基于ESP32的地毯式搜索设备

import pandas as pd import folium #读取保存了GPS位置的文件 df = pd.read_csv("TEST002.csv",encoding = 'gb2312') #处理经度 df1 = (df.iloc[:,4] - int(df.iloc[:,4][0]/100)*100)/60 + int(df.iloc[:,4][0]/100) #处理纬度 df2 = (df.iloc[:,3] - int(df.iloc[:,3][0]/100)*100)/60 + int(df.iloc[:,3][0]/100) group_A_jingdu = df1[df.iloc[:,2] == 'A'] group_A_weidu = df2[df.iloc[:,2] == 'A'] group_B_jingdu = df1[df.iloc[:,2] == 'B'] group_B_weidu = df2[df.iloc[:,2] == 'B'] group_C_jingdu = df1[df.iloc[:,2] == 'C'] group_C_weidu = df2[df.iloc[:,2] == 'C'] group_A_df3 = pd.DataFrame({'latitude':group_A_weidu,'longitude':group_A_jingdu}) group_B_df3 = pd.DataFrame({'latitude':group_B_weidu,'longitude':group_B_jingdu}) group_C_df3 = pd.DataFrame({'latitude':group_C_weidu,'longitude':group_C_jingdu}) #dataframe转为列表 group_A_df4 = group_A_df3.values.tolist() group_B_df4 = group_B_df3.values.tolist() group_C_df4 = group_C_df3.values.tolist() import math def get_C_coordinate(A, B, d): x1, y1 = A x2, y2 = B d = d AB = (x2 - x1, y2 - y1) AB_len = math.sqrt(AB[0] ** 2 + AB[1] ** 2) u = (AB[0] / AB_len, AB[1] / AB_len) BC_len = d theta = math.pi / 2 cos_t = math.cos(theta) sin_t = math.sin(theta) BC_x = u[0] * cos_t - u[1] * sin_t BC_y = u[0] * sin_t + u[1] * cos_t BC = (BC_x * BC_len, BC_y * BC_len) x_c, y_c = x2 + BC[0], y2 + BC[1] return x_c, y_c def get_D_coordinate(A, B, d): x1, y1 = A x2, y2 = B d = d AB = (x2 - x1, y2 - y1) AB_len = math.sqrt(AB[0] ** 2 + AB[1] ** 2) u = (AB[0] / AB_len, AB[1] / AB_len) BC_len = d theta = math.pi / 2 cos_t = math.cos(theta) sin_t = math.sin(theta) BC_x = u[0] * cos_t - u[1] * sin_t BC_y = u[0] * sin_t + u[1] * cos_t BC = (BC_x * BC_len, BC_y * BC_len) x_c, y_c = x2 - BC[0], y2 - BC[1] return x_c, y_c group_A_C_list = [] group_A_D_list = [] group_A_df3.index = range(len(group_A_df3)) for i in range(0,len(group_A_df3)-1): A = [group_A_df3['latitude'][i], group_A_df3['longitude'][i]] B = [group_A_df3['latitude'][i+1],group_A_df3['longitude'][i+1]] d = 0.0001 C = get_C_coordinate(A, B, d) my_list_C = list(C) group_A_C_list.append(my_list_C) print(B) for i in range(0,len(group_A_df3)-1): A = [group_A_df3['latitude'][i], group_A_df3['longitude'][i]] B = [group_A_df3['latitude'][i+1],group_A_df3['longitude'][i+1]] d = 0.0001 D = get_D_coordinate(A, B, d) my_list_D = list(D) group_A_D_list.append(my_list_D) group_B_C_list = [] group_B_D_list = [] group_B_df3.index = range(len(group_B_df3)) for i in range(0,len(group_B_df3)-1): A = [group_B_df3['latitude'][i], group_B_df3['longitude'][i]] B = [group_B_df3['latitude'][i+1],group_B_df3['longitude'][i+1]] d = 0.0001 C = get_C_coordinate(A, B, d) my_list_C = list(C) group_B_C_list.append(my_list_C) for i in range(0,len(group_B_df3)-1): A = [group_B_df3['latitude'][i], group_B_df3['longitude'][i]] B = [group_B_df3['latitude'][i+1],group_B_df3['longitude'][i+1]] d = 0.0001 D = get_D_coordinate(A, B, d) my_list_D = list(D) group_B_D_list.append(my_list_D) group_C_C_list = [] group_C_D_list = [] group_C_df3.index = range(len(group_C_df3)) for i in range(0,len(group_C_df3)-1): A = [group_C_df3['latitude'][i], group_C_df3['longitude'][i]] B = [group_C_df3['latitude'][i+1],group_C_df3['longitude'][i+1]] d = 0.0001 C = get_C_coordinate(A, B, d) my_list_C = list(C) group_C_C_list.append(my_list_C) for i in range(0,len(group_C_df3)-1): A = [group_C_df3['latitude'][i], group_C_df3['longitude'][i]] B = [group_C_df3['latitude'][i+1],group_C_df3['longitude'][i+1]] d = 0.0001 D = get_D_coordinate(A, B, d) my_list_D = list(D) group_C_D_list.append(my_list_D) group_A_C_data = group_A_C_list group_A_D_data = group_A_D_list group_B_C_data = group_B_C_list group_B_D_data = group_B_D_list group_C_C_data = group_C_C_list group_C_D_data = group_C_D_list # 将整个二维列表反转 reversed_r_group_A_D_data = list(reversed(group_A_D_data)) group_A_CD = group_A_C_data + reversed_r_group_A_D_data group_A_CD.append(group_A_C_data[0]) # 将整个二维列表反转 reversed_r_group_B_D_data = list(reversed(group_B_D_data)) group_B_CD = group_B_C_data + reversed_r_group_B_D_data group_B_CD.append(group_B_C_data[0]) # 将整个二维列表反转 reversed_r_group_C_D_data = list(reversed(group_C_D_data)) group_C_CD = group_C_C_data + reversed_r_group_C_D_data group_C_CD.append(group_C_C_data[0]) ### 绘制地图 #### m = folium.Map(group_A_df4[0], zoom_start=15,position='absolutely', attr='default',zoom_control=True) #中心区域的确定 folium.PolyLine( group_A_df4, weight=3, color='red', opacity=0.8, ).add_to(m) # 起始点，结束点 folium.Marker(group_A_df4[0], popup='<b>Starting Point</b>').add_to(m) folium.Marker(group_A_df4[-1], popup='<b>End Point</b>').add_to(m) ll = folium.PolyLine(locations = group_A_CD, color='black', opacity=0.8, fill=True, fill_color='#111111') folium.PolyLine( group_B_df4, weight=3, color='blue', opacity=0.8 ).add_to(m) folium.Marker(group_B_df4[0], popup='<b>Starting Point</b>').add_to(m) folium.Marker(group_B_df4[-1], popup='<b>End Point</b>').add_to(m) ls = folium.PolyLine(locations = group_B_CD, color='orange', opacity=0.8, fill=True, fill_color='#111111') folium.PolyLine( group_C_df4, weight=3, color='blue', opacity=0.8 ).add_to(m) folium.Marker(group_C_df4[0], popup='<b>Starting Point</b>').add_to(m) folium.Marker(group_C_df4[-1], popup='<b>End Point</b>').add_to(m) ls = folium.PolyLine(locations = group_C_CD, color='red', opacity=0.8, fill=True, fill_color='#111111') ls.add_to(m) ll.add_to(m) m