如何在散点图框上绘制圆形半径图(Plotly Python)

首先，我在与您在屏幕截图中显示的数据相同的地理区域创建了一些样本数据.

然后，我们可以使用@Stéphane提供的[近似][1]来计算半径为r、中心点和采样点数量的圆的(纬度、经度)点(对于您的问题，您希望围绕中心点的5公里半径足够小，因此此近似很好地适用).

注意:我try 使用geog.propogate计算圆的确切坐标，但没有成功，如[此处概述][2]，但它没有为中心坐标周围的圆生成正确的坐标.

然后你可以将圆的(纬度，经度)点传递给go.Scattermapbox，将模式设置为‘线’，并将轨迹添加到你的图形中.

import numpy as np
import pandas as pd
import plotly.graph_objects as go
import plotly.express as px
from math import radians, cos, sin, asin, sqrt, pi

def haversine(lon1, lat1, lon2, lat2):

    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])

    dlon = lon2 - lon1 
    dlat = lat2 - lat1 
    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
    c = 2 * asin(sqrt(a)) 
    r = 6371
    return c * r

## create a sample dataframe to reproduce your data
lat_input, long_input = -0.622929, 117.575513,

lat_min, lat_max = -0.59, -0.68
long_min, long_max = 117.543, 117.614

np.random.seed(42)
df_latlong = pd.DataFrame({
    'Latitude': np.random.uniform(lat_min, lat_max, size=20),
    'Longitude': np.random.uniform(long_min, long_max, size=20),
    '#WELL': ["TN-test"]*20
})

center_point = pd.DataFrame({'Longitude':[long_input], 'Latitude':[lat_input]})
test_point = df_latlong[['Longitude','Latitude']].reset_index().drop('index',axis=1)

lat1 = center_point['Latitude'][0]
lon1 = center_point['Longitude'][0]

df_nearest = []
for i, (index, row) in enumerate(df_latlong.iterrows()):
    lat2 = test_point['Latitude'][i]
    lon2 = test_point['Longitude'][i]
    a = haversine(lon1, lat1, lon2, lat2)
    df_nearest.append(a)

df_latlong['Distance'] = df_nearest
df_radius = df_latlong[df_latlong['Distance'] <= 5] #5 kilometers for radius 

fig_map3 = px.scatter_mapbox(df_radius, lon=df_radius['Longitude'], lat=df_radius['Latitude'],
                             hover_name='#WELL', zoom=9, width=300, height=500)

radius = 5 * 1000 # m - the following code is an approximation that stays reasonably accurate for distances < 100km

# parameters
N = 360 # number of discrete sample points to be generated along the circle

# generate points
circle_lats, circle_lons = [], []
for k in range(N):
    # compute
    angle = pi*2*k/N
    dx = radius*cos(angle)
    dy = radius*sin(angle)
    circle_lats.append(lat1 + (180/pi)*(dy/6378137))
    circle_lons.append(lon1 + (180/pi)*(dx/6378137)/cos(lat1*pi/180))
circle_lats.append(circle_lats[0])
circle_lons.append(circle_lons[0])

fig_map3.add_trace(go.Scattermapbox(
    lat=circle_lats,
    lon=circle_lons,
    mode='lines',
    marker=go.scattermapbox.Marker(
        size=1, color="BlueViolet"
    ),
))

fig_map3.update_layout(mapbox_style='open-street-map', margin={'r':0, 't':0, 'l':0, 'b':0}, width=500)

fig_map3.show()