极坐标图作为地图上的图像

Question

我有这个代码块可以通过 matplotlib 极坐标图将陀螺仪校准绘制为罗盘，请参见下图。现在我想在 folium 地图上绘制指南针，以便观察者可以看到陀螺仪航向确实与校准期间船舶停泊的港口码头区对齐。

如何将极坐标图绘制为透明（白色背景透明）.png 或 .svg @ folium 地图上的位置坐标？

from pvlib import solarposition
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Polarplot

# user input _____________________________________________________________________________
tz = 'Europe/Amsterdam'
lat = 52+(57/60)+(26.9/3600)
lon =  4+(46/60)+(37.5/3600)
lat_dms, lon_dms ="52°57′26.9″","004°46′37.5″"  # position strings

loc_descr = "Den Helder - Nieuwe Diep"

# Corrected gyro heading
gyro_corrected = 154.92
st_dev_gyro = 0.03

# First fix Zn
first_fix = 138.873

# Last fix Zn
last_fix = 144.915
#user input ______________________________________________________________________________

# Function to convert degrees to radians
def degrees_to_radians(degrees):
    return degrees * np.pi / 180.0

# Convert angles to radians
gyro_corrected_rad = degrees_to_radians(gyro_corrected)
first_fix_rad = degrees_to_radians(first_fix)
last_fix_rad = degrees_to_radians(last_fix)

# */ solar trajectory plot ------------------------------------------------------------------------------------------------------
# set times for solar trajectory
times = pd.date_range('2019-12-31 00:00:00', '2020-01-01', freq='H', tz=tz)
solpos = solarposition.get_solarposition(times, lat, lon)
# remove nighttime
solpos = solpos.loc[solpos['apparent_elevation'] > 0, :]

#make polarplot
ax = plt.subplot(1, 1, 1, projection='polar')

# /* solar  plot ------------------------------------------------------------------------------------------------------

# Plot the corrected gyro heading vector
ax.quiver(0, 0, gyro_corrected_rad, 90, angles='xy', scale_units='xy', scale=1, color='darkgreen', label=f'Gyro Heading True: ({gyro_corrected} ± {st_dev_gyro})°')


# /* solar  plot ------------------------------------------------------------------------------------------------------
# draw hour labels
for hour in np.unique(solpos.index.hour):
    # choose label position by the smallest radius for each hour
    subset = solpos.loc[solpos.index.hour == hour, :]
    r = subset.apparent_zenith
    pos = solpos.loc[r.idxmin(), :]
    ax.text(np.radians(pos['azimuth']), pos['apparent_zenith'], str(hour))

# draw individual days
for date in pd.to_datetime(['2019-12-31']):
    times = pd.date_range(date, date+pd.Timedelta('24h'), freq='5min', tz=tz)
    solpos = solarposition.get_solarposition(times, lat, lon)
    solpos = solpos.loc[solpos['apparent_elevation'] > 0, :]
    label =  f"☀️ @ {date.strftime('%Y-%m-%d')} -localtime: UTC+1"
    ax.plot(np.radians(solpos.azimuth), solpos.apparent_zenith, label=label, color='darkorange', linewidth=2)
# /* solar trajectory plot ------------------------------------------------------------------------------------------------------

# Plot the line for the first fix
ax.plot([0, first_fix_rad], [0, 90], color= 'orange', linestyle='--', label=f'{first_fix}° -fix 1 ☀️')

# Plot the line for the last fix
ax.plot([0, last_fix_rad], [0, 90], color='gold', linestyle='--', label=f'{last_fix}° -last fix ☀️')

# change coordinates to be like a compass
data = pd.DataFrame({'value': [0, 20, 30, 20, 0, 10, 15, 10],
                     'bearing': range(0, 360, 45),
                     'compass': ['000°\nN', 'NE', '090°\n E', 'SE', '180°\nS', 'SW', '270°\nW', 'NW']})

data.index = data['bearing'] * 2*np.pi / 360

ax.set_title(f"Sunshot Gyro Calibration @ {lat_dms}N, {lon_dms}E\n{loc_descr}\n")

# Place the legend below the plot
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.18), fancybox=True, shadow=True, ncol=2) # 1.  

ax.set_theta_zero_location('N') # North-up
ax.set_theta_direction(-1)
ax.set_xticklabels(data.compass)
#ax.set_yticklabels()

ax.set_rgrids([])
ax.set_rmax(90)

plt.show()

Answer 1

IIUC，你可以

savefig

搭配透明背景，然后将其用作

FloatImage

:

plt.figure(figsize=(4, 2)) # <<< add this
ax = plt.subplot(1, 1, 1, projection='polar')

# rest of the code..

import io
import base64
import folium

buff = io.BytesIO()
plt.savefig(buff, transparent=True)
img = base64.b64encode(buff.getvalue()).decode()

m = folium.Map([lat, lon], zoom_start=10)

folium.plugins.FloatImage(
    f"data:image/png;base64,{img}", bottom=30, left=-5
).add_to(m)

输出（

m

）：