使用matplotlib/basemap进行Python插值 [英] Python Interpolation with matplotlib/basemap

问题描述

我对编程还很陌生，并且很难理解插值.我能找到的每个试图解释它的原始资料都是非常神秘的(特别是底图/matplotlib的特定于软件包的站点).我正在使用matplotlib的底图进行映射，但是我的数据的性质是它以5度乘5度的块(纬度块)进来.我想通过插值对地图进行平滑处理.

I am rather new to programming and am having a very hard time understanding interpolation. Every single source I can find that attempts to explain it is extremely cryptic (especially the package specific sites for basemap/matplotlib). I am mapping using matplotlib's basemap however the nature of my data is that it comes in 5 degree by 5 degree blocks (lat lon blocks). I want to smooth out the map by interpolation.

首先，这是我的代码.

So first here is my code.

from netCDF4 import Dataset
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap, addcyclic

#load the netcdf file into a variable
mar120="C:/Users/WillEvo/Desktop/sec_giptie_cpl_mar_120.nc"

#grab the data into a new variable
fh=Dataset(mar120,mode="r")

#assign model variable contents to python variables
lons=fh.variables['lon'][:]
lats=fh.variables['lat'][:]
test=fh.variables['NE'][:]

#specifying which time and elevation to map
ionst=test[12,0]

#close the netCDF file
fh.close()

# get rid of white stripe on map
ionst, lons=addcyclic(ionst, lons)

#map settings
m=Basemap(llcrnrlon=-180, llcrnrlat=-87.5, urcrnrlon=180, urcrnrlat=87.5,rsphere=6467997, resolution='i', projection='cyl',area_thresh=10000, lat_0=0, lon_0=0)

#Creating 2d array of latitude and longitude
lon, lat=np.meshgrid(lons, lats)
xi, yi=m(lon, lat)

#setting plot type and which variable to plot
cs=m.pcolormesh(xi,yi,np.squeeze(ionst))

#drawing grid lines
m.drawparallels(np.arange(-90.,90.,30.),labels=[1,0,0,0],fontsize=10)
m.drawmeridians(np.arange(-180.,181.,30.), labels=[0,0,0,1],fontsize=10)

#drawing coast lines
m.drawcoastlines()

#color bar
cbar=m.colorbar(cs, location='bottom', pad="10%")
cbar.set_label("Elecron Density cm-3")

#showing the plot
plt.show()

那么，现在如何轻松地对数据进行插值以使其平滑?我尝试调用Basemap.interp，但是收到一条错误消息，说该底图没有属性interp.

So now, how can I easily interpolate my data to smooth it out? I have tried to call Basemap.interp however I get an error saying that basemap has no attribute interp.

我真的很公正地使用数据进行插值，我真的很需要别人像我一样愚蠢地向我解释一下.

I am really impartial to what I use to interpolate the data, I just really need someone to explain this to me like I am dumb.

还请注意，我正在学习映射的过程，因此像标签这样的细节，到目前为止还不太担心.下面是上面的代码输出的示例地图.

Also note that I am in the process of learning to map so details like labels and such I am not too worried about as of yet. Below is an example map that the code above outputs.

推荐答案

为了使事情顺利进行，我将使用imshow而不是pcolormesh

To smooth things out I would use imshow rather than pcolormesh

例如:

from pylab import *

data = random((3,3))
figure(1)
imshow(data, interpolation='none')

plt.show()

给出:

和

imshow(data, interpolation='bicubic')

给予:

帮助页面列出了所有可能的插值: http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.imshow

The help page gives a list of all possible interpolations : http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.imshow

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