我有SRTM高程数据的numpy数组，我需要计算路径配置文件 - 从一个点（发射器）到我的地图的每个点的高程数据的矢量。这是我目前的解决方案：
def get_elev_vector(self, coord1, coord2, step=90):
if coord1 == coord2:
return 0
lat1, long1 = coord1
lat2, long2 = coord2
dist = self.get_dist(coord1, coord2)
npt = dist / step
vect = np.zeros(npt + 3, dtype='float32')
vect[0] = npt
vect[1] = dist
vect[2] = self.get_elevation_direct(coord1)
vect[npt] = self.get_elevation_direct(coord2)
g = pyproj.Geod(ellps='WGS84')
coordvect = g.npts(long1, lat1, long2, lat2, npt)
i = 3
for lon, lat in coordvect:
vect[i] = self.get_elevation((lat, lon))
i += 1
return vect
#(tx, ty) transmission coordinates
while lat > latmax:
long = longmin
while long<longmax:
vect = self.carta.get_elev_vector((tx, ty), (lat, lon))
arr[xarr, yarr] = 100
yarr +=1
lon += dlon
xarr +=1
lat +=dx
它有效，但20x20公里区域需要3个小时。有没有办法让它更快地运作？
添加
def get_elevation(self, coord):
"""TODO"""
lat, lon = self.xyfromlatlon(coord)
mlat = int(lat)
mlon = int(lon)
vicin = self.tile['numpy_array'][mlat: mlat + 2, mlon: mlon + 2]
temp_bool = np.equal(vicin, -32768)
np.putmask(vicin, temp_bool, 0)
elev = billin_interpol(vicin[0][0], vicin[0][1], vicin[1][0],
vicin[1][1], lat - mlat, lon - mlon)
return int(elev + 0.5)
def billin_interpol(tl, tr, bl, br, x, y):
"""Bilinear interpolation.
Return:
float, interpolated value
"""
b1 = tl
b2 = bl - tl
b3 = tr - tl
b4 = tl - bl - tr + br
return b1 + b2 * x + b3 * y + b4 * x * y