From e36d6f1f766e702d147ca494e21131cc66f157dd Mon Sep 17 00:00:00 2001
From: Tom Rondeau <trondeau@vt.edu>
Date: Mon, 13 Feb 2012 16:10:14 -0500
Subject: volk: can specify a table to calculate the percent improvement
against instead of just the raw numbers.
---
.../python/volk_benchmark/volk_plot.py | 80 ++++++++++++++++------
1 file changed, 60 insertions(+), 20 deletions(-)
(limited to 'gnuradio-examples/python')
diff --git a/gnuradio-examples/python/volk_benchmark/volk_plot.py b/gnuradio-examples/python/volk_benchmark/volk_plot.py
index 562d4f2f75..823dfbf641 100755
--- a/gnuradio-examples/python/volk_benchmark/volk_plot.py
+++ b/gnuradio-examples/python/volk_benchmark/volk_plot.py
@@ -25,11 +25,15 @@ def main():
choices=['mean', 'min', 'max'],
default='mean',
help='Set the type of plot to produce [default: %(default)s]')
+ parser.add_argument('-%', '--percent', type=str,
+ default=None, metavar="table",
+ help='Show percent difference to the given type [default: %(default)s]')
args = parser.parse_args()
# Set up global plotting properties
matplotlib.rcParams['figure.subplot.bottom'] = 0.2
matplotlib.rcParams['figure.subplot.top'] = 0.95
+ matplotlib.rcParams['figure.subplot.right'] = 0.98
matplotlib.rcParams['ytick.labelsize'] = 16
matplotlib.rcParams['xtick.labelsize'] = 16
matplotlib.rcParams['legend.fontsize'] = 18
@@ -39,9 +43,6 @@ def main():
tables = list_tables(conn)
M = len(tables)
- # width of bars depends on number of comparisons
- wdth = 0.80/M
-
# Colors to distinguish each table in the bar graph
# More than 5 tables will wrap around to the start.
colors = ['b', 'r', 'g', 'm', 'k']
@@ -85,12 +86,23 @@ def main():
table_data[table[0]] = data
+ if args.percent is not None:
+ for i,t in enumerate(table_data):
+ if args.percent == t:
+ norm_data = []
+ for name in name_reg:
+ if(args.plot == 'max'):
+ norm_data.append(table_data[t][name]['max'])
+ elif(args.plot == 'min'):
+ norm_data.append(table_data[t][name]['min'])
+ elif(args.plot == 'mean'):
+ norm_data.append(table_data[t][name]['avg'])
+
+
# Plot the results
x0 = xrange(len(name_reg))
- for i,t in enumerate(table_data):
- # makes x values for this data set placement
- x1 = [x + i*wdth for x in x0]
-
+ i = 0
+ for t in (table_data):
ydata = []
stds = []
for name in name_reg:
@@ -99,24 +111,52 @@ def main():
ydata.append(table_data[t][name]['max'])
elif(args.plot == 'min'):
ydata.append(table_data[t][name]['min'])
- if(args.plot == 'mean'):
+ elif(args.plot == 'mean'):
ydata.append(table_data[t][name]['avg'])
- if(args.errorbars is False):
- s0.bar(x1, ydata, width=wdth,
- color=colors[i%M], label=t,
- edgecolor='k', linewidth=2)
+ if args.percent is not None:
+ ydata = [-100*(y-n)/y for y,n in zip(ydata,norm_data)]
+ if(args.percent != t):
+ # makes x values for this data set placement
+ # width of bars depends on number of comparisons
+ wdth = 0.80/(M-1)
+ x1 = [x + i*wdth for x in x0]
+ i += 1
+
+ s0.bar(x1, ydata, width=wdth,
+ color=colors[(i-1)%M], label=t,
+ edgecolor='k', linewidth=2)
+
else:
- s0.bar(x1, ydata, width=wdth,
- yerr=stds,
- color=colors[i%M], label=t,
- edgecolor='k', linewidth=2,
- error_kw={"ecolor": 'k', "capsize":5,
- "linewidth":2})
+ # makes x values for this data set placement
+ # width of bars depends on number of comparisons
+ wdth = 0.80/M
+ x1 = [x + i*wdth for x in x0]
+ i += 1
+
+ if(args.errorbars is False):
+ s0.bar(x1, ydata, width=wdth,
+ color=colors[(i-1)%M], label=t,
+ edgecolor='k', linewidth=2)
+ else:
+ s0.bar(x1, ydata, width=wdth,
+ yerr=stds,
+ color=colors[i%M], label=t,
+ edgecolor='k', linewidth=2,
+ error_kw={"ecolor": 'k', "capsize":5,
+ "linewidth":2})
+
+ nitems = res[0]['nitems']
+ if args.percent is None:
+ s0.set_ylabel("Processing time (sec) [{0:G} items]".format(nitems),
+ fontsize=22, fontweight='bold',
+ horizontalalignment='center')
+ else:
+ s0.set_ylabel("% Improvement over {0} [{1:G} items]".format(
+ args.percent, nitems),
+ fontsize=22, fontweight='bold')
s0.legend()
- s0.set_ylabel("Processing time (sec) [{0:G} items]".format(res[0]['nitems']),
- fontsize=22, fontweight='bold')
s0.set_xticks(x0)
s0.set_xticklabels(name_reg)
for label in s0.xaxis.get_ticklabels():
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