diff options
Diffstat (limited to 'gnuradio-examples/python/volk_benchmark/volk_plot.py')
| -rwxr-xr-x | gnuradio-examples/python/volk_benchmark/volk_plot.py | 169 |
1 files changed, 0 insertions, 169 deletions
diff --git a/gnuradio-examples/python/volk_benchmark/volk_plot.py b/gnuradio-examples/python/volk_benchmark/volk_plot.py deleted file mode 100755 index 823dfbf64..000000000 --- a/gnuradio-examples/python/volk_benchmark/volk_plot.py +++ /dev/null @@ -1,169 +0,0 @@ -#!/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]') - 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 - - # Get list of tables to compare - conn = create_connection(args.database) - tables = list_tables(conn) - M = len(tables) - - # 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 - - 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)) - i = 0 - for t in (table_data): - 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']) - elif(args.plot == 'mean'): - ydata.append(table_data[t][name]['avg']) - - 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: - # 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_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() |