如何从matplotlib中的x，y，z坐标绘制等高线图？ （plt.contourf或plt.contour）

Question

这些meshgrid对我来说有点令人困惑。我正在尝试使用x和y坐标绘制散点图，并在散点图上覆盖轮廓图，并连续分布z坐标。类似于立面图。

如果我将meshgrid与x，y和z坐标一起使用，那么我得到的3D数组仍然是错误的输入。

df_xyz = pd.read_table("https://pastebin.com/raw/f87krHFK", sep="\t", index_col=0)
x = df_xyz.iloc[:,0].values
y = df_xyz.iloc[:,1].values
z = df_xyz.iloc[:,2].values

XX, YY = np.meshgrid(x,y)
with plt.style.context("seaborn-white"):
    fig, ax = plt.subplots(figsize=(13,8))
    ax.scatter(x,y, color="black", linewidth=1, edgecolor="ivory", s=50)
    ax.contourf(XX,YY,z)
#     TypeError: Input z must be a 2D array.

XX, YY, ZZ = np.meshgrid(x,y,z)
with plt.style.context("seaborn-white"):
    fig, ax = plt.subplots(figsize=(13,8))
    ax.scatter(x,y, color="black", linewidth=1, edgecolor="ivory", s=50)
    ax.contourf(XX,YY,ZZ)
#     TypeError: Input z must be a 2D array.

这是我当前的输出：

我正在尝试执行以下操作：

Answer 1

import pandas as pd
import numpy as np
from scipy.interpolate import griddata
import matplotlib.pyplot as plt
%matplotlib inline

df_xyz = pd.read_table("https://pastebin.com/raw/f87krHFK", sep="\t", index_col=0)
x = df_xyz.iloc[:,0].values
y = df_xyz.iloc[:,1].values
z = df_xyz.iloc[:,2].values

def plot_contour(x,y,z,resolution = 50,contour_method='linear'):
    resolution = str(resolution)+'j'
    X,Y = np.mgrid[min(x):max(x):complex(resolution),   min(y):max(y):complex(resolution)]
    points = [[a,b] for a,b in zip(x,y)]
    Z = griddata(points, z, (X, Y), method=contour_method)
    return X,Y,Z

X,Y,Z = plot_contour(x,y,z,resolution = 50,contour_method='linear')

with plt.style.context("seaborn-white"):
    fig, ax = plt.subplots(figsize=(13,8))
    ax.scatter(x,y, color="black", linewidth=1, edgecolor="ivory", s=50)
    ax.contourf(X,Y,Z)