l3-ENSL/dendrobates-t-azureus
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Remove tikzplotlib dependancy

Browse Source 
Remove gmpy2 dependancy
Fix numpy conversion warnings
This commit is contained in:
augustin64 2024-06-04 17:00:33 +02:00
parent 8edd90b6a3
commit 4817065712
1 changed files with 10 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
cache_utils/analyse_csv.py
View File

@ -6,7 +6,7 @@
import pandas as pd import pandas as pd
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import seaborn as sns import seaborn as sns
import tikzplotlib #import tikzplotlib
from sys import exit from sys import exit
import wquantiles as wq import wquantiles as wq
import numpy as np import numpy as np
@ -16,7 +16,10 @@ from functools import partial
import sys import sys
# For cyber cobay sanity check : # For cyber cobay sanity check :
from gmpy2 import popcount # from gmpy2 import popcount
def popcount(x):
return x.bit_count()
functions_i9_9900 = [ functions_i9_9900 = [
0b1111111111010101110101010001000000, 0b1111111111010101110101010001000000,
0b0110111110111010110001001000000000, 0b0110111110111010110001001000000000,
@ -35,7 +38,8 @@ def convert64(x):
return np.int64(int(x, base=16)) return np.int64(int(x, base=16))
def convert8(x): def convert8(x):
return np.int8(int(x, base=16)) return np.array(int(x, base=16)).astype(np.int64)
# return np.int8(int(x, base=16))
df = pd.read_csv(sys.argv[1] + "-results_lite.csv.bz2", df = pd.read_csv(sys.argv[1] + "-results_lite.csv.bz2",
dtype={ dtype={
@ -141,7 +145,7 @@ def custom_hist(x, *y, **kwargs):
custom_hist(df["time"], df["clflush_miss_n"], df["clflush_remote_hit"]) custom_hist(df["time"], df["clflush_miss_n"], df["clflush_remote_hit"])
tikzplotlib.save("fig-hist-all.tex")#, axis_width=r'0.175\textwidth', axis_height=r'0.25\textwidth') #tikzplotlib.save("fig-hist-all.tex")#, axis_width=r'0.175\textwidth', axis_height=r'0.25\textwidth')
plt.show() plt.show()
attacker = 2 attacker = 2
@ -151,7 +155,7 @@ slice = 14
df_ax_vx_sx = df[(df["hash"] == slice) & (df["main_core"] == attacker) & (df["helper_core"] == victim)] df_ax_vx_sx = df[(df["hash"] == slice) & (df["main_core"] == attacker) & (df["helper_core"] == victim)]
custom_hist(df_ax_vx_sx["time"], df_ax_vx_sx["clflush_miss_n"], df_ax_vx_sx["clflush_remote_hit"]) custom_hist(df_ax_vx_sx["time"], df_ax_vx_sx["clflush_miss_n"], df_ax_vx_sx["clflush_remote_hit"])
tikzplotlib.save("fig-hist-good-A{}V{}S{}.tex".format(attacker,victim,slice))#, axis_width=r'0.175\textwidth', axis_height=r'0.25\textwidth') #tikzplotlib.save("fig-hist-good-A{}V{}S{}.tex".format(attacker,victim,slice))#, axis_width=r'0.175\textwidth', axis_height=r'0.25\textwidth')
plt.show() plt.show()
attacker = 9 attacker = 9
@ -161,7 +165,7 @@ slice = 8
df_ax_vx_sx = df[(df["hash"] == slice) & (df["main_core"] == attacker) & (df["helper_core"] == victim)] df_ax_vx_sx = df[(df["hash"] == slice) & (df["main_core"] == attacker) & (df["helper_core"] == victim)]
custom_hist(df_ax_vx_sx["time"], df_ax_vx_sx["clflush_miss_n"], df_ax_vx_sx["clflush_remote_hit"]) custom_hist(df_ax_vx_sx["time"], df_ax_vx_sx["clflush_miss_n"], df_ax_vx_sx["clflush_remote_hit"])
tikzplotlib.save("fig-hist-bad-A{}V{}S{}.tex".format(attacker,victim,slice))#, axis_width=r'0.175\textwidth', axis_height=r'0.25\textwidth') #tikzplotlib.save("fig-hist-bad-A{}V{}S{}.tex".format(attacker,victim,slice))#, axis_width=r'0.175\textwidth', axis_height=r'0.25\textwidth')
plt.show() plt.show()