python中不规则网格上具有地图覆盖的等高线

以下是我的数据：

Lon   Lat     Z   Z2  pos
32.6  -13.6   41   9  CHIP
27.1  -16.9   43  12  CHOM
32.7  -10.2   46  14  ISOK
24.2  -13.6   33  13  KABO
28.5  -14.4   43  11  KABW
28.1  -12.6   33  16  KAFI
27.9  -15.8   46  13  KAFU
24.8  -14.8   44   9  KAOM
31.1  -10.2   35  14  KASA
25.9  -13.5   24   8  KASE
29.1   -9.8   10  13  KAWA
25.8  -17.8   39  11  LIVI
33.2  -12.3   44   8  LUND
28.3  -15.4   46  12  LUSA
27.6  -16.1   47   9  MAGO
28.9  -11.1   31  15  MANS
31.3   -8.9   39   9  MBAL
31.9  -13.3   45   9  MFUW
23.1  -15.3   31   9  MONG
31.4  -11.9   39   9  MPIK
27.1  -15.0   42  12  MUMB
24.4  -11.8   15   9  MWIN
28.6  -13.0   39   9  NDOL
31.3  -14.3   44  12  PETA
23.3  -16.1   39   5  SENA
30.2  -13.2   38  11  SERE
24.3  -17.5   32  10  SESH
26.4  -12.2   23  12  SOLW
23.1  -13.5   27  14  ZAMB

这是我试过的代码。给我带来问题的部分是数据网格和轮廓。下面的代码主要来自stackoverflow上的各种帖子，但很难找到任何与我的特定主题相关的内容

#!/usr/bin/python

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import griddata

#prepare a basemap
m = Basemap(projection = 'merc',llcrnrlon = 21, llcrnrlat = -18, urcrnrlon = 34, urcrnrlat = -8)
m.drawmapboundary(fill_color = 'white')
m.fillcontinents(color = '0.85')

# draw country outlines.
m.drawcountries(linewidth=0.5, linestyle='solid', color='k', antialiased=1, ax=None, zorder=None)

m.drawparallels(np.arange(-18, -8, 2.), color = '0.25', linewidth = 0.5)
m.drawparallels(parallels,labels=[True,False,False,False])

m.drawmeridians(np.arange(21,36, 2.), color = '0.25', linewidth = 0.5)
m.drawmeridians(meridians,labels=[False,False,False,True])

#plt.show() ##Code works up to here, drawing basemap
#######################################################

#prepare data for contouring
#declare empty arrays for xyz
xarray = []
yarray = []
zarray = []

#get data and pack in the arrays
with open("meansr.txt", "r") as f:
    for line in f:
        (x, y, z, z2, pos) = line.split()
        xarray.append(x)
        yarray.append(y)
        zarray.append(z)
    f.close()

#prepare and grid the data
extent = (min(xarray), max(xarray), min(yarray), max(yarray))
xs,ys = np.mgrid[extent[0]:extent[1]:30j, extent[2]:extent[3]:30j]
z = griddata((xarray, yarray),  zarray, (xs, ys))
x,y = m(xarray,yarray)

#make contour plot
cs = m.contourf(x, y, z)
cs2 = m.contour(x,y,z, levels = range(10,50,5),colors = 'blue')
plt.clabel(cs, fmt = '%.0f', inline = True)
plt.show()

以下是我在轮廓部分得到的错误：

Traceback (most recent call last):
File "./contour12.py", line 44, in <module>
xs,ys = np.mgrid[extent[0]:extent[1]:29j, extent[2]:extent[3]:29j]
File "/home/zmumba/anaconda/lib/python2.7/site-packages/numpy/lib/index_tricks.py", line 185, in __getitem__
step = key.step
AttributeError: 'tuple' object has no attribute 'step'

回溯（最近一次呼叫最后一次）：
文件“/contour12.py”，第44行，在
xs，ys=np.mgrid[extent[0]：extent[1]：29j，extent[2]：extent[3]：29j]
文件“/home/zmumba/anaconda/lib/python2.7/site packages/numpy/lib/index_tricks.py”，第185行，在u getitem中__
步骤=key.step
AttributeError:“元组”对象没有属性“步骤”

---

我不知道30j在上面的代码中应该做什么，虽然我的数据有29个点，但让我们忽略基于地图的部分，只将你的lat长坐标视为笛卡尔坐标系

import numpy as np
import pandas as pd
from matplotlib.mlab import griddata
import matplotlib.pyplot as plt

#-- Read the data.
# I'm going to use `pandas` to read in and work with your data, mostly due to
# the text site names. Using pandas is optional, however.
data = pd.read_csv('your_data.txt', delim_whitespace=True)

#-- Now let's grid your data.
# First we'll make a regular grid to interpolate onto. This is equivalent to
# your call to `mgrid`, but it's broken down a bit to make it easier to
# understand. The "30j" in mgrid refers to 30 rows or columns.
numcols, numrows = 30, 30
xi = np.linspace(data.Lon.min(), data.Lon.max(), numcols)
yi = np.linspace(data.Lat.min(), data.Lat.max(), numrows)
xi, yi = np.meshgrid(xi, yi)

#-- Interpolate at the points in xi, yi
# "griddata" expects "raw" numpy arrays, so we'll pass in
# data.x.values instead of just the pandas series data.x
x, y, z = data.Lon.values, data.Lat.values, data.Z.values
zi = griddata(x, y, z, xi, yi)

#-- Display the results
fig, ax = plt.subplots()
im = ax.contourf(xi, yi, zi)
ax.scatter(data.Lon, data.Lat, c=data.Z, s=100,
           vmin=zi.min(), vmax=zi.max())
fig.colorbar(im)

plt.show()

“块状”边界是由于网格的粗略（30x30）分辨率造成的

griddata

使用三角剖分方法，因此不会对数据点凸包之外的任何内容进行插值。要更清楚地了解这一点，请将numcols和numrows增加到300x300：

---

还可以使用其他几种插值方法（特别是如果希望将插值扩展到数据的凸包之外）

@Kington解决了我的问题，但我想我遗漏了一些东西，因为我得到了“AttributeError:“DataFrame”对象没有属性“Lon”。请原谅我的遗漏，代码工作正常。我遗漏了标题行。请原谅我的无知，我尝试过修改绘图部分，但没有成功，目前我得到了两个单独的绘图（底图和等高线并排。我如何修改“fig，ax=plt.subplot（）”？。此外，作为跟进，是否有办法让等高线填充感兴趣的区域（国家地图）除了国家边界外什么都没有？我知道人们都很忙，我希望有人能抽出一些时间来修改上面的代码，以便覆盖等高线和底图，目前我在合并了底图代码和等高线代码后得到了两个图。我试了很多次，但我目前对python的了解仍然是lac国王。