更新的进度在2D散点图/轮廓图上显示Z轴数据Python

如何解决更新的进度在2D散点图/轮廓图上显示Z轴数据Python

大家晚上好

我已经取得了一些进步，但是更多的是“向前迈出，向后迈出两步”类型的事情。

我已经在分散/等高线图(matplotlib)上绘制了钻井数据。散点图显示了每个钻孔的位置，而等高线图则插入了一条古老河流的基岩标高。

问题是我无法在注释弹出窗口上显示基岩高程值（z轴）数据。用mplcursors构造的注释显示轮廓的行号，但不显示用于构造基岩高程的插值z值。

我认为，通过输入zi值（从zi = interpolator(Xi,Yi)生成的mask.array），可以将z值显示为基岩标高，而不是等高线号。

肯定有我缺少的东西。知道为什么这行不通吗？

这是我当前的输出：

"""
# -----------------------
# Import libraries
# -----------------------
"""


import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
import pandas as pd
from mpldatacursor import datacursor
import mplcursors


"""
# -----------------------
# Access and extract data from spreadsheet
# -----------------------
"""

# access csv and assign as a variable
dataset = pd.read_csv('Stoffdraai.csv')

# x_axis values extracted and converted to a list from the csv
x = list(dataset["Easting"])

# y_axis values extracted and converted to a list from the csv
y = list(dataset["Northing"])

# z_axis values extracted and converted to a list from the csv
z = list(dataset["Bdr_Elevat"])


ngridx = 1000
ngridy = 2000


fig,(ax1) = plt.subplots()

"""
# -----------------------
# Interpolation on a grid
# -----------------------
# A contour plot of irregularly spaced data coordinates
# via interpolation on a grid.
"""

# Create grid values first.
xi = np.linspace(-2.1,2.1,ngridx)
yi = np.linspace(-2.1,ngridy)

# Linearly interpolate the data (x,y) on a grid defined by (xi,yi).
triang = tri.Triangulation(x,y)
interpolator = tri.LinearTriInterpolator(triang,z)
Xi,Yi = np.meshgrid(xi,yi)
zi = interpolator(Xi,Yi)

"""
# ----------
# Tricontour
# ----------
"""

cf = ax1.tricontour(x,y,z,levels=36,linewidths=0.25,colors='k') #
cntr2 = ax1.tricontourf(x,cmap="terrain")  # Colour Bar has colour scheme RdBu_r


"""
# ----------
# Plot Setup
# ----------
"""


fig.colorbar(cntr2,ax=ax1)
ax1.set_title('Bedrock Elevation')
ax1.plot(x,'ko',ms=1.5)
ax1.set(xlim=(min(x) - 100,max(x) + 100),ylim=(min(y) - 100,max(y) + 100))  # Sets up the grid



  # Superficial Graph Formatting

ax1.set_title('Bedrock Elevation')  # Defines the plot name
plt.ylabel('Northing')   # y axis label
plt.xlabel('Easting')   # x axis label
ax1.ticklabel_format(useOffset=False,style='plain')
plt.subplots_adjust(hspace=1)



"""
# ----------
# Map cursor
# ----------
Map cursor currently displays x and y axis values on the drill holes and the interpolated contour lines
Uses mpldatacursors


"""

cursor = mplcursors.cursor()


  #The function below appears to extract the z value,not from the interpolated z values,the number of contour lines.

@cursor.connect("add")
def on_add(sel):
    ann = sel.annotation.
    ann.set_text("{}\nBedrock Elevation={:.0f}".format(
        ann.get_text(),cf.cvalues[cf.collections.index(sel.artist)]))


plt.show()