bakeup
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@ -9,7 +9,8 @@ func: extract_data()
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import numpy as np
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import re
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import os
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from collections import OrderedDict
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import matplotlib.pyplot as plt
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@ -206,19 +207,130 @@ def read_deletedBarcode_file(filePth):
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return all_list
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def read_weight_timeConsuming(filePth):
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WeightDict, SensorDict, ProcessTimeDict = OrderedDict(), OrderedDict(), OrderedDict()
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with open(filePth, 'r', encoding='utf-8') as f:
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lines = f.readlines()
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for i, line in enumerate(lines):
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line = line.strip()
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if line.find(':') < 0: continue
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if line.find("Weight") >= 0:
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label = "Weight"
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continue
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if line.find("Sensor") >= 0:
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label = "Sensor"
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continue
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if line.find("processTime") >= 0:
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label = "ProcessTime"
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continue
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keyword = line.split(':')[0]
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value = line.split(':')[1]
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if label == "Weight":
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WeightDict[keyword] = float(value.strip(','))
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if label == "Sensor":
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SensorDict[keyword] = [float(s) for s in value.split(',') if len(s)]
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if label == "ProcessTime":
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ProcessTimeDict[keyword] = float(value.strip(','))
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# print("Done!")
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return WeightDict, SensorDict, ProcessTimeDict
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def plot_sensor_curve(WeightDict, SensorDict, ProcessTimeDict):
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wtime, wdata = [], []
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stime, sdata = [], []
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for key, value in WeightDict.items():
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wtime.append(int(key))
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wdata.append(value)
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for key, value in SensorDict.items():
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if len(value) != 9: continue
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stime.append(int(key))
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sdata.append(np.array(value))
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static_range = []
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dynamic_range = []
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windth = 8
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nw = len(wdata)
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assert(nw) >= 8, "The num of weight data is less than 8!"
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i1, i2 = 0, 7
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while i2 < nw:
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data = wdata[i1:(i2+1)]
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max(data) - min(data)
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if i2<7:
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i1 = 0
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else:
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i1 = i2-windth
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min_t = min(wtime + stime)
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wtime = [t-min_t for t in wtime]
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stime = [t-min_t for t in stime]
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max_t = max(wtime + stime)
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fig = plt.figure(figsize=(16, 12))
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gs = fig.add_gridspec(2, 1, left=0.1, right=0.9, bottom=0.1, top=0.9,
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wspace=0.05, hspace=0.15)
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# ax1, ax2 = axs
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ax1 = fig.add_subplot(gs[0,0])
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ax2 = fig.add_subplot(gs[1,0])
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ax1.plot(wtime, wdata, 'b--', linewidth=2 )
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for i in range(9):
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ydata = [s[i] for s in sdata]
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ax2.plot(stime, ydata, linewidth=2 )
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ax1.grid(True), ax1.set_xlim(0, max_t), ax1.set_title('Weight')
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ax1.set_label("(Time: ms)")
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# ax1.legend()
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ax2.grid(True), ax2.set_xlim(0, max_t), ax2.set_title('IMU')
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# ax2.legend()
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plt.show()
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def main(file_path):
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WeightDict, SensorDict, ProcessTimeDict = read_weight_timeConsuming(file_path)
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plot_sensor_curve(WeightDict, SensorDict, ProcessTimeDict)
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if __name__ == "__main__":
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files_path = 'D:/contrast/dataset/1_to_n/709/20240709-112658_6903148351833/'
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# 遍历目录下的所有文件和目录
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files_path = r'\\192.168.1.28\share\测试_202406\0814\0814\20240814-102227-62264578-a720-4eb9-b95e-cb8be009aa98_null'
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k = 0
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for filename in os.listdir(files_path):
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filename = '1_track.data'
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filename = 'process.data'
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file_path = os.path.join(files_path, filename)
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if os.path.isfile(file_path) and filename.find("track.data")>0:
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extract_data(file_path)
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print("Done")
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if os.path.isfile(file_path) and filename.find("process.data")>=0:
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main(file_path)
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k += 1
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if k == 1:
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break
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# print("Done")
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