Convert 2D table to three 1D arrays in Python

Question

I have data in an nxm 2D table like this:

In my Python code, it looks like this:

import numpy as np

xData = np.array([-225,    -200,   -175])
yData = np.array([0.1,     1.0,    5.0])
zData = np.array([[749.36, 698.96, 471.88],
                  [1012.1, 987.87, 890.69],
                  [1283.9, 1270.1, 1217.1]])

In order to do some curve fitting, I would like to have it in the form of three 1D arrays where each has the size 1 x (nxm) :

xData = np.array([-225,   -225,   -225,   -200,   -200,   -200,   -175,   -175,   -175])
yData = np.array([0.1,    1.0,    5.0,    0.1,    1.0,    5.0,    0.1,    1.0,    5.0])   
zData = np.array([749.36, 698.96, 471.88, 1012.1, 987.87, 890.69, 1283.9, 1270.1, 1217.1])

What is a nice and clean way to achieve this? Note that in general, xData and yData are not evenly spaced.

Answer 1

This should do the trick:

xData = np.repeat(xData, np.shape(zData)[1])
yData = np.tile(yData, np.shape(zData)[0])
zData = np.reshape(zData, (1, np.size(zData)))