python - Slicing a 2D array to match entries from a 3D array? -


my task today slice 2d array matches correctly entries in 3d array. example, have 3d array below:

[[[  1.06103295e+02   0.00000000e+00   0.00000000e+00]   [  0.00000000e+00   1.06103295e+02   0.00000000e+00]   [  0.00000000e+00   0.00000000e+00   1.06103295e+02]]   [[  5.09297818e+05   5.09296818e+05   5.09296818e+05]  [  5.09296818e+05   5.09297818e+05   5.09296818e+05]  [  5.09296818e+05   5.09296818e+05   5.09297818e+05]]  [[  5.09297818e+05   5.09296818e+05   5.09296818e+05]  [  5.09296818e+05   5.09297818e+05   5.09296818e+05]  [  5.09296818e+05   5.09296818e+05   5.09297818e+05]]  [[  1.06103295e+02   0.00000000e+00   0.00000000e+00] [  0.00000000e+00   1.06103295e+02   0.00000000e+00] [  0.00000000e+00   0.00000000e+00   1.06103295e+02]]]

using "numpy.reshape" command, changed 2d array dimensions (12, 3). 

[[  1.06103295e+02   0.00000000e+00   0.00000000e+00]  [  0.00000000e+00   1.06103295e+02   0.00000000e+00]  [  0.00000000e+00   0.00000000e+00   1.06103295e+02]  [  5.09297818e+05   5.09296818e+05   5.09296818e+05]  [  5.09296818e+05   5.09297818e+05   5.09296818e+05]  [  5.09296818e+05   5.09296818e+05   5.09297818e+05]  [  5.09297818e+05   5.09296818e+05   5.09296818e+05]  [  5.09296818e+05   5.09297818e+05   5.09296818e+05]  [  5.09296818e+05   5.09296818e+05   5.09297818e+05]  [  1.06103295e+02   0.00000000e+00   0.00000000e+00]  [  0.00000000e+00   1.06103295e+02   0.00000000e+00]  [  0.00000000e+00   0.00000000e+00   1.06103295e+02]]

now how slice entries in same form above?

for example, sliced 1 of entries such:

m11 = myarrayname[0:3, 0:3]

and got result: 

[[ 106.10329539    0.            0.        ]  [   0.          106.10329539    0.        ]  [   0.            0.          106.10329539]]

notice same 1 of blocks 3d array above (minus scientific notation). how keep slicing entries other 3 blocks 3d array above?

when tried m12 = myarrayname[4:6, 4:6],

i got empty array.

you use np.reshape again (if a array):

b = np.reshape(a, (12, 3)) c = np.reshape(b, (4, 3, 3))

but if you'd rather select arrays yourself, then:

m11 = b[0:3, 0:3] m12 = b[3:6, 0:3] m13 = b[6:9, 0:3] m14 = b[9:12, 0:3]

-

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