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distance_trace_display.py
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distance_trace_display.py
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import matplotlib.pyplot as plt
from matplotlib.pyplot import MultipleLocator
import numpy as np
import os
import sys
import re
LOG_FILE_EXTENSION = ".log"
LOG_FILE_PREFIX = "Blvd_New_R"
OUTPU_FOLDER = "plot trace\\"
def parse_log_file(root, input_file):
data_ori = []
data_optimized = []
rx_fail_list = []
## 全局变量设置
title = os.path.splitext(input_file)[0]
input_file = os.path.join(root, input_file)
y_angle_min = -90
y_angle_max = 90
y_angle_multipleLocator = 10
RAW_DISTANCE_PATTERN = "Raw Distance"
FILTER_DISTANCE_PATTERN = "Peer .* Distance"
RX_FAIL_PATTERN = "UWB RX fail"
with open(input_file,'r') as fin:
for line in fin:
raw_distance_re = re.search(r'%s (\d+)cm' %RAW_DISTANCE_PATTERN, line)
if raw_distance_re:
data_ori.append(int(raw_distance_re.group(1)))
filter_distance_re = re.search(r'%s (\d+)cm' %FILTER_DISTANCE_PATTERN, line)
if filter_distance_re:
data_optimized.append(int(filter_distance_re.group(1)))
rx_fail_re = re.search(r'%s 0x(\d+)' %RX_FAIL_PATTERN, line)
if rx_fail_re:
rx_fail_list.append(int(rx_fail_re.group(1), 16))
if len(data_ori) == 0:
return
if len(data_ori) < len(data_optimized):
remove_count = len(data_optimized) - len(data_ori)
data_optimized = data_optimized[0 : -remove_count]
if len(data_ori) > len(data_optimized):
remove_count = len(data_ori) - len(data_optimized)
data_ori = data_ori[0 : -remove_count]
min_val_ori = min(data_ori)
max_val_ori = max(data_ori)
delta_val_ori = max_val_ori - min_val_ori
min_val_optimized = min(data_optimized)
max_val_optimized = max(data_optimized)
delta_val_optimized = max_val_optimized - min_val_optimized
print ('min_val_ori = ', min_val_ori)
print ('max_val_ori = ', max_val_ori)
print ('delta_val_ori = ', delta_val_ori)
print ('min_val_optimized = ', min_val_optimized)
print ('max_val_optimized = ', max_val_optimized)
print ('delta_val_optimized = ', delta_val_optimized)
min_all = min(min_val_ori, min_val_optimized)
max_all = max(max_val_ori, max_val_optimized)
print ('min_all = ', min_all)
print ('max_all = ', max_all)
# plt.rcParams['font.sans-serif'] = ['SimHei']
'''
设置纵轴的范围和刻度，影响整体的美观度！！
'''
y_min = (min_all // 10) * 10 - 40 # //获整数部分
y_max = (max_all // 10) * 10 + 20
#y_min = 13900
#y_max = 14100
y_multipleLocator = 10
plt.figure(figsize=(40,20))
ax = plt.gca()
ax.yaxis.set_major_locator(MultipleLocator(y_multipleLocator)) #设置纵坐标刻度
ax.set_ylabel('Distance / cm', fontsize=20)
ax.set_title(title, fontsize=30)
x = [i+1 for i in range(len(data_ori))]
plt.grid()
plt.plot(x, data_ori, color='darkblue',label='origin')
plt.plot(x, data_optimized, color='darkred',label='optimized')
plt.legend(fontsize=20)
plt.axis([0, len(data_ori), y_min, y_max]) #set the x and y axis ranging
## 数值处理
std_ori = np.std(data_ori)
std_ori = round(std_ori,2) #数值精度 保留4位
std_optimized = np.std(data_optimized)
std_optimized = round(std_optimized,2)
print ('std_ori = ', std_ori)
print ('std_optimized = ', std_optimized)
## 添加关键信息
y_index_text = (min_all // 5 ) * 5 - y_multipleLocator
x_ori = 1
x_list = [x_ori, x_ori, x_ori, x_ori]
y_list = [y_index_text,y_index_text - y_multipleLocator, y_index_text - y_multipleLocator*2,y_index_text - y_multipleLocator*3]
text = []
text.append('min of ori = ' + str(min_val_ori) + 'cm') # + 字符串拼接
text.append('max of ori = ' + str(max_val_ori) + 'cm')
text.append('delta of ori = ' + str(delta_val_ori) + 'cm')
text.append('std of ori = ' + str(std_ori) + 'cm')
for idx in range(len(x_list)): #range :
plt.text(x_list[idx],y_list[idx],text[idx],color='darkblue',fontsize=20)
#x_list = [len(data_ori) / 2,len(data_ori) / 2, len(data_ori) / 2, len(data_ori) / 2]
x_opt = len(data_ori) / 5
x_list = [x_opt, x_opt, x_opt, x_opt]
y_list = [y_index_text,y_index_text - y_multipleLocator, y_index_text
- y_multipleLocator*2, y_index_text - y_multipleLocator*3]
text = []
text.append('min of optimized = ' + str(min_val_optimized) + 'cm')
text.append('max of optimized = ' + str(max_val_optimized) + 'cm')
text.append('delta of optimized = ' + str(delta_val_optimized) + 'cm')
text.append('std of optimized = ' + str(std_optimized) + 'cm')
idx = 0
for idx in range(len(x_list)):
plt.text(x_list[idx],y_list[idx],text[idx],color='darkred',fontsize=20)
#lack_rate = fail_count / (max(data_package) - min(data_package) + 1)
#lack_rate = round(lack_rate, 4)*100
lack_rate = len(rx_fail_list) / (len(rx_fail_list) + len(data_ori))*100
lack_rate = round(lack_rate, 2)
x = x_opt * 2
y = y_index_text
text = 'ranging failed = ' + str(lack_rate) + '%'
plt.text(x,y,text,color='green',fontsize=20)
#creating folder
output_dir = os.path.join(root, OUTPU_FOLDER)
if not os.path.isdir(output_dir):
os.mkdir(output_dir)
plt.savefig(output_dir + title + '.png')
# plt.show()
def find_all_file(base):
for root, dirs, files in os.walk(base):
for f in files:
print(f)
yield f
#list all files in current direction, could not include the subdirection.
def find_cur_dir_files(path):
file_name = []
for file in os.listdir(path):
print(file)
file_name.append(file)
return file_name
# if __name__ == '__main__':
# path = os.getcwd()
# print(path)
# for i in find_cur_dir_files(path):
# if i.endswith(LOG_FILE_EXTENSION):
# print(i)
# print("---------------new file-----------------")
# parse_log_file(i)
def parse_file_and_draw_trace(root, files):
for file in files:
if file.endswith(LOG_FILE_EXTENSION) and file.startswith(LOG_FILE_PREFIX):
parse_log_file(root, file)
pass
if __name__ == '__main__':
for root, dirs, files in os.walk(".", topdown=False):
parse_file_and_draw_trace(root, files)