Changes in benchmark/plot.py [8fca132:c0458be3]

File:

• benchmark/plot.py (modified) (10 diffs)

benchmark/plot.py

@@ -18 +18 @@
 import statistics
 import sys
-import time
-
-import matplotlib
+
 import matplotlib.pyplot as plt
-from matplotlib.ticker import EngFormatter, ScalarFormatter
-
-def fmtDur( duration ):
-        if duration :
-                hours, rem = divmod(duration, 3600)
-                minutes, rem = divmod(rem, 60)
-                seconds, millis = divmod(rem, 1)
-                return "%2d:%02d.%03d" % (minutes, seconds, millis * 1000)
-        return " n/a"
+from matplotlib.ticker import EngFormatter
 
 class Field:
@@ -42 +32 @@
 field_names = {
         "ns per ops"            : Field('ns'    , 0, False),
-        "Number of processors"  : Field(''      , 1, "exact"),
+        "Number of processors"  : Field(''      , 1, False),
         "Ops per procs"         : Field('Ops'   , 0, False),
         "Ops per threads"       : Field('Ops'   , 0, False),
-        "ns per ops/procs"      : Field(''      , 0, False, _name = "ns $\\times$ (Processor $/$ Total Ops)" ),
+        "ns per ops/procs"      : Field(''      , 0, False, _name = "Latency (ns $/$ (Processor $\\times$ Operation))" ),
         "Number of threads"     : Field(''      , 1, False),
         "Total Operations(ops)" : Field('Ops'   , 0, False),
@@ -55 +45 @@
         "Target QPS"            : Field(''      , 0, False),
         "Actual QPS"            : Field(''      , 0, False),
-        "Average Read Latency"  : Field('s'     , 0, False, _factor = 0.000001),
+        "Average Read Latency"  : Field('s'     , 0, True, _factor = 0.000001),
         "Median Read Latency"   : Field('s'     , 0, True, _factor = 0.000001),
         "Tail Read Latency"     : Field('s'     , 0, True, _factor = 0.000001),
@@ -61 +51 @@
         "Median Update Latency" : Field('s'     , 0, True, _factor = 0.000001),
         "Tail Update Latency"   : Field('s'     , 0, True, _factor = 0.000001),
-        "Update Ratio"          : Field('%'   , 0, False),
+        "Update Ratio"          : Field('\%'    , 0, False),
         "Request Rate"          : Field('req/s' , 0, False),
         "Data Rate"             : Field('b/s'   , 0, False, _factor = 1000 * 1000, _name = "Response Throughput"),
-        "Errors"                : Field('%'   , 0, False),
 }
 
 def plot(in_data, x, y, options, prefix):
         fig, ax = plt.subplots()
-        colors  = itertools.cycle(['#006cb4','#0aa000','#ff6600','#8510a1','#0095e3','#fd8f00','#e30002','#8f00d6','#4b009a','#ffff00','#69df00','#fb0300','#b13f00'])
-        markers = itertools.cycle(['x', '+', '1', '2', '3', '4'])
-        series  = {} # scatter data for each individual data point
-        groups  = {} # data points for x value
+        colors = itertools.cycle(['#006cb4','#0aa000','#ff6600','#8510a1','#0095e3','#fd8f00','#e30002','#8f00d6','#4b009a','#ffff00','#69df00','#fb0300','#b13f00'])
+        series = {} # scatter data for each individual data point
+        groups = {} # data points for x value
 
         print("Preparing Data")
@@ -78 +66 @@
         for entry in in_data:
                 name = entry[0]
-                if options.filter and not name.startswith(options.filter):
-                        continue
-
                 if not name in series:
                         series[name] = {'x':[], 'y':[]}
@@ -117 +102 @@
         for name, data in sorted(series.items()):
                 _col = next(colors)
-                _mrk = next(markers)
-                plt.scatter(data['x'], data['y'], color=_col, label=name[len(prefix):], marker=_mrk)
-                plt.plot(lines[name]['x'], lines[name]['min'], ':', color=_col)
+                plt.scatter(data['x'], data['y'], color=_col, label=name[len(prefix):], marker='x')
+                plt.plot(lines[name]['x'], lines[name]['min'], '--', color=_col)
                 plt.plot(lines[name]['x'], lines[name]['max'], '--', color=_col)
                 plt.plot(lines[name]['x'], lines[name]['med'], '-', color=_col)
@@ -139 +123 @@
         elif field_names[x].log:
                 ax.set_xscale('log')
-                if field_names[x].log == "exact":
-                        xvals = set()
-                        for s in series.values():
-                                xvals |= set(s['x'])
-                        ax.set_xticks(sorted(xvals))
-                        ax.get_xaxis().set_major_formatter(ScalarFormatter())
-                        plt.xticks(rotation = 45)
         else:
                 plt.xlim(field_names[x].min, mx + 0.25)
@@ -161 +138 @@
 
         print("Results Ready")
-        start = time.time()
         if options.out:
                 plt.savefig(options.out, bbox_inches='tight')
         else:
                 plt.show()
-        end = time.time()
-        print("Took {}".format(fmtDur(end - start)))
 
 
@@ -181 +155 @@
         parser.add_argument('--logy', action='store_true', help="if set, makes the y-axis logscale")
         parser.add_argument('--MaxY', nargs='?', type=int, help="maximum value of the y-axis")
-        parser.add_argument('--filter', nargs='?', type=str, default="", help="if not empty, only print series that start with specified filter")
 
         options =  parser.parse_args()
-
-        # if not options.out:
-        #       matplotlib.use('SVG')
 
         # ================================================================================
@@ -208 +178 @@
                         fields.add(label)
 
-        # filter out the series if needed
-        if options.filter:
-                series = set(filter(lambda elem: elem.startswith(options.filter), series))
-
-        # find the common prefix on series for removal (only if no filter)
+        # find the common prefix on series for removal
         prefix = os.path.commonprefix(list(series))