Question

我已经为我的原始gps数据计算了停靠点，并且希望为我的输出导入target_id。请注意，输入文件的大小与输出的大小不同

id，时间，纬度，经度，海拔，精度，轴承，速度，卫星，提供者，hdop，vdop，pdop，geoidheigh，track_id，target_id 0,2018-08-19T14：29：28.000Z，52.38250042,9.725429713,101,18.224，，0,0，gps，``，''，1,75924 1,2018-08-19T14：29：31.000Z，52.38250202,9.725448912,101,11.792，，0,0，gps，0.8,0.7,1,46,1,75924 2,2018-08-19T14：29：32.631Z，52.38247107,9.725490814,102,9.648001，，0,15，gps，0.8,0.7,1,46,1,36337 3,2018-08-19T14：29：34.777Z，52.3825016,9.725443781,101,9.648001，，0,14，gps，``46,1,75924 4,2018-08-19T14：29：36.910Z，52.38250126,9.725439726,100,8.576，，0,15，gps，``46,1,75924 5,2018-08-19T14：29：39.039Z，52.38250164,9.72544436,100,7.504，，0,10，gps，``46,1,75924 6,2018-08-19T14：29：41.238Z，52.38246406,9.725492349,100,7.504，，0,0，gps，``46,1,36337 7,2018-08-19T14：29：43.387Z，52.38246311,9.725492558,100,6.432，，0,0，gps，1.5,0.8,1.7,46,1,36337 8,2018-08-19T14：29：45.548Z，52.38236408,9.725469972,100,6.432,166.9,2.63,9，gps，1.5,0.8,1.7,46,1,76994 9,2018-08-19T14：29：47.682Z，52.38228523,9.725550264,97,6.432,169.9,5.44,8，gps，``46,1,37044 10,2018-08-19T14：29：49.840Z，52.38216741,9.725602733,97,7.504,163.4,6.21,6，gps，``46,1,37044 11,2018-08-19T14：29：53.000Z，52.38205119,9.725687278,90,10.72,155.8,6.11,0，gps ,,,, 46,1,36330

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# Input trajectory data
dataset = pd.read_csv("matched_all.csv")
m = dataset.query('track_id==1')
m_asarray = m.values
num_pt,num_attr = m_asarray.shape
# A basic model for stop detection based on velocity
velocity = m_asarray[:,7]
v_threshold = 0.02
is_stop = np.zeros(num_pt, dtype=bool)
for i in range(num_pt):
    if velocity[i] < v_threshold:
        is_stop[i] = 1
# plot
lat = m_asarray[:,2]
lon = m_asarray[:,3]
target_id = m_asarray[:,15]
plt.plot(lon,lat)
#plt.scatter(lon[is_stop],lat[is_stop])
# Clustering and Filtering
i = 0
count = 0  # Number of Stops
stops = np.zeros([0,2])
while i < num_pt:
    if is_stop[i] == True :
        j = 0
        while i+j < num_pt and is_stop[i+j] == True :
            j = j+1
        a = np.mean(lat[i:i+j]) 
        b = np.mean(lon[i:i+j])
        coords = np.hstack((a,b))
        stops = np.vstack((stops,coords))
        count = count+1
        i = i+j
        continue
    i = i+1
#print(stops)
print(stops)
plt.scatter(stops[:,1],stops[:,0],c='r',marker='o')
stops_as_df = pd.DataFrame(columns=['lat','lon'],data=stops)
file_name = 'stops_example.csv'
stops_as_df.to_csv(file_name,sep=',',encoding='utf-8')
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从输入到输出添加属性

0 个答案: