libCacheSim/scripts/traceAnalysis/reuse.py at develop · cacheMon/libCacheSim · GitHub

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"""
plot reuse time distribution

usage:
1. run traceAnalyzer: `./traceAnalyzer /path/trace trace_format --common`,
this will generate some output, including reuse distribution result, trace.reuse
2. plot reuse distribution using this script:
`python3 reuse.py trace.reuse`

"""

importos
importsys
importre
importnumpyasnp
importmatplotlib.pyplotasplt
fromtypingimportList, Dict, Tuple
importlogging

sys.path.append(os.path.dirname(os.path.abspath(__file__)))
fromutils.trace_utilsimportextract_dataname
fromutils.plot_utilsimportFIG_DIR, FIG_TYPE
fromutils.data_utilsimportconv_to_cdf

logger=logging.getLogger("reuse")


def_load_reuse_data(datapath: str) ->Tuple[dict, dict]:
"""load reuse distribution plot data from C++ computation

 Args:
 datapath (str): the path of reuse data file

 Returns:
 Tuple[dict, dict]: reuse_rtime_count, reuse_vtime_count

 """

ifile=open(datapath)
data_line=ifile.readline()
desc_line=ifile.readline()
m=re.match(r"# reuse real time: freq \(time granularity (?P<tg>\d+)\)", desc_line)
assertmisnotNone, (
"the input file might not be reuse data file, desc line "
+desc_line
+" data "
+datapath
 )

rtime_granularity=int(m.group("tg"))
log_base=1.5

reuse_rtime_count, reuse_vtime_count= {}, {}

forlineinifile:
ifline[0] =="#"and"virtual time"inline:
m=re.match(
r"# reuse virtual time: freq \(log base (?P<lb>\d+\.?\d*)\)", line
 )
assertmisnotNone, (
"the input file might not be reuse data file, desc line "
+line
+" data "
+datapath
 )
log_base=float(m.group("lb"))
break
eliflen(line.strip()) ==0:
continue
else:
reuse_time, count= [int(i) foriinline.split(":")]
ifreuse_time<-1:
print("find negative reuse time "+line)
reuse_rtime_count[reuse_time*rtime_granularity] =count

forlineinifile:
iflen(line.strip()) ==0:
continue
else:
reuse_time, count= [int(i) foriinline.split(":")]
ifreuse_time<-1:
print("find negative reuse time "+line)
reuse_vtime_count[log_base**reuse_time] =count

ifile.close()

returnreuse_rtime_count, reuse_vtime_count


defplot_reuse(datapath: str, figname_prefix: str="") ->None:
"""
 plot reuse time distribution

 Args:
 datapath (str): the path of reuse data file
 figname_prefix (str, optional): the prefix of figname. Defaults to "".

 Returns:
 None: None

 """

iflen(figname_prefix) ==0:
figname_prefix=extract_dataname(datapath)

reuse_rtime_count, reuse_vtime_count=_load_reuse_data(datapath)

x, y=conv_to_cdf(None, data_dict=reuse_rtime_count)
ifx[0] <0:
x=x[1:]
y= [y[i] -y[0] foriinrange(1, len(y))]
plt.plot([i/3600foriinx], y)
plt.grid(linestyle="--")
plt.ylim(0, 1)
plt.xlabel("Time (Hour)")
plt.ylabel("Fraction of requests (CDF)")
plt.savefig(
"{}/{}_reuse_rt.{}".format(FIG_DIR, figname_prefix, FIG_TYPE),
bbox_inches="tight",
 )
plt.xscale("log")
plt.xticks(
np.array([60, 300, 3600, 86400, 86400*2, 86400*4]) /3600,
 ["1 min", "5 min", "1 hour", "1 day", "", "4 day"],
rotation=28,
 )
plt.savefig(
"{}/{}_reuse_rt_log.{}".format(FIG_DIR, figname_prefix, FIG_TYPE),
bbox_inches="tight",
 )
plt.clf()

x, y=conv_to_cdf(None, data_dict=reuse_vtime_count)
ifx[0] <0:
x=x[1:]
y= [y[i] -y[0] foriinrange(1, len(y))]
plt.plot([iforiinx], y)
plt.grid(linestyle="--")
plt.xlabel("Virtual time (# requests)")
plt.ylabel("Fraction of requests (CDF)")
plt.savefig(
"{}/{}_reuse_vt.{}".format(FIG_DIR, figname_prefix, FIG_TYPE),
bbox_inches="tight",
 )
plt.xscale("log")
plt.savefig(
"{}/{}_reuse_vt_log.{}".format(FIG_DIR, figname_prefix, FIG_TYPE),
bbox_inches="tight",
 )
plt.clf()
logger.info(
"reuse time plot saved to {}/{}_reuse_rt.{} and {}/{}_reuse_vt.{}".format(
FIG_DIR, figname_prefix, FIG_TYPE, FIG_DIR, figname_prefix, FIG_TYPE
 )
 )


if__name__=="__main__":
importargparse

ap=argparse.ArgumentParser()
ap.add_argument("datapath", type=str, help="data path")
ap.add_argument(
"--figname-prefix", type=str, default="", help="the prefix of figname"
 )
p=ap.parse_args()

plot_reuse(p.datapath, p.figname_prefix)