small_gicp/scripts/plot_odometry_native.py

66 lines
2.1 KiB
Python

#!/usr/bin/python3
import os
import re
import numpy
from collections import namedtuple
from matplotlib import pyplot
Result = namedtuple('Result', ['reg_mean', 'reg_std', 'tp_mean', 'tp_std'])
def parse_result(filename):
reg_mean = None
reg_std = None
throughput_mean = None
throughput_std = None
with open(filename, 'r') as f:
for line in f.readlines():
found = re.findall(r'([^=]+)\s*\+\-\s*(\S+)', line)
if not found or len(found) != 2:
found = re.findall(r'total_throughput=(\S+)', line)
if found:
throughput_mean = float(found[0])
continue
reg_mean = float(found[0][0].strip())
reg_std = float(found[0][1].strip())
throughput_mean = float(found[1][0].strip())
throughput_std = float(found[1][1].strip())
return Result(reg_mean, reg_std, throughput_mean, throughput_std)
def main():
results_path = os.path.dirname(__file__) + '/results'
results = {}
for filename in os.listdir(results_path):
found = re.findall(r'odometry_benchmark_(\S+)_(native|nonnative)_(\d+).txt', filename)
if not found:
continue
rets = parse_result(results_path + '/' + filename)
results['{}_{}_{}'.format(found[0][0], found[0][1], found[0][2])] = rets
fig, axes = pyplot.subplots(1, 1, figsize=(12, 2))
axes = [axes]
num_threads = [1, 2, 4, 8, 16, 32, 64, 128]
print(results['small_gicp_native_1'], results['small_gicp_tbb_native_1'])
print(results['small_gicp_nonnative_1'], results['small_gicp_tbb_nonnative_1'])
native = [results['small_gicp_tbb_native_{}'.format(N)].reg_mean for N in num_threads]
nonnative = [results['small_gicp_tbb_nonnative_{}'.format(N)].reg_mean for N in num_threads]
axes[0].plot(num_threads, native, label='small_gicp_tbb (-march=native)', marker='o')
axes[0].plot(num_threads, nonnative, label='small_gicp_tbb (nonnative)', marker='o')
axes[0].set_xlabel('Number of threads [1, 2, ..., 128]')
axes[0].set_ylabel('Time [msec/scan]')
axes[0].set_xscale('log')
axes[0].grid()
axes[0].legend()
pyplot.show()
if __name__ == "__main__":
main()