sample 2D positions into an gridded array in numpy

Question

I'm looking for an approach to parse xy positional information (mesh centers) into a numpy array to extract the column row information for each xy position. z is object name (or could be a reference to FbxMesh)

[
    [1782.6000366210938, 336.4900026321411, u'5_07_05'],
    [2397.0, -1506.7100219726562, u'5_08_08'],
    [3011.4000244140625, -277.9100217819214, u'5_09_06'],
    [3011.4000244140625, 336.4900026321411, u'5_09_05'], 
    [2397.0, -277.9099597930908, u'5_08_06'],
    [2397.0, 336.4900026321411, u'5_08_05'],
    [1782.6000366210938, -1506.7100219726562, u'5_07_08'], 
    [2397.0, -892.3099975585938, u'5_08_07'], 
    [1782.6000366210938, -892.3099975585938, u'5_07_07'],
    [3011.4000244140625, -1506.7100219726562, u'5_09_08'],
    [1782.6000366210938, -277.90999126434326, u'5_07_06'], 
    [3011.4000244140625, -892.3099975585938, u'5_09_07']
]

The idea would be to reshape the array above into a correctly shaped array from the lowest value on the bottom left to the highest on the top right.. then sample the column and row index of each item [0,0] [0,1] etc.. and then export the mesh with an appropriate name.. cheers

Update:

I can sort that above list sorted_array = sorted(unsorted_array,key=lambda x: (x[0],x[1]))

[1782.6000366210938, -1506.7100219726562, u'5_07_08']
[1782.6000366210938, -892.3099975585938, u'5_07_07']
[1782.6000366210938, -277.90999126434326, u'5_07_06']
[1782.6000366210938, 336.4900026321411, u'5_07_05']
[2397.0, -1506.7100219726562, u'5_08_08']
[2397.0, -892.3099975585938, u'5_08_07']
[2397.0, -277.9099597930908, u'5_08_06']
[2397.0, 336.4900026321411, u'5_08_05']
[3011.4000244140625, -1506.7100219726562, u'5_09_08']
[3011.4000244140625, -892.3099975585938, u'5_09_07']
[3011.4000244140625, -277.9100217819214, u'5_09_06']
[3011.4000244140625, 336.4900026321411, u'5_09_05']

format [X, Y, 'name']

I'd like to arrange this into a grid and then transpose , for example

After this the idea is to read out each grid cells index and the name in the array eg tile_X0_Y0 etc..

Answer 1

Just play with the axes of the transpose and flip commands.

import numpy as np

a=np.array([[[9,8],[9,7],[9,6],[9,5]],
            [[8,8],[8,7],[8,6],[8,5]],
            [[7,8],[7,7],[7,6],[7,5]]])

b=np.transpose(a,axes=[1,0,2])
c=np.flip(b,axis=1)
d=np.flip(c,axis=0)

print(a)

print('******')
print(b)
print('*****')
print(c)
print('*****')
print(d)

output:

[[[9 8]
  [9 7]
  [9 6]
  [9 5]]

 [[8 8]
  [8 7]
  [8 6]
  [8 5]]

 [[7 8]
  [7 7]
  [7 6]
  [7 5]]]
******
[[[9 8]
  [8 8]
  [7 8]]

 [[9 7]
  [8 7]
  [7 7]]

 [[9 6]
  [8 6]
  [7 6]]

 [[9 5]
  [8 5]
  [7 5]]]
*****
[[[7 8]
  [8 8]
  [9 8]]

 [[7 7]
  [8 7]
  [9 7]]

 [[7 6]
  [8 6]
  [9 6]]

 [[7 5]
  [8 5]
  [9 5]]]
*****
[[[7 5]
  [8 5]
  [9 5]]

 [[7 6]
  [8 6]
  [9 6]]

 [[7 7]
  [8 7]
  [9 7]]

 [[7 8]
  [8 8]
  [9 8]]]