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Commit f9e0c8d2 authored by Ashwin Rao's avatar Ashwin Rao
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For avoiding type3 fonts

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parse_results/parse_rtcm3_logs.ipynb
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%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
# Parse the RTCM3 Logs # Parse the RTCM3 Logs
import seaborn as sns import seaborn as sns
import pandas import pandas
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy
# to avoid type 3 fonts.
plt.rc('pdf',fonttype = 42)
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
# Read the files and pre process them for plotting. # Read the files and pre process them for plotting.
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
# Read the file # Read the file
timestamps = pandas.read_csv("./timestamps.csv") timestamps = pandas.read_csv("./timestamps.csv")
# Compute the latency in ms # Compute the latency in ms
timestamps["Latency"] = (timestamps["ts_client"]-timestamps["ts_relay"])*1000 timestamps["Latency"] = (timestamps["ts_client"]-timestamps["ts_relay"])*1000
# Inter-arrival time between messages. The diff is in microsec # Remember the diff is still in seconds.
timestamps['relay_iat'] = timestamps['ts_relay'].diff() timestamps['relay_iat'] = timestamps['ts_relay'].diff()
timestamps['relay_iat'] = timestamps['relay_iat'].apply(lambda x : x if x > 0 else numpy.nan) # Dirty hack for jumps between experiments.
timestamps['relay_iat'] = timestamps['relay_iat'].apply(lambda x : x if x < 100 else numpy.nan) # Dirty hack for jumps between experiments.
timestamps['client_iat'] = timestamps['ts_client'].diff() timestamps['client_iat'] = timestamps['ts_client'].diff()
timestamps['iat_diff'] = (timestamps['relay_iat']-timestamps['client_iat'])*1000 timestamps['client_iat'] = timestamps['client_iat'].apply(lambda x : x if x > 0 else numpy.nan) # Dirty hack for jumps between experiments.
print(timestamps) timestamps['client_iat'] = timestamps['client_iat'].apply(lambda x : x if x < 100 else numpy.nan) # Dirty hack for jumps between experiments.
# Inter-arrival time between messages. The diff is in millisec.
timestamps['iat_diff'] = abs(timestamps['relay_iat']-timestamps['client_iat'])*1000
print(timestamps["iat_diff"])
ping = pandas.read_csv("./ping.csv") ping = pandas.read_csv("./ping.csv")
print(ping) #print(ping)
ping['Latency'] = ping['rtt']/2.0 ping['Latency'] = ping['rtt']/2.0
print(timestamps[timestamps["Latency"] == max(timestamps["Latency"])])
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
fig, ax = plt.subplots(figsize=(10,5)) fig, ax = plt.subplots(figsize=(17.5,5))
sns.set_context("poster"), sns.set_context("poster")
sns.set_style("white") sns.set_style("white")
sns.color_palette("husl", 8)
sns.boxplot(data=timestamps, x="Location", y="Latency",hue="Technology", whis=[5,95], showfliers=False) #plot_data = timestamps[timestamps["Technology"].isin(["Ethernet", "Wi-Fi(PE)", "Wi-Fi(PE)", "5G(BE)", "5G(BD)"]) ]
plot_data = timestamps
#handles, labels = ax.get_legend_handles_labels() sns.boxplot(data=plot_data, x="Location", y="Latency",hue="Technology", whis=[5,95], showfliers=False)
#ax.set_xticklabels(labels=['Ethernet', 'Wi-Fi', '5G'])
ax.set_ylim(0,50) handles, labels = ax.get_legend_handles_labels()
ax.set_xlabel("Location") ax.set_yticklabels(labels=['0.1', '1', '10', '100'])
ax.set_ylabel("Latency (ms)") ax.set_ylim(0.1,300)
ax.set_xlabel("Location", weight="bold")
ax.set_ylabel("Latency (ms)", weight="bold")
handles, labels = ax.get_legend_handles_labels()
