mirror of https://github.com/koide3/small_gicp.git
66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
#!/usr/bin/python3
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import os
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import re
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import numpy
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from collections import namedtuple
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from matplotlib import pyplot
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Result = namedtuple('Result', ['reg_mean', 'reg_std', 'tp_mean', 'tp_std'])
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def parse_result(filename):
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reg_mean = None
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reg_std = None
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throughput_mean = None
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throughput_std = None
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with open(filename, 'r') as f:
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for line in f.readlines():
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found = re.findall(r'([^=]+)\s*\+\-\s*(\S+)', line)
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if not found or len(found) != 2:
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found = re.findall(r'total_throughput=(\S+)', line)
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if found:
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throughput_mean = float(found[0])
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continue
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reg_mean = float(found[0][0].strip())
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reg_std = float(found[0][1].strip())
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throughput_mean = float(found[1][0].strip())
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throughput_std = float(found[1][1].strip())
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return Result(reg_mean, reg_std, throughput_mean, throughput_std)
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def main():
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results_path = os.path.dirname(__file__) + '/results'
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results = {}
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for filename in os.listdir(results_path):
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found = re.findall(r'odometry_benchmark_(\S+)_(native|nonnative)_(\d+).txt', filename)
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if not found:
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continue
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rets = parse_result(results_path + '/' + filename)
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results['{}_{}_{}'.format(found[0][0], found[0][1], found[0][2])] = rets
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fig, axes = pyplot.subplots(1, 1, figsize=(12, 2))
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axes = [axes]
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num_threads = [1, 2, 4, 8, 16, 32, 64, 128]
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print(results['small_gicp_native_1'], results['small_gicp_tbb_native_1'])
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print(results['small_gicp_nonnative_1'], results['small_gicp_tbb_nonnative_1'])
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native = [results['small_gicp_tbb_native_{}'.format(N)].reg_mean for N in num_threads]
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nonnative = [results['small_gicp_tbb_nonnative_{}'.format(N)].reg_mean for N in num_threads]
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axes[0].plot(num_threads, native, label='small_gicp_tbb (-march=native)', marker='o')
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axes[0].plot(num_threads, nonnative, label='small_gicp_tbb (nonnative)', marker='o')
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axes[0].set_xlabel('Number of threads [1, 2, ..., 128]')
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axes[0].set_ylabel('Time [msec/scan]')
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axes[0].set_xscale('log')
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axes[0].grid()
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axes[0].legend()
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pyplot.show()
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if __name__ == "__main__":
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main() |