Fix plot scripts and doc for traceAnalyzer (#68)

* Fix scripts for traceAnalyzer

* Update doc of traceAnalyzer

Author: haochengxia

doc/quickstart_traceAnalyzer.md

@@ -79,7 +79,7 @@ After generating plot data, we can plot access pattern, request rate, size, reus
 python3 scripts/traceAnalysis/access_pattern.py ${dataname}.accessRtime
 
 # plot the access pattern using logical/virtual (request count) time 
-python3 scripts/traceAnalysis/access_pattern.py ${dataname}.accessRtime
+python3 scripts/traceAnalysis/access_pattern.py ${dataname}.accessVtime
 ```
 
 Some example plots are shown below:
@@ -243,7 +243,7 @@ There are two versions of the plots, one is line plot, and the other is a heatma
 ```bash
 # this requires a long trace (e.g., 7 day) to generate a meaningful plot
 # and most block workloads do not have enough requests to plot meaningful popularity decay
-python3 scripts/traceAnalysis/popularity_decay.py ${dataname}.popularityDecay_w300
+python3 scripts/traceAnalysis/popularity_decay.py ${dataname}.popularityDecay_w300_obj
 ```
 
 <!-- Some example plots are shown below:

scripts/traceAnalysis/access_pattern.py

@@ -105,7 +105,7 @@ def plot_access_pattern(
     is_real_time = "Rtime" in datapath
     if is_real_time:
         xlabel = "Time (hour)"
-        figname = "fig/{}_access_rt.{}".format(figname_prefix, FIG_TYPE)
+        figname = "{}/{}_access_rt.{}".format(FIG_DIR, figname_prefix, FIG_TYPE)
         for idx, ts_list in enumerate(access_time_list):
             # access_rtime_list stores N objects, each object has one access pattern list
             plt.scatter(
@@ -117,7 +117,7 @@ def plot_access_pattern(
             "Vtime" in datapath
         ), "the input file might not be accessPattern data file"
         xlabel = "Time (# million requests)"
-        figname = "fig/{}_access_vt.{}".format(figname_prefix, FIG_TYPE)
+        figname = "{}/{}_access_vt.{}".format(FIG_DIR, figname_prefix, FIG_TYPE)
         for idx, ts_list in enumerate(access_time_list):
             # access_rtime_list stores N objects, each object has one access pattern list
             plt.scatter(

scripts/traceAnalysis/experimental/scanSize.py

@@ -57,7 +57,7 @@ def plot_scan_size(datapath, figname_prefix=""):
 
     plt.xlabel("Scan size")
     plt.ylabel("Count")
-    plt.savefig("{}_scan_size.png".format(figname_prefix), bbox_inches="tight")
+    plt.savefig("{}/{}_scan_size.{}".format(FIG_DIR, figname_prefix, FIG_TYPE), bbox_inches="tight")
     plt.clf()
 
     x, y = conv_to_cdf(scan_size_cnt)
@@ -74,7 +74,7 @@ def plot_scan_size(datapath, figname_prefix=""):
     plt.grid(linestyle="--")
     plt.xlabel("Scan size")
     plt.ylabel("CDF")
-    plt.savefig("{}_scan_size_cdf.png".format(figname_prefix), bbox_inches="tight")
+    plt.savefig("{}/{}_scan_size_cdf.{}".format(FIG_DIR, figname_prefix, FIG_TYPE), bbox_inches="tight")
     plt.clf()
 
 

scripts/traceAnalysis/run.sh

@@ -2,7 +2,8 @@
 
 dataname=$1
 
-python3 access_pattern.py ${dataname}.access
+python3 access_pattern.py ${dataname}.accessRtime
+python3 access_pattern.py ${dataname}.accessVtime
 python3 req_rate.py ${dataname}.reqRate_w300
 python3 size.py ${dataname}.size
 python3 reuse.py ${dataname}.reuse
@@ -11,5 +12,5 @@ python3 popularity.py ${dataname}.popularity
 python3 size_heatmap.py ${dataname}.sizeWindow_w300
 # python3 futureReuse.py ${dataname}.access
 
-python3 popularity_decay.py ${dataname}.popularityDecay_w300
+python3 popularity_decay.py ${dataname}.popularityDecay_w300_obj
 python3 reuse_heatmap.py ${dataname}.reuseWindow_w300