光栅图像不适合叶片地图（leaflet.js）

Question

我正在尝试从传单中的netcdf文件绘制光栅图像，但在地图中不适合正确的光栅图像。感谢您的帮助，也许解决方法是使用rasterio或geopandas投影。我使用的代码：

import xarray as xr
import numpy as np
import matplotlib.pyplot as plt
import folium

# geting Tmax
# you can download netcdf file here: https://www.dropbox.com/s/r7oxk8q3kh4ozs7/Tmax_daily_UT_Brazil_v2.1_19900101_19991231.nc?dl=0
path = '/home/'
data = xr.open_mfdataset(path + 'Tmax_daily_UT_Brazil_v2.1_19800101_19891231.nc', combine='by_coords').Tmax

data2plot = np.flipud(data.isel(time=0).values.astype(np.float64))
lon, lat = np.meshgrid(data.longitude.values.astype(np.float64), data.latitude.values.astype(np.float64))

cm = plt.cm.get_cmap('cubehelix')
normed_data = (data2plot - np.nanmin(data2plot)) / (np.nanmax(data2plot) - np.nanmin(data2plot))
colored_data = cm(normed_data)

m = folium.Map(location=[lat.mean(), lon.mean()], zoom_start=4)
folium.raster_layers.ImageOverlay(
    image=colored_data,
    bounds=[[lat.min(), lon.min()], [lat.max(), lon.max()]],
    opacity=0.5
).add_to(m)

m.save('test_xarray_folium.html')

如您在下面看到的，图像在地图上不正确。

Answer 1

我在以下位置找到了解决方案的基础：https://github.com/ocefpaf/folium_notebooks/blob/master

import xarray as xr
import numpy as np
import folium
from cartopy.img_transform import warp_array
import cartopy.crs as ccrs
import matplotlib.cm

# based in https://github.com/ocefpaf/folium_notebooks/blob/master/test_image_overlay_geodetic.ipynb
# get data
path = '/home/'
data = xr.open_mfdataset(path + 'Tmax_daily_UT_Brazil_v2.1_19800101_19891231.nc', combine='by_coords').Tmax
data2plot = np.flipud(data.isel(time=0).values.astype(np.float64))
lon, lat = np.meshgrid(data.longitude.values.astype(np.float64), data.latitude.values.astype(np.float64))
source_extent = [lon.min(), lon.max(), lat.min(), lat.max()]
normed_data = (data2plot - np.nanmin(data2plot)) / (np.nanmax(data2plot) - np.nanmin(data2plot))
cm = matplotlib.cm.get_cmap('cubehelix')
colored_data = cm(normed_data)

m = folium.Map(location=[lat.mean(), lon.mean()], zoom_start=4)
folium.raster_layers.ImageOverlay(colored_data,
                     [[lat.min(), lon.min()], [lat.max(), lon.max()]],
                     mercator_project=True,
                     opacity=0.5).add_to(m)

m.save('test_xarray_folium.html')