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"""
plot size heatmap
usage:
1. run traceAnalyzer: `./traceAnalyzer /path/trace trace_format --common`,
this will generate some output, including size distribution result, trace.size
2. plot size heatmap using this script:
`python3 size_heatmap.py trace.sizeWindow_w300`
"""
importos, sys
importre
importnumpyasnp
importmatplotlib.pyplotasplt
importcopy
importnumpy.maasma
frommatplotlib.tickerimportFuncFormatter
fromtypingimportList, Dict, Tuple
importlogging
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
fromutils.trace_utilsimportextract_dataname
fromutils.plot_utilsimportFIG_DIR, FIG_TYPE
logger=logging.getLogger("size_heatmap")
def_load_size_heatmap_data(datapath) ->Tuple[np.ndarray, int, float, int]:
"""load size heatmap plot data from C++ computation
Args:
datapath (str): the path of size heatmap data file
Returns:
Tuple[np.ndarray, int, float, int]: plot_data, time_window, log_base, size_base
"""
ifile=open(datapath)
data_line=ifile.readline()
desc_line=ifile.readline()
m=re.search(
r"# (object_size): \w\w\w_cnt \(time window (?P<tw>\d+), log_base (?P<logb>\d+\.?\d*), size_base (?P<sizeb>\d+)\)",
desc_line,
)
assertmisnotNone, (
"the input file might not be size heatmap data file, desc line "
+desc_line
+" data "
+datapath
)
time_window=int(m.group("tw"))
log_base=float(m.group("logb"))
size_base=int(m.group("sizeb"))
size_distribution_over_time= []
forlineinifile:
# if "obj_cnt" in line:
# curr_data = size_distribution_by_obj_over_time
# elif len(line.strip()) == 0:
# continue
# else:
count_list=line.strip("\n,").split(",")
size_distribution_over_time.append(count_list)
ifile.close()
dim=max([len(l) forlinsize_distribution_over_time])
plot_data=np.zeros((len(size_distribution_over_time), dim))
foridx, linenumerate(size_distribution_over_time):
l=np.array(l, dtype=np.float64)
l=l/np.sum(l)
plot_data[idx][: len(l)] =l
returnplot_data.T, time_window, log_base, size_base
defplot_size_heatmap(datapath: str, figname_prefix: str=""):
"""
plot size heatmap
Args:
datapath (str): the path of size heatmap data file
figname_prefix (str, optional): the prefix of figname. Defaults to "".
"""
iflen(figname_prefix) ==0:
figname_prefix=extract_dataname(datapath)
plot_data, time_window, log_base, size_base=_load_size_heatmap_data(
datapath+"_req"
)
# plot heatmap
cmap=copy.copy(plt.cm.jet)
# cmap = copy.copy(plt.cm.viridis)
cmap.set_bad(color="white", alpha=1.0)
img=plt.imshow(plot_data, origin="lower", cmap=cmap, aspect="auto")
cb=plt.colorbar(img)
plt.gca().xaxis.set_major_formatter(
FuncFormatter(lambdax, pos: "{:.0f}".format(x*time_window/3600))
)
plt.gca().yaxis.set_major_formatter(
FuncFormatter(lambdax, pos: "{:.0f}".format(log_base**x*size_base))
)
plt.xlabel("Time (hour)")
plt.ylabel("Request size (Byte)")
plt.savefig(
"{}/{}_size_heatmap_req.{}".format(FIG_DIR, figname_prefix, FIG_TYPE),
bbox_inches="tight",
)
plt.clf()
plot_data, time_window, log_base, size_base=_load_size_heatmap_data(
datapath+"_obj"
)
img=plt.imshow(plot_data, origin="lower", cmap=cmap, aspect="auto")
cb=plt.colorbar(img)
plt.gca().xaxis.set_major_formatter(
FuncFormatter(lambdax, pos: "{:.0f}".format(x*time_window/3600))
)
plt.gca().yaxis.set_major_formatter(
FuncFormatter(lambdax, pos: "{:.0f}".format(log_base**x*size_base))
)
plt.xlabel("Time (hour)")
plt.ylabel("Object size (Byte)")
plt.savefig(
"{}/{}_size_heatmap_obj.{}".format(FIG_DIR, figname_prefix, FIG_TYPE),
bbox_inches="tight",
)
plt.clf()
logger.info(
"plot saved to {}/{}_size_heatmap_req.{} and {}/{}_size_heatmap_obj.{}".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()
ifp.datapath.endswith("_req") orp.datapath.endswith("_obj"):
p.datapath=p.datapath[:-4]
plot_size_heatmap(p.datapath, p.figname_prefix)