ax.legend(ncol=5, title="Technology", bbox_to_anchor=(-0.02, 1.35), loc="upper left")
ax.set_yscale("log")
ax.grid(True, which='major', axis='y') ax.grid(True, which='major', axis='y')
ax.grid(True, which='minor', axis='y')
plt.savefig("timestamps.pdf", dpi=1200, bbox_inches='tight') plt.savefig("timestamps.pdf", dpi=1200, bbox_inches='tight')
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
# Plot the one way latency between the client and the relay # Plot the one way latency between the client and the relay
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
fig, ax = plt.subplots(figsize=(17.5,5))
sns.set_context("poster"),
sns.set_style("white")
sns.set_palette("colorblind")
sns.boxplot(data=ping, x="Location", y="Latency",hue="Technology", whis=[5,95], showfliers=False)
ax.set_ylim(0.1,300)
ax.set_xlabel("Location", weight="bold")
ax.set_ylabel("Latency (ms)", weight="bold")
ax.legend(ncol=5, title="Technology", bbox_to_anchor=(-0.02, 1.35), loc="upper left")
ax.set_yscale("log")
ax.grid(True, which='major', axis='y')
ax.grid(True, which='minor', axis='y')
plt.savefig("ping.pdf", dpi=1200, bbox_inches='tight')
``` ```
%% Cell type:markdown id: tags:
# Plot the difference in the inter-arrival time of the messages.
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
fig, ax = plt.subplots(figsize=(10,5)) fig, ax = plt.subplots(figsize=(17.5,5))
sns.set_context("poster"), sns.set_context("poster"),
sns.set_style("white") sns.set_style("white")
sns.boxplot(data=ping, x="Location", y="Latency",hue="Technology", whis=[5,95], showfliers=False) sns.set_palette("colorblind")
ax.set_xlabel("Location")
ax.set_ylabel("Latency (ms)")
ax.set_ylim(0,50) sns.boxplot(data=timestamps, x="Location", y="iat_diff",hue="Technology", whis=[5,95], showfliers=False)
ax.set_ylim(0.01,300)
ax.set_xlabel("Location", weight="bold")
ax.set_ylabel("Inter-arrival Time \n Difference (ms)", weight="bold")
#ax.set_yscale("log")
ax.legend(ncol=5, title="Technology", bbox_to_anchor=(-0.02, 1.35), loc="upper left")
ax.set_yscale("log")
ax.grid(True, which='major', axis='y') ax.grid(True, which='major', axis='y')
plt.savefig("ping.pdf", dpi=1200, bbox_inches='tight') ax.grid(True, which='minor', axis='y')
plt.savefig("iat.pdf", dpi=1200, bbox_inches='tight')
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
# Plot the difference in the inter-arrival time of the messages. # Plot the CDF of the IAT
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
fig, ax = plt.subplots(figsize=(10,5)) fig, ax = plt.subplots(figsize=(15,5))
sns.set_context("poster"), sns.set_context("poster"),
sns.set_style("white") sns.set_style("white")
sns.set_palette("colorblind")
sns.boxplot(data=timestamps, x="Location", y="iat_diff",hue="Technology", whis=[5,95], showfliers=False)
ax.set_xlabel("Location") def ecdf(x):
ax.set_ylabel("Inter-arrival Time \n Difference (μs)") xs = numpy.sort(x)
ys = numpy.arange(1, len(xs)+1)/float(len(xs))
return xs, ys
plot_data = timestamps[timestamps["relay_iat"].notnull()]
#plot_data = plot_data[plot_data["relay_iat"]>0]
x = plot_data["relay_iat"]*1000 # Convert to ms.
xs, ys = ecdf(x)
plt.plot(xs,ys)
ax.set_xscale("log")
ax.grid(True, which='major')
ax.grid(True, which='minor')
ax.set_ylabel("ECDF", weight="bold")
ax.set_xlabel("Inter Arrival Time (ms)", weight="bold")
plt.savefig("ecdfiat.pdf", dpi=1200, bbox_inches='tight')
```
%% Cell type:code id: tags:
``` python
for font in plt.rcParams['font.sans-serif']:
print(font)
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
``` ```
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