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Add plots for rep-20

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Tobias Eidelpes 2021-05-17 12:19:42 +02:00
parent d0105475ea
commit b32c5e60f6
3 changed files with 20 additions and 2 deletions
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ex3/figures/FFT_packets_uIPs.png Normal file
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ex3/figures/tcp_packets_uIPs_timeseries.png Normal file
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ex3/rep-20.py
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@ -4,6 +4,9 @@ import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import math as m import math as m
dataset = pd.read_csv('csv/team13_protocol.csv').fillna(0) dataset = pd.read_csv('csv/team13_protocol.csv').fillna(0)
dataset['timestamp'] = pd.to_datetime(dataset['timestamp'], unit='s')
dataset = dataset.set_index('timestamp')
print(dataset)
p6_pkts = dataset['6 · # Packets'].tolist() p6_pkts = dataset['6 · # Packets'].tolist()
#return number of elements in p6_pkts list #return number of elements in p6_pkts list
n = len(p6_pkts) n = len(p6_pkts)
@ -18,6 +21,9 @@ k = range(0,n-1) #creates an array from 0 to n-1
x = k[1:m.floor(n/2)] x = k[1:m.floor(n/2)]
#set amp. values in the y-axis and specify the limit #set amp. values in the y-axis and specify the limit
y = pkt_amp[1:m.floor(n/2)] y = pkt_amp[1:m.floor(n/2)]
plt.figure(figsize=(20,10))
plt.tight_layout(h_pad=0.5)
plt.subplot(2, 1, 1)
plt.stem(x, y) plt.stem(x, y)
#find max index and value #find max index and value
max_k = np.flip(np.argsort(pkt_amp[1:m.floor(n/2)]))[0] max_k = np.flip(np.argsort(pkt_amp[1:m.floor(n/2)]))[0]
@ -45,7 +51,8 @@ k = range(0,n_2-1) #creates an array from 0 to n-1
#set k values in the x-axis and specify the limit #set k values in the x-axis and specify the limit
x = k[1:m.floor(n_2/2)] x = k[1:m.floor(n_2/2)]
#set amp. values in the y-axis and specify the limit #set amp. values in the y-axis and specify the limit
y = pkt_amp[1:m.floor(n/2)] y = uIPs_amp[1:m.floor(n/2)]
plt.subplot(2, 1, 2)
plt.stem(x, y) plt.stem(x, y)
#find max index and value #find max index and value
max_k = np.flip(np.argsort(uIPs_amp[1:m.floor(n_2/2)]))[0] max_k = np.flip(np.argsort(uIPs_amp[1:m.floor(n_2/2)]))[0]
@ -54,8 +61,19 @@ plt.xlim(1, m.floor(n_2/2))
plt.xlabel('k') #sets x-axis label plt.xlabel('k') #sets x-axis label
#set y-axis label #set y-axis label
plt.ylabel('Amplitude [millions of unique source IPs]') plt.ylabel('Amplitude [millions of unique source IPs]')
plt.title('Amp. Spectrum for unique source IPs') #displays title plt.title('Amp. Spectrum for #unique source IPs') #displays title
plt.show()
print('TCP #uIPs/hour - FFT max value: ', round(max_amp / 1000000, 2)) print('TCP #uIPs/hour - FFT max value: ', round(max_amp / 1000000, 2))
print('TCP #uIPs/hour - k of FFT max value: ', np.where(uIPs_amp == max_amp)) print('TCP #uIPs/hour - k of FFT max value: ', np.where(uIPs_amp == max_amp))
print('TCP #uIPs/hour - period of k corresponding to FFT max value: ', n_2 / 31) print('TCP #uIPs/hour - period of k corresponding to FFT max value: ', n_2 / 31)
# Plot TCP #pkts/hour and TCP #uIPs/hour timeseries
plt.figure(figsize=(20,10))
plt.tight_layout(h_pad=2)
plt.subplot(2, 1, 1)
dataset['6 · # Packets'].plot(xlabel='', ylabel='Number of TCP Packets', title='Number of TCP Packets over Time')
plt.subplot(2, 1, 2)
dataset['6 · # Unique Source IPs'].plot(xlabel='Time', ylabel='Number of Unique TCP Source IPs', title='Number of Unique TCP Source IPs over Time')
plt.show()