Python 带起点的流图的Cartopy platecarree和正交投影问题

我想使用

matplotlib

函数，将速度场（u，v）绘制为（经度，纬度）的函数，并将其作为流图、板内卡利（lon-lat）和正交投影。我希望固定流图的起点，因为我希望最终创建一些特征在球体上旋转的动画，其中流线“锚定”在某处。然而，我在这些预测中遇到了一些问题，下面将进一步详述

我使用以下软件包版本：

Python

3.7.6、

matplotlib

3.2.2、

cartopy

0.18.0

---

创建包含或不包含上述预测起点的流线图的“最小”示例为：

import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs

# define longitude and latitude grids
nlon, nlat = 48, 24
dlon, dlat = 7.5, 7.5
lons = np.linspace(-180+dlon,180,nlon)
lats = np.linspace(-90,90-dlat,nlat)

# define random velocity fields
np.random.seed(999)
u = np.random.rand(nlat, nlon)
v = np.random.rand(nlat, nlon)

# get indices of latitudes north of the equator and longitudes within +/- 90 deg
ilat_north = np.where(lats >= 0)[0]
ilon = np.where(np.abs(lons) <= 90)[0]

# create a list of 5 starting points at various latitudes aligned at a longitude of 0 deg
start_points = list(zip(list(np.linspace(0,0,5)),list(np.linspace(0,80,5))))

# output plot directory and whether plots should be saved
plot_dir = '/home/proxauf/test_streamplot_cartopy'
save_plots = True

def plot_streamplot(mode, start_points=None, figtitle=None, outname=None, save_plot=False):

    fig = plt.figure()
    if mode == 'mpl-platecarree':
        # a Plate-Carree projection without Cartopy (directly using matplotlib)
        ax = plt.gca()
        ax.streamplot(lons, lats[ilat_north], u[ilat_north,:], v[ilat_north,:], start_points=start_points)
    elif 'cartopy' in mode:
        if mode == 'cartopy-platecarree':
            # a Plate-Carree projection with Cartopy
            ax = plt.subplot(projection=ccrs.PlateCarree())
            ax.streamplot(lons, lats[ilat_north], u[ilat_north,:], v[ilat_north,:], start_points=start_points, transform=ccrs.PlateCarree())
        elif mode == 'cartopy-orthographic0':
            # an orthographic projection with a latitudinal inclination of 0 deg with Cartopy
            # restrict longitudes to +/- 90 deg, otherwise an error occurs (outside of projection area)
            ax = plt.subplot(projection=ccrs.Orthographic(central_longitude=0,central_latitude=0))
            ax.streamplot(lons[ilon], lats[ilat_north], u[ilat_north[:,None],ilon[None,:]], v[ilat_north[:,None], ilon[None,:]], start_points=start_points, transform=ccrs.PlateCarree())
        if mode == 'cartopy-orthographic90':
            # an orthographic projection with a latitudinal inclination of 90 deg with Cartopy
            ax = plt.subplot(projection=ccrs.Orthographic(central_longitude=0,central_latitude=90))
            ax.streamplot(lons, lats[ilat_north], u[ilat_north,:], v[ilat_north,:], start_points=start_points, transform=ccrs.PlateCarree())
    if 'platecarree' in mode:
        ax.set_xlim(-180,180)
        ax.set_ylim(-90,90)
    ax.set_aspect('equal')
    if 'cartopy' in mode:
        # draw gridlines with label for visual orientation
        ax.gridlines(draw_labels=True)
    if start_points is not None:
        # plot starting points for the streamplot
        for i in start_points:
            if 'cartopy' in mode:
                ax.plot(i[0],i[1],marker='o',transform=ccrs.PlateCarree())
            else:
                ax.plot(i[0],i[1],marker='o')
    fig.suptitle(figtitle)
    if save_plot:
        # save the plot and close it
        plt.savefig('%s/%s' % (plot_dir, outname))
        plt.close()

# create and save streamplots for different projections, with and without starting points
plot_streamplot(mode='mpl-platecarree', start_points=None, figtitle='mpl-platecarree, without start points', outname='test_streamplot_mpl_pc_sp_no.png', save_plot=save_plots)
plot_streamplot(mode='cartopy-platecarree', start_points=None, figtitle='cartopy-platecarree, without start points', outname='test_streamplot_cartopy_pc_sp_no.png', save_plot=save_plots)
plot_streamplot(mode='cartopy-orthographic0', start_points=None, figtitle='cartopy-orthographic0, without start points', outname='test_streamplot_cartopy_ortho0_sp_no.png', save_plot=save_plots)
plot_streamplot(mode='cartopy-orthographic90', start_points=None, figtitle='cartopy-orthographic90, without start points', outname='test_streamplot_cartopy_ortho90_sp_no.png', save_plot=save_plots)
plot_streamplot(mode='mpl-platecarree', start_points=start_points, figtitle='mpl-platecarree, with start points', outname='test_streamplot_mpl_pc_sp_yes.png', save_plot=save_plots)
plot_streamplot(mode='cartopy-platecarree', start_points=start_points, figtitle='cartopy-platecarree, with start points', outname='test_streamplot_cartopy_pc_sp_yes.png', save_plot=save_plots)
plot_streamplot(mode='cartopy-orthographic0', start_points=start_points, figtitle='cartopy-orthographic0, with start points', outname='test_streamplot_cartopy_ortho0_sp_yes.png', save_plot=save_plots)
plot_streamplot(mode='cartopy-orthographic90', start_points=start_points, figtitle='cartopy-orthographic90, with start points', outname='test_streamplot_cartopy_ortho90_sp_yes.png', save_plot=save_plots)

将numpy导入为np
将matplotlib.pyplot作为plt导入
将cartopy.crs作为CCR导入
#定义经纬度栅格
nlon，nlat=48,24
dlon，dlat=7.5,7.5
lons=np.linspace（-180+dlon，180，nlon）
lats=np.linspace（-90,90-dlat，nlat）
#定义随机速度场
np.随机种子（999）
u=np.random.rand（nlat，nlon）
v=np.random.rand（nlat，nlon）
#获取赤道以北的纬度指数和+/-90度范围内的经度指数
ilat_north=np.其中（纬度>=0）[0]
ilon=np.where（np.abs（lons）