更新：我正在尝试映射一些数据。我有一组从网格中的参考点测量的后向方位角（baz）。我想在网格上找到沿着 baz 的一个大圆圈会穿过的所有点。为此，我遍历网格中的每个点，计算该点与参考点之间的预期后向方位角，并与每个测量的 baz 进行比较。如果两者之间的差异很小（小于 2 度），我会权衡这一点。然后我把它全部放在地图上。我使用的代码如下，但结果看起来有点奇怪，有谁知道我哪里出错了，或者如果有更好的方法（更快）然后我做了什么？
from matplotlib.colorbar import ColorbarBase
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap
import mpl_toolkits.basemap.pyproj as pyproj
llcrnrlon = -30.0
llcrnrlat = 45.0
urcrnrlon = 0.0
urcrnrlat = 65.0
lon_0 = (urcrnrlon + llcrnrlon) / 2.
lat_0 = (urcrnrlat + llcrnrlat) / 2.
lat = 51.58661577 # reference point
lon = -9.18822525
# Generate random back-azimuths.
baz = zeros((20))
for i in xrange(len(baz)):
baz[i] = random.randint(200,230)
####################################################################
## Set up the map background.
m = Basemap(llcrnrlon=llcrnrlon,llcrnrlat=llcrnrlat,urcrnrlon=urcrnrlon,urcrnrlat=urcrnrlat,
resolution='i',projection='lcc',lon_0=lon_0,lat_0=lat_0)
m.drawcoastlines()
m.fillcontinents()
# draw parallels
m.drawparallels(np.arange(10,70,10),labels=[1,0,0,0])
# draw meridians
m.drawmeridians(np.arange(-80, 25, 10),labels=[0,0,0,1])
# Plot station locations.
x, y = m(lon, lat) # array ref points
m.plot(x,y,'ro', ms=5)
####################################################################
## Set up the grids etc.
glons = np.linspace(llcrnrlon, urcrnrlon, 100)
glats = np.linspace(llcrnrlat, urcrnrlat, 100)
# Convert to map coords.
xlons, ylats = m(glons, glats)
# create grid for pcolormesh.
grid_lon, grid_lat = np.meshgrid(xlons, ylats)
# create weights for pcolormesh.
weights = np.zeros(np.shape(grid_lon))
# create grid of lat-lon coords for baz calculation.
gln, glt = np.meshgrid(glons, glats)
####################################################################
## calculate baz from grid_lon, grid_lat to lon, lat. If less
## than error weight grid point.
# method for BAZ calculation via pyproj.
def get_baz(lon1, lat1, lon2, lat2):
g = pyproj.Geod(ellps='WGS84')
az, baz, dist = g.inv(lon1, lat1, lon2, lat2)
return baz
# BAZ calcultion for each point in grid.
ll=0
for mBAZ in baz:
for i in xrange(len(gln)):
for k in xrange(len(gln[i])):
nbaz = get_baz(lon, lat, gln[i][k], glt[i][k])
nbaz += 180
if abs(nbaz - mBAZ) < 2:
weights[i][k] = 1
ll+=1
# plot grid.
m.pcolormesh(grid_lon, grid_lat, weights, cmap=plt.cm.YlOrBr)
plt.colorbar()
plt.show()
下面的原始问题，现在已经过时了。
我正在尝试映射一些数据。我有一个数据集，它为每个方向提供一系列值（频率）。我想将它们绘制在网格上，以便沿特定方位角的每个网格点都由特定频率的功率加权。我创建了一个带有底图的地图并在其上绘制了一个网格，如下所示，
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
from shoot import *
llcrnrlon = -20.0
llcrnrlat = 45.0
urcrnrlon = 10.0
urcrnrlat = 65.0
lon_0 = (urcrnrlon + llcrnrlon) / 2.
lat_0 = (urcrnrlat + llcrnrlat) / 2.
m = Basemap(llcrnrlon=llcrnrlon,llcrnrlat=llcrnrlat,urcrnrlon=urcrnrlon,urcrnrlat=urcrnrlat,
resolution='i',projection='lcc',lon_0=lon_0,lat_0=lat_0)
## Set up the grid.
glons = np.linspace(-20,10,50)
glats = np.linspace(45, 65, 50)
xlons, ylats = m(glons, glats)
grid_lon, grid_lat = np.meshgrid(xlons, ylats)
pwr = np.zeros((50,50))
m.drawcoastlines()
m.fillcontinents()
# draw parallels
m.drawparallels(np.arange(10,70,10),labels=[1,0,0,0])
# draw meridians
m.drawmeridians(np.arange(-80, 25, 10),labels=[0,0,0,1])
lats = [54.8639587, 51.5641564]
lons = [-8.1778180, -9.2754284]
x, y = m(lons, lats) # array ref points
# Plot station locations.
m.plot(x,y,'ro', ms=5)
m.pcolormesh(grid_lon, grid_lat, pwr)
然后我使用我在这个不错的网站上找到的一些功能射出我想要的大圆圈
glon1 = lons[0]
glat1 = lats[0]
azimuth = 280.
maxdist = 200.
great(m, glon1, glat1, azimuth, color='orange', lw=2.0)
plt.show()
但是，仅绘制线条是不够的，我希望能够找到大圆穿过的网格点，以便为它们分配值。有谁知道该怎么做？
