如何用 Python 改進這個插值結果？

Question

我有這個 XYZ 文本文件（3 列）並且我正在嘗試運行插值，因此我可以創建一個漂亮的顏色模型。 問題是返回的結果沒有正確表示我的數據分布的地形......我的意思是，它的表面並不像我想要的那樣光滑。 底部顏色（紅色）跟隨數據（黑點），但頂部顏色（藍色）不是。 有什么幫助嗎？

我得到的： 我的代碼：

import matplotlib.pyplot as plt
import scipy.interpolate

x,y,z = np.loadtxt("vel_model.txt",usecols=(0,1,2),unpack=True)

x_grid = np.linspace(x.min(),x.max(),100)
y_grid = np.linspace(y.min(),y.max(),100)
xi,yi = np.meshgrid(x_grid,y_grid)
zi = scipy.interpolate.griddata((x, y), z, (xi, yi), method = 'cubic')
fig = plt.figure()
ax = fig.add_subplot(111)
cm = ax.contourf(xi, yi, zi, cmap='jet')
ax.scatter(x,y,color='black',s = 6, label = 'Data points')
ax.set_aspect('equal')
ax.set_xlabel('Distance (m)')
ax.set_ylabel('Elevation (m)')
plt.legend(loc = 'best')
plt.grid(color='grey', linestyle='--', linewidth=0.3)
plt.show()```

Answer 1

按照這個問題讓它工作： Limit/mask matplotlib contour to data area

結果：

編碼：

import numpy as np
import matplotlib.pyplot as plt
import scipy.interpolate
from matplotlib.path import Path
from matplotlib.patches import PathPatch

x,y,z = np.loadtxt("modeloVS_teste.txt",usecols=(0,1,2),unpack=True)
x_grid = np.linspace(x.min(),x.max(),100)
y_grid = np.linspace(y.min(),y.max(),100)
xi,yi = np.meshgrid(x_grid,y_grid)
zi = scipy.interpolate.griddata((x, y), z, (xi, yi), method = 'cubic')
fig = plt.figure()
ax = fig.add_subplot(111)
cm = ax.contourf(xi, yi, zi, cmap='jet')
ax.scatter(x,y,color = 'black',s = 5, label = 'Data points')
ax.set_aspect('equal')
ax.set_xlabel('Distance (m)')
ax.set_ylabel('Elevation (m)')
plt.legend(loc = 'best')
plt.grid(color='grey', linestyle='--', linewidth=0.3)
columns = {}
for i in range(len(x)):
    columns.update({x[i]:[]})
for i in range(len(x)):  
    columns[x[i]].append((y[i]))  
limits = []
for key in columns:
    limits.append((key,max(columns[key])))
limits = limits[::-1]
for key in columns:
    limits.append((key,min(columns[key])))
clippath = Path(limits)
patch = PathPatch(clippath, facecolor='none', alpha = 0)
ax.add_patch(patch)
for c in cm.collections:
    c.set_clip_path(patch)
plt.show()