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#!/usr/bin/env python
import sys, math
import argparse
from volk_test_funcs import *
try:
import matplotlib
import matplotlib.pyplot as plt
except ImportError:
sys.stderr.write("Could not import Matplotlib (http://matplotlib.sourceforge.net/)\n")
sys.exit(1)
def main():
desc='Plot Volk performance results from a SQLite database. ' + \
'Run one of the volk tests first (e.g, volk_math.py)'
parser = argparse.ArgumentParser(description=desc)
parser.add_argument('-D', '--database', type=str,
default='volk_results.db',
help='Database file to read data from [default: %(default)s]')
parser.add_argument('-E', '--errorbars',
action='store_true', default=False,
help='Show error bars (1 standard dev.)')
parser.add_argument('-P', '--plot', type=str,
choices=['mean', 'min', 'max'],
default='mean',
help='Set the type of plot to produce [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['ytick.labelsize'] = 16
matplotlib.rcParams['xtick.labelsize'] = 16
matplotlib.rcParams['legend.fontsize'] = 18
# Get list of tables to compare
conn = create_connection(args.database)
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']
# Set up figure for plotting
f0 = plt.figure(0, facecolor='w', figsize=(14,10))
s0 = f0.add_subplot(1,1,1)
# Create a register of names that exist in all tables
tmp_regs = []
for table in tables:
# Get results from the next table
res = get_results(conn, table[0])
tmp_regs.append(list())
for r in res:
try:
tmp_regs[-1].index(r['kernel'])
except ValueError:
tmp_regs[-1].append(r['kernel'])
# Get only those names that are common in all tables
name_reg = tmp_regs[0]
for t in tmp_regs[1:]:
name_reg = list(set(name_reg) & set(t))
name_reg.sort()
# Pull the data out for each table into a dictionary
# we can ref the table by it's name and the data associated
# with a given kernel in name_reg by it's name.
# This ensures there is no sorting issue with the data in the
# dictionary, so the kernels are plotted against each other.
table_data = dict()
for i,table in enumerate(tables):
# Get results from the next table
res = get_results(conn, table[0])
data = dict()
for r in res:
data[r['kernel']] = r
table_data[table[0]] = data
# 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]
ydata = []
stds = []
for name in name_reg:
stds.append(math.sqrt(table_data[t][name]['var']))
if(args.plot == 'max'):
ydata.append(table_data[t][name]['max'])
elif(args.plot == 'min'):
ydata.append(table_data[t][name]['min'])
if(args.plot == 'mean'):
ydata.append(table_data[t][name]['avg'])
if(args.errorbars is False):
stds = None
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})
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():
label.set_rotation(45)
label.set_fontsize(16)
plt.show()
if __name__ == "__main__":
main()
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