You should be able to construct a 3D array from your existing temp 1D array as follows:
zz = np.arange(-200,0.1,2.5)
def grid_function(x, ABath=-0.2, BBath=0.1, CBath=50.,DBath=10.):
"""This function creates a theoretical grid"""
from numpy import tanh, arange
ans = ABath * (tanh(BBath * (-x - CBath))) + DBath
return ans
temp = grid_function(zz)
# Construct 1D 100-element array with z-coordinates
z_new = np.linspace(zz[0], zz[-1], 100)
# Interpolate 1D temperatures at new set of 100 z-coordinates
temp_1d_new = np.interp(z_new, zz, temp)
# Replicate 1D temperatures into two additional dimensions
temp_3d_new = np.tile(temp_1d_new, (6, 599, 1))
You could also take a more direct approach however and start immediately with a z-coordinates 1D array with the desired 100 elements (i.e. skip the interpolation step). Like so:
def grid_function(x, ABath=-0.2, BBath=0.1, CBath=50.,DBath=10.):
"""This function creates a theoretical grid"""
from numpy import tanh, arange
ans = ABath * (tanh(BBath * (-x - CBath))) + DBath
return ans
# Create 1D arrays with x-coordinates, y-coordinates and z-coordinates
x = np.linspace(0., 100., 6)
y = np.linspace(0., 100., 599)
z = np.linspace(-200., 0., 100)
# Create 3D meshgrids for x-coordinates, y-coordinates and z-coordinates
(xx, yy, zz) = np.meshgrid(x, y, z)
# Calculate temperatures 3D array from z-coordinates 3D array
temp = grid_function(zz)
Side note
It's considered good practice to place import statements always at the top of your code file.
