How to combine matrices
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I have to combine
NETPLP(:,:,1) =
22 22.45 89.42
22 22.55 114.42
21.95 22.5 114.42
22.55 22.5 -35.59
22 22.55 114.42
22 22.45 89.42
22.05 22.5 89.42
22.45 22.5 -10.59
NETPLP(:,:,2) =
22 22.4 76.92
22 22.6 126.92
21.9 22.5 126.92
22.6 22.5 -48.09
22 22.6 126.92
22 22.4 76.92
22.1 22.5 76.92
22.4 22.5 1.91
NETPLP(:,:,3) =
22 22.35 64.42
22 22.65 139.42
21.85 22.5 139.42
22.65 22.5 -60.59
22 22.65 139.42
22 22.35 64.42
22.15 22.5 64.42
22.35 22.5 14.41
NETPLP(:,:,4) =
22 22.3 51.92
22 22.7 151.92
21.8 22.5 151.92
22.7 22.5 -73.09
22 22.7 151.92
22 22.3 51.92
22.2 22.5 51.92
22.3 22.5 26.92
NETPLP(:,:,5) =
22 22.25 39.42
22 22.75 164.42
21.75 22.5 164.42
22.75 22.5 -85.59
22 22.75 164.42
22 22.25 39.42
22.25 22.5 39.42
22.25 22.5 39.42
NETPLP(:,:,6) =
22 22.2 26.92
22 22.8 176.92
21.7 22.5 176.93
22.8 22.5 -98.09
22 22.8 176.92
22 22.2 26.92
22.3 22.5 26.92
22.2 22.5 51.92
NETPLP(:,:,7) =
22 22.15 14.42
22 22.85 189.42
21.65 22.5 189.43
22.85 22.5 -110.59
22 22.85 189.42
22 22.15 14.42
22.35 22.5 14.41
22.15 22.5 64.42
NETPLP(:,:,8) =
22 22.1 1.92
22 22.9 201.92
21.6 22.5 201.93
22.9 22.5 -123.09
22 22.9 201.92
22 22.1 1.92
22.4 22.5 1.91
22.1 22.5 76.92
NETPLP(:,:,9) =
22 22.05 -10.58
22 22.95 214.42
21.55 22.5 214.43
22.95 22.5 -135.59
22 22.95 214.42
22 22.05 -10.58
22.45 22.5 -10.59
22.05 22.5 89.42
NETPLP(:,:,10) =
22 22 -23.08
22 23 226.92
21.5 22.5 226.93
23 22.5 -148.09
22 23 226.92
22 22 -23.08
22.5 22.5 -23.09
22 22.5 101.92
>> bhu = reshape(NETPLP,[size(NETPLP,1)*size(NETPLP,3),3])
bhu =
22 22.3 14.42
22 22.7 189.42
21.95 22.5 189.43
22.55 22.5 -110.59
22 22.7 189.42
22 22.3 14.42
22.05 22.5 14.41
22.45 22.5 64.42
22.45 51.92 22
22.55 151.92 22
22.5 151.92 21.6
22.5 -73.09 22.9
22.55 151.92 22
22.45 51.92 22
22.5 51.92 22.4
22.5 26.92 22.1
89.42 22 22.1
114.42 22 22.9
114.42 21.75 22.5
-35.59 22.75 22.5
114.42 22 22.9
89.42 22 22.1
89.42 22.25 22.5
-10.59 22.25 22.5
22 22.25 1.92
22 22.75 201.92
21.9 22.5 201.93
22.6 22.5 -123.09
22 22.75 201.92
22 22.25 1.92
22.1 22.5 1.91
22.4 22.5 76.92
22.4 39.42 22
22.6 164.42 22
22.5 164.42 21.55
22.5 -85.59 22.95
22.6 164.42 22
22.4 39.42 22
22.5 39.42 22.45
22.5 39.42 22.05
76.92 22 22.05
126.92 22 22.95
126.92 21.7 22.5
-48.09 22.8 22.5
126.92 22 22.95
76.92 22 22.05
76.92 22.3 22.5
1.91 22.2 22.5
22 22.2 -10.58
22 22.8 214.42
21.85 22.5 214.43
22.65 22.5 -135.59
22 22.8 214.42
22 22.2 -10.58
22.15 22.5 -10.59
22.35 22.5 89.42
22.35 26.92 22
22.65 176.92 22
22.5 176.93 21.5
22.5 -98.09 23
22.65 176.92 22
22.35 26.92 22
22.5 26.92 22.5
22.5 51.92 22
64.42 22 22
139.42 22 23
139.42 21.65 22.5
-60.59 22.85 22.5
139.42 22 23
64.42 22 22
64.42 22.35 22.5
14.41 22.15 22.5
22 22.15 -23.08
22 22.85 226.92
21.8 22.5 226.93
22.7 22.5 -148.09
22 22.85 226.92
22 22.15 -23.08
22.2 22.5 -23.09
22.3 22.5 101.92
this matrix, but location is not appropriate. please help me for uniformity.
2 comentarios
Simon Chan
el 19 de Ag. de 2021
What is the expected size of the combined matrix?
Triveni
el 19 de Ag. de 2021
Respuesta aceptada
Más respuestas (1)
Jan
el 19 de Ag. de 2021
permute(reshape(permute(NETPLP, [2, 1, 3]), 4, []), [2, 1])
All reshaping operations of N-dimensional arrays can be solved by this approach: permute(reshape(permute(x))).
In this case permute(Y, [ 2, 1]) can be abbreviated to Y.'
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