什么可能导致SciPy中不正确的2D插值？

Question

我有一个数据（x，y，V）的直线（非规则）网格，其中V是位置（x，y）处的值。我想使用这个数据源来插值我的结果，这样我就可以在将来填补空白并绘制插值（在范围内）。（我还需要griddata的功能来检查范围内的任意值）

我查看了SciPy和here的文档。 以下是我尝试的结果：

It clearly doesn't match the data.

# INTERPOLATION ATTEMPT?
from scipy.interpolate import Rbf
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm

edges = np.linspace(-0.05, 0.05, 100)
centers = edges[:-1] + np.diff(edges[:2])[0] / 2.
XI, YI = np.meshgrid(centers, centers)

# use RBF
rbf = Rbf(x, y, z, epsilon=2)
ZI = rbf(XI, YI)

# plot the result
plt.subplots(1,figsize=(12,8))
X_edges, Y_edges = np.meshgrid(edges, edges)
lims = dict(cmap='viridis')
plt.pcolormesh(X_edges, Y_edges, ZI, shading='flat', **lims)
plt.scatter(x, y, 200, z, edgecolor='w', lw=0.1, **lims)

#decoration
plt.title('RBF interpolation?')
plt.xlim(-0.05, 0.05)
plt.ylim(-0.05, 0.05)
plt.colorbar()
plt.show()

作为参考，这里是我的数据（提取），它有一个圆形图案，我需要插值来识别

#DATA
experiment1raw = np.array([
[0,40,1,11.08,8.53,78.10,2.29],
[24,-32,2,16.52,11.09,69.03,3.37],
[8,-32,4,14.27,10.68,71.86,3.19],
[-8,-32,6,10.86,9.74,76.69,2.72], 
[-24,-32,8,6.72,12.74,77.08,3.45],
[32,-24,9,18.49,13.67,64.32,3.52],
[-32,-24,17,6.72,12.74,77.08,3.45],
[16,-16,20,13.41,21.33,59.92,5.34],
[0,-16,22,12.16,14.67,69.04,4.12],
[-16,-16,24,9.07,13.37,74.20,3.36],
[32,-8,27,19.35,17.88,57.86,4.91],
[-32,-8,35,6.72,12.74,77.08,3.45],
[40,0,36,19.25,20.36,54.97,5.42],
[16,0,39,13.41,21.33,59.952,5.34],
[0,0,41,10.81,19.55,64.37,5.27],
[-16,0,43,8.21,17.83,69.34,4.62],
[-40,0,46,5.76,13.43,77.23,3.59],
[32,8,47,15.95,23.61,54.34,6.10],
[-32,8,55,5.97,19.09,70.19,4.75],
[16,16,58,11.27,26.03,56.36,6.34],
[0,16,60,9.19,24.94,60.06,5.79],
[-16,16,62,7.10,22.75,64.57,5.58],
[32,24,65,12.39,29.19,51.17,7.26],
[-32,24,73,5.40,24.55,64.33,5.72],
[24,32,74,10.03,31.28,50.96,7.73],
[8,32,76,8.68,30.06,54.34,6.92],
[-8,32,78,6.88,28.78,57.84,6.49],
[-24,32,80,5.83,26.70,61.00,6.46],
[0,-40,81,7.03,31.55,54.40,7.01],
])

#Atomic Percentages are set here
Cr1 = experiment1raw[:,3]
Mn1 = experiment1raw[:,4]
Fe1 = experiment1raw[:,5]
Co1 = experiment1raw[:,6]

#COORDINATE VALUES IN PRE-T
x_pret = experiment1raw[:,0]/1000
y_pret = experiment1raw[:,1]/1000

#important translation
x = -y_pret
y = -x_pret
z = Cr1

Answer 1

您在RBF中使用了较大的epsilon。最好的办法是将其设置为默认值，并让scipy计算适当的值。请参阅实现here

因此，设置默认值epsilon：

rbf = Rbf(x, y, z)

我对你的数据做了很好的插值（主观意见）。