具有x,y地理坐标的值表“ tempcc”(不知道此处是否附加文件,我的csv中有86行):
X Y Temp
0 35.268 55.618 1.065389
1 35.230 55.682 1.119160
2 35.508 55.690 1.026214
3 35.482 55.652 1.007834
4 35.289 55.664 1.087598
5 35.239 55.655 1.099459
6 35.345 55.662 1.066117
7 35.402 55.649 1.035958
8 35.506 55.643 0.991939
9 35.526 55.688 1.018137
10 35.541 55.695 1.017870
11 35.471 55.682 1.033929
12 35.573 55.668 0.985559
13 35.547 55.651 0.982335
14 35.425 55.671 1.042975
15 35.505 55.675 1.016236
16 35.600 55.681 0.985532
17 35.458 55.717 1.063691
18 35.538 55.720 1.037523
19 35.230 55.726 1.146047
20 35.606 55.707 1.003364
21 35.582 55.700 1.006711
22 35.350 55.696 1.087173
23 35.309 55.677 1.088988
24 35.563 55.687 1.003785
25 35.510 55.764 1.079220
26 35.334 55.736 1.119026
27 35.429 55.745 1.093300
28 35.366 55.752 1.119061
29 35.501 55.745 1.068676
.. ... ... ...
56 35.472 55.800 1.117183
57 35.538 55.855 1.134721
58 35.507 55.834 1.129712
59 35.256 55.845 1.211969
60 35.338 55.823 1.174397
61 35.404 55.835 1.162387
62 35.460 55.826 1.138965
63 35.497 55.831 1.130774
64 35.469 55.844 1.148516
65 35.371 55.510 0.945187
66 35.378 55.545 0.969400
67 35.456 55.502 0.902285
68 35.429 55.517 0.925932
69 35.367 55.710 1.090652
70 35.431 55.490 0.903296
71 35.284 55.606 1.051335
72 35.234 55.634 1.088135
73 35.284 55.591 1.041181
74 35.354 55.587 1.010446
75 35.332 55.581 1.015004
76 35.356 55.606 1.023234
77 35.311 55.545 0.997468
78 35.307 55.575 1.020845
79 35.363 55.645 1.047831
80 35.401 55.628 1.021373
81 35.340 55.629 1.045491
82 35.440 55.643 1.017227
83 35.293 55.630 1.063910
84 35.370 55.623 1.029797
85 35.238 55.601 1.065699
我尝试使用以下方法创建等值线:
from numpy import meshgrid,linspace
data=tempcc
m = Basemap(lat_0 = np.mean(tempcc['Y'].values),\
lon_0 = np.mean(tempcc['X'].values),\
llcrnrlon=35,llcrnrlat=55.3, \
urcrnrlon=35.9, urcrnrlat=56.0, resolution='l')
x = linspace(m.llcrnrlon, m.urcrnrlon, data.shape[1])
y = linspace(m.llcrnrlat, m.urcrnrlat, data.shape[0])
xx, yy = meshgrid(x, y)
m.contour(xx, yy, data,latlon=True)
#pt.legend()
m.scatter(tempcc['X'].values, tempcc['Y'].values, latlon=True)
#m.contour(x,y,data,latlon=True)
但是我无法正确处理,尽管一切似乎都很好。据我了解,我必须制作一个二维值矩阵,其中i是lat,j是lon,但我找不到该示例。 The result I get
如您所见,区域正确,但是插值效果不好。
怎么了?我忘记了哪个参数?
答案 0 :(得分:0)
您可以使用Triangulation,然后调用tricontour()而不是contour()
import matplotlib.pyplot as plt
from matplotlib.tri import Triangulation
from mpl_toolkits.basemap import Basemap
import numpy
m = Basemap(lat_0 = np.mean(tempcc['Y'].values),
lon_0 = np.mean(tempcc['X'].values),
llcrnrlon=35,llcrnrlat=55.3,
urcrnrlon=35.9, urcrnrlat=56.0, resolution='l')
triMesh = Triangulation(tempcc['X'].values, tempcc['Y'].values)
tctr = m.tricontour(triMesh, tempcc['Temp'].values,
levels=numpy.linspace(min(tempcc['Temp'].values),
max(tempcc['Temp'].values), 7),
latlon=True)