python: how to create submatrices? Numpy
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I have a matrix 1500X2, and I have to create 10 submatrices of 150 rows. How can i do this without for loop. I need a function, because with the [:] is too slow and complicated
python matrix
edited Nov 22 at 21:35
Roman Pokrovskij
4,25664978
asked Nov 22 at 14:35
Ari
12
add a comment |
up vote
-1
down vote
favorite
I have a matrix 1500X2, and I have to create 10 submatrices of 150 rows. How can i do this without for loop. I need a function, because with the [:] is too slow and complicated
python matrix
edited Nov 22 at 21:35
Roman Pokrovskij
4,25664978
asked Nov 22 at 14:35
Ari
12
3
Why not show a Minimal, Complete, and Verifiable example and some benchmarks that show what is slow?
– jdv
Nov 22 at 16:58
add a comment |
up vote
-1
down vote
favorite
up vote
-1
down vote
favorite
I have a matrix 1500X2, and I have to create 10 submatrices of 150 rows. How can i do this without for loop. I need a function, because with the [:] is too slow and complicated
python matrix
edited Nov 22 at 21:35
Roman Pokrovskij
4,25664978
asked Nov 22 at 14:35
Ari
12
I have a matrix 1500X2, and I have to create 10 submatrices of 150 rows. How can i do this without for loop. I need a function, because with the [:] is too slow and complicated
python matrix
python matrix
edited Nov 22 at 21:35
Roman Pokrovskij
4,25664978
asked Nov 22 at 14:35
Ari
12
edited Nov 22 at 21:35
Roman Pokrovskij
4,25664978
asked Nov 22 at 14:35
Ari
12
edited Nov 22 at 21:35
Roman Pokrovskij
4,25664978
edited Nov 22 at 21:35
Roman Pokrovskij
4,25664978
edited Nov 22 at 21:35
Roman Pokrovskij
4,25664978
4,25664978
asked Nov 22 at 14:35
Ari
12
asked Nov 22 at 14:35
Ari
12
asked Nov 22 at 14:35
Ari
12
12
3
Why not show a Minimal, Complete, and Verifiable example and some benchmarks that show what is slow?
– jdv
Nov 22 at 16:58
add a comment |
3
Why not show a Minimal, Complete, and Verifiable example and some benchmarks that show what is slow?
– jdv
Nov 22 at 16:58
3
3
Why not show a Minimal, Complete, and Verifiable example and some benchmarks that show what is slow?
– jdv
Nov 22 at 16:58
Why not show a Minimal, Complete, and Verifiable example and some benchmarks that show what is slow?
– jdv
Nov 22 at 16:58
add a comment |
1 Answer
1
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oldest
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up vote
0
down vote
You could use the numpy.take function to select a range of rows of your matrix. You can pass the indices you want to select and the axis over which you want to select your items.
import numpy as np
indices = list(range(0,3))
array = np.random.rand(5,2)
print(array)
res = np.take(array, indices, 0)
print(res)
You get something like this:
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]
[0.98148503 0.5669895 ]
[0.42720908 0.57326236]]
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]]
answered Nov 22 at 14:50
user10455554
17817
add a comment |
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1 Answer
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active
oldest
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
You could use the numpy.take function to select a range of rows of your matrix. You can pass the indices you want to select and the axis over which you want to select your items.
import numpy as np
indices = list(range(0,3))
array = np.random.rand(5,2)
print(array)
res = np.take(array, indices, 0)
print(res)
You get something like this:
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]
[0.98148503 0.5669895 ]
[0.42720908 0.57326236]]
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]]
answered Nov 22 at 14:50
user10455554
17817
add a comment |
up vote
0
down vote
You could use the numpy.take function to select a range of rows of your matrix. You can pass the indices you want to select and the axis over which you want to select your items.
import numpy as np
indices = list(range(0,3))
array = np.random.rand(5,2)
print(array)
res = np.take(array, indices, 0)
print(res)
You get something like this:
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]
[0.98148503 0.5669895 ]
[0.42720908 0.57326236]]
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]]
answered Nov 22 at 14:50
user10455554
17817
add a comment |
up vote
0
down vote
up vote
0
down vote
You could use the numpy.take function to select a range of rows of your matrix. You can pass the indices you want to select and the axis over which you want to select your items.
import numpy as np
indices = list(range(0,3))
array = np.random.rand(5,2)
print(array)
res = np.take(array, indices, 0)
print(res)
You get something like this:
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]
[0.98148503 0.5669895 ]
[0.42720908 0.57326236]]
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]]
answered Nov 22 at 14:50
user10455554
17817
You could use the numpy.take function to select a range of rows of your matrix. You can pass the indices you want to select and the axis over which you want to select your items.
import numpy as np
indices = list(range(0,3))
array = np.random.rand(5,2)
print(array)
res = np.take(array, indices, 0)
print(res)
You get something like this:
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]
[0.98148503 0.5669895 ]
[0.42720908 0.57326236]]
[[0.63680493 0.27066094]
[0.71182288 0.48258969]
[0.61321531 0.02215374]]
answered Nov 22 at 14:50
user10455554
17817
answered Nov 22 at 14:50
user10455554
17817
answered Nov 22 at 14:50
user10455554
17817
answered Nov 22 at 14:50
user10455554
17817
17817
add a comment |
add a comment |
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3
Why not show a Minimal, Complete, and Verifiable example and some benchmarks that show what is slow?
– jdv
Nov 22 at 16:58