin/env python3
import csv
import glob
import math
from collections import defaultdict
from pathlib import Path
LABELS = ["VANILLA", "FALCO", "TETRA", "TRACE"]
def label_from_path(path: str, prefix: str) -> str:
stem = Path(path).stem
if stem.startswith(prefix):
stem = stem[len(prefix):]
return stem.upper()
def format_size(n: int) -> str:
gib = 1024 ** 3
mib = 1024 ** 2
kib = 1024
if n >= gib:
v = n / gib
if abs(v - round(v)) < 0.03:
return f"{int(round(v))}G"
return f"{v:.1f}G"
if n >= mib:
v = n / mib
if abs(v - round(v)) < 0.03:
return f"{int(round(v))}M"
return f"{round(n / 1_000_000)}M"
if n >= kib:
return f"{round(n / 1000)}K"
return f"{n}B"
def mean(xs):
return sum(xs) / len(xs)
def stddev(xs):
m = mean(xs)
return math.sqrt(sum((x - m) ** 2 for x in xs) / len(xs))
def prepare_times():
groups = defaultdict(list)
for path in sorted(glob.glob("times_*.csv")):
label = label_from_path(path, "times_")
if label not in LABELS:
print(f"Skipping unknown latency label: {path}")
continue
with open(path, newline="") as f:
r = csv.DictReader(f)
if r.fieldnames != ["bytes", "time_usec"]:
raise ValueError(f"{path}: expected bytes,time_usec, got {r.fieldnames}")
for row in r:
nbytes = int(row["bytes"])
time_usec = float(row["time_usec"])
groups[(label, nbytes)].append(time_usec)
sizes = sorted({nbytes for (_, nbytes) in groups.keys()})
fieldnames = ["bytes"]
for label in LABELS:
fieldnames += [f"{label}_time_usec", f"{label}_cdf"]
with open("times_all.CSV", "w", newline="") as f:
w = csv.DictWriter(f, fieldnames=fieldnames)
w.writeheader()
for nbytes in sizes:
per_label = {}
max_n = 0
for label in LABELS:
values = sorted(groups.get((label, nbytes), []))
n = len(values)
max_n = max(max_n, n)
per_label[label] = [
(v, (i + 1) / n) for i, v in enumerate(values)
] if n else []
for i in range(max_n):
row = {"bytes": nbytes}
for label in LABELS:
if i < len(per_label[label]):
t, cdf = per_label[label][i]
row[f"{label}_time_usec"] = f"{t / 1000.0:.6f}"
row[f"{label}_cdf"] = f"{cdf:.9f}"
else:
row[f"{label}_time_usec"] = ""
row[f"{label}_cdf"] = ""
w.writerow(row)
print("Wrote times_all.CSV")
def prepare_bw():
groups = defaultdict(list)
for path in sorted(glob.glob("bw_*.csv")):
label = label_from_path(path, "bw_")
if label not in LABELS:
print(f"Skipping unknown bandwidth label: {path}")
continue
with open(path, newline="") as f:
r = csv.DictReader(f)
if r.fieldnames != ["bytes", "bw_KiBps"]:
raise ValueError(f"{path}: expected bytes,bw_KiBps, got {r.fieldnames}")
for row in r:
nbytes = int(row["bytes"])
bw_mibps = float(row["bw_KiBps"]) / 1024.0
groups[(label, nbytes)].append(bw_mibps)
sizes = sorted({nbytes for (_, nbytes) in groups.keys()})
fieldnames = ["bytes", "size"]
for label in LABELS:
fieldnames += [label, f"{label}_err"]
with open("bw_all.CSV", "w", newline="") as f:
w = csv.DictWriter(f, fieldnames=fieldnames)
w.writeheader()
for nbytes in sizes:
row = {
"bytes": nbytes,
"size": format_size(nbytes),
}
for label in LABELS:
values = groups.get((label, nbytes), [])
if values:
row[label] = f"{mean(values):.6f}"
row[f"{label}_err"] = f"{stddev(values):.6f}"
else:
row[label] = ""
row[f"{label}_err"] = ""
w.writerow(row)
print("Wrote bw_all.CSV")
def main():
prepare_times()
prepare_bw()
if __name__ == "__main__":
main()
|
