Python使用2d数组数据绘制轮廓线并找到中心

Question

I was reading a paper named 'Geolocation assessment for CrIS sensor data records', and there was a figure like this

The cost function is defined as the RMSE varying with the number of shifted pixels in the along- and cross-track directions. which means [-5,-5] is the pixel shift 5 steps along left and 5 steps along down from [0,0], and the value of [-5,-5] is a rmse between two dataset, which has been calculated.

I have a similar problem like this, but I have no idea how to plot the image like this, anyone knows?

Edit:

Now I know using pyplot.imshow(rmsedataset,...) could be plot like this, and they look like ellipses, how can I find the center of smallest ellipse(where + is)?

According to the paper. Since each contour line can be treated as a closed ellipse, a fitting ellipse can be found, and the center of the ellipse reflects the minimum of the cost function.

Answer 1

Here is an example using numpy and matplotlib

First we create random numbers between 1500 to 5500 and create a 50 x 100 numpy array , then we simply plott the data that gives a color bar.

Hope this helps.

Demo Code:

import numpy as np
from numpy import array
import matplotlib.pyplot as plt
import random


#Generate a list of 5000 int between 1200,5500
M = 5000
myList = [random.randrange(1200,5500)  for i in xrange(0,M)]

#Convert to 50 x 100 list
n = 50
newList = [myList[i:i+n] for i in range(0, len(myList), n)]

#Convert to 50 x 100 numpy array
nArray = array(newList)
print nArray

a11=nArray.reshape(50,100)
fig = plt.figure()
fig.suptitle('Test Title')
plt.xlabel('X-Axis')
plt.ylabel('Y-Axis')
plt.imshow(a11, cmap='hot')
plt.colorbar()
plt.show()

Plot