当从 2d 过渡到 3d 时，z 值似乎映射到不正确的 x 和 y 值

Question

i have a function that calculates az values based on given xy values in space. I am trying to combine all the data together into a 3D grid however i noticed that the z values are not mapping correctly. In other words when print the xyz and perform the calculation as a check in excel I do not get the right z values, but i'm confident my function is calculating correctly. If i check it on an individual basis it gives the result i'm looking for. So i'm pretty sure the z values are getting mapped to the incorrect x,y.

FYI the reason i need the grid together as XYZ is: once i get the function running i need to perform grid math on the resulting grid. For example i need to find certain locations based on a given X and Y and then find nodes that correspond to a certain z value and sum the area of the nodes...etc. I haven't gotten there yet obviously. I'm new to python and working my way there.

What am I doing wrong here? Note I don't get any errors.

Any help is greatly appreciated.

What am i doing wrong?

import pandas as pd
import math
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.tri as tri
import matplotlib.pyplot as plt
from matplotlib import rcParams

#define the flow potential equation where X,Y is the injection well locations and x,y is the point of interest, Q is flow rate
def func(X, Y, x, y, Q):
    return (Q / (2 * np.pi)) * np.arctan((y-Y)/(x-X))

# necessary data
X1=2318743.658
Y1=797346.704
Q1=5
X2=2318690.718
Y2=797343.693
Q2=5
X3=2318715.221
Y3=797309.685
Q3=5

#initiate the XY grid - this will be a standard that will encompass all IW and MW
xi = np.linspace(2318675,2318800,625)
yi = np.linspace(797300,797375,375)

#mesh the grid in to x,y space
x,y = np.meshgrid(xi,yi)

#calculate the valus over the grid at every x,y using the defined function above
zi = (func(X1,Y1,x,y,Q1)+func(X2,Y2,x,y,Q2)+func(X3,Y3,x,y,Q3))

#reshape the xy space into 3d space
xy = np.array([[(x, y) for y in yi] for x in xi])

#reshape z into 3d space
z = np.array(zi).reshape(xy.shape[0],xy.shape[1], -1)

#combined xyz into a single grid
xyz = np.concatenate((xy, z), axis = -1)

Answer 1

I believe I was able to resolve the issue by changing this line of code:

xy = np.array([[(x, y) for y in yi] for x in xi])

to this:

xy = np.array([[(x, y) for x in xi] for y in yi])