+++ /dev/null
-import matplotlib.pyplot as plt
-import numpy as np
-import pandas as pd
-from ggplot import *
-
-open=pd.read_csv("execution_openssl_rpi3.txt",sep='\t',header=None)
-one=pd.read_csv("execution_oneround_rpi3.txt",sep='\t',header=None)
-
-
-open=open.drop(open.columns[[4,5]], axis=1)
-one=one.drop(one.columns[[0,4,5]], axis=1)
-
-open.columns = ["Buffer","OpenSSL enc CBC","OpenSSL dec CBC", "OpenSSL (en|de)c CTR"]
-
-one.columns=["OneRound enc DECB", "OneRound dec DECB", "OneRound (en|de)c CTR"]
-
-print(one)
-print(open)
-
-res=pd.concat([open,one],axis=1)
-#print(res)
-
-res2 = pd.melt(res, id_vars=['Buffer'])
-
-print(res2)
-
-
-print(ggplot(res2,aes("Buffer","value")) + \
- geom_line(aes(colour="variable")) + \
-# geom_line(color='coral') + \
- scale_x_continuous("Buffer size",trans="log10") + \
- scale_y_continuous("Bytes per second",trans="log10",breaks=[1e7,2e8,1e7]))
-# theme(axis_text=element_text(size=20, color='green'), x_axis_text=element_text(angle=45)) +\
-
-
-# annotation_logticks())
- #scale_x_date(breaks=date_breaks('36 months'), labels='%Y') + \
-# scale_y_continuous(labels='millions'))
-
-
- #theme(legend.position="top")
- # geom_line(aes(colour="Legend"))) +\