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Commit dbd7b504 authored by Karsten Loesing's avatar Karsten Loesing
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Split visualizations by public and onion service. 

Fixes #34216.
parent fb96513a
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onionperf/visualization.py
+ 55
− 42
View file @ dbd7b504
......@@ -12,6 +12,7 @@ import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import datetime
import numpy as np
class Visualization(object, metaclass=ABCMeta):
......@@ -54,6 +55,7 @@ class TGenVisualization(Visualization):
for transfer_id, transfer_data in tgen_transfers.items():
transfer = {"transfer_id": transfer_id, "label": label,
"filesize_bytes": transfer_data["filesize_bytes"]}
transfer["server"] = "onion" if ".onion:" in transfer_data["endpoint_remote"] else "public"
if "elapsed_seconds" in transfer_data:
s = transfer_data["elapsed_seconds"]
if "first_byte" in s:
......@@ -68,64 +70,75 @@ class TGenVisualization(Visualization):
self.data = pd.DataFrame.from_records(transfers, index="transfer_id")
def __plot_firstbyte_ecdf(self):
for server in self.data["server"].unique():
self.__draw_ecdf(x="time_to_first_byte", hue="label", hue_name="Data set",
data=self.data, title="Time to download first byte",
data=self.data[self.data["server"] == server],
title="Time to download first byte from {0} service".format(server),
xlabel="Download time (s)", ylabel="Cumulative Fraction")
def __plot_firstbyte_time(self):
for bytes in self.data["filesize_bytes"].unique():
for bytes in np.sort(self.data["filesize_bytes"].unique()):
for server in self.data["server"].unique():
self.__draw_timeplot(x="start", y="time_to_first_byte", hue="label", hue_name="Data set",
data=self.data[self.data["filesize_bytes"]==bytes],
title="Time to download first of {0} bytes over time".format(bytes),
data=self.data[(self.data["server"] == server) & (self.data["filesize_bytes"] == bytes)],
title="Time to download first of {0} bytes from {1} service over time".format(bytes, server),
xlabel="Download start time", ylabel="Download time (s)")
def __plot_lastbyte_ecdf(self):
for bytes in self.data["filesize_bytes"].unique():
for bytes in np.sort(self.data["filesize_bytes"].unique()):
for server in self.data["server"].unique():
self.__draw_ecdf(x="time_to_last_byte", hue="label", hue_name="Data set",
data=self.data[self.data["filesize_bytes"]==bytes],
title="Time to download last of {0} bytes".format(bytes),
data=self.data[(self.data["server"] == server) & (self.data["filesize_bytes"] == bytes)],
title="Time to download last of {0} bytes from {1} service".format(bytes, server),
xlabel="Download time (s)", ylabel="Cumulative Fraction")
def __plot_lastbyte_box(self):
for bytes in self.data["filesize_bytes"].unique():
for bytes in np.sort(self.data["filesize_bytes"].unique()):
for server in self.data["server"].unique():
self.__draw_boxplot(x="label", y="time_to_last_byte",
data=self.data[self.data["filesize_bytes"]==bytes],
title="Time to download last of {0} bytes".format(bytes),
data=self.data[(self.data["server"] == server) & (self.data["filesize_bytes"] == bytes)],
title="Time to download last of {0} bytes from {1} service".format(bytes, server),
xlabel="Data set", ylabel="Download time (s)")
def __plot_lastbyte_bar(self):
for bytes in self.data["filesize_bytes"].unique():
for bytes in np.sort(self.data["filesize_bytes"].unique()):
for server in self.data["server"].unique():
self.__draw_barplot(x="label", y="time_to_last_byte",
data=self.data[self.data["filesize_bytes"]==bytes],
title="Mean time to download last of {0} bytes".format(bytes),
data=self.data[(self.data["server"] == server) & (self.data["filesize_bytes"] == bytes)],
title="Mean time to download last of {0} bytes from {1} service".format(bytes, server),
xlabel="Data set", ylabel="Downloads time (s)")
def __plot_lastbyte_time(self):
for bytes in self.data["filesize_bytes"].unique():
for bytes in np.sort(self.data["filesize_bytes"].unique()):
for server in self.data["server"].unique():
self.__draw_timeplot(x="start", y="time_to_last_byte", hue="label", hue_name="Data set",
data=self.data[self.data["filesize_bytes"] == bytes],
title="Time to download last of {0} bytes over time".format(bytes),
data=self.data[(self.data["server"] == server) & (self.data["filesize_bytes"] == bytes)],
title="Time to download last of {0} bytes from {1} service over time".format(bytes, server),
xlabel="Download start time", ylabel="Download time (s)")
def __plot_downloads_count(self):
for bytes in self.data["filesize_bytes"].unique():
for bytes in np.sort(self.data["filesize_bytes"].unique()):
for server in self.data["server"].unique():
self.__draw_countplot(x="label",
data=self.data[self.data["filesize_bytes"] == bytes],
data=self.data[(self.data["server"] == server) & (self.data["filesize_bytes"] == bytes)],
xlabel="Data set", ylabel="Downloads completed (#)",
title="Number of downloads of {0} bytes completed".format(bytes))
title="Number of downloads of {0} bytes completed from {1} service".format(bytes, server))
def __plot_errors_count(self):
if "error_code" in self.data.columns:
self.__draw_countplot(x="error_code", hue="label", hue_name="Data set", data=self.data,
for server in self.data["server"].unique():
if "error_code" in self.data.columns and self.data[self.data["server"] == server]["error_code"].count() > 0:
self.__draw_countplot(x="error_code", hue="label", hue_name="Data set",
data=self.data[self.data["server"] == server],
xlabel="Error code", ylabel="Downloads failed (#)",
title="Number of downloads failed")
title="Number of downloads failed from {0} service".format(server))
def __plot_errors_time(self):
if "error_code" in self.data.columns:
for server in self.data["server"].unique():
if "error_code" in self.data.columns and self.data[self.data["server"] == server]["error_code"].count() > 0:
self.__draw_stripplot(x="start", y="error_code", hue="label", hue_name="Data set",
data = self.data,
data=self.data[self.data["server"] == server],
xlabel="Download start time", ylabel="Error code",
title="Downloads failed over time")
title="Downloads failed over time from {0} service".format(server))
def __draw_ecdf(self, x, hue, hue_name, data, title, xlabel, ylabel):
data = data.dropna(subset=[x])
......
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