Numpy question regarding accessing elements
So I have created an array from 3 nested lists (atleast I think it is an array from 3 lists), and I want to access the three diagonal elements in it. I have the array created, but how do I access the three diagonal elements in it?
from numpy import *
test1 = arange(27).reshape(3,3,3)
test1
Result:
array([[[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8]],
[[ 9, 10, 11],
[12, 13, 14],
[15, 16, 17]],
[[18, 19, 20],
[21, 22, 23],
[24, 25, 26]]])
python numpy
asked Nov 22 '18 at 1:58
blarghblargh
63
add a comment |
So I have created an array from 3 nested lists (atleast I think it is an array from 3 lists), and I want to access the three diagonal elements in it. I have the array created, but how do I access the three diagonal elements in it?
from numpy import *
test1 = arange(27).reshape(3,3,3)
test1
Result:
array([[[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8]],
[[ 9, 10, 11],
[12, 13, 14],
[15, 16, 17]],
[[18, 19, 20],
[21, 22, 23],
[24, 25, 26]]])
python numpy
asked Nov 22 '18 at 1:58
blarghblargh
63
add a comment |
So I have created an array from 3 nested lists (atleast I think it is an array from 3 lists), and I want to access the three diagonal elements in it. I have the array created, but how do I access the three diagonal elements in it?
from numpy import *
test1 = arange(27).reshape(3,3,3)
test1
Result:
array([[[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8]],
[[ 9, 10, 11],
[12, 13, 14],
[15, 16, 17]],
[[18, 19, 20],
[21, 22, 23],
[24, 25, 26]]])
python numpy
asked Nov 22 '18 at 1:58
blarghblargh
63
So I have created an array from 3 nested lists (atleast I think it is an array from 3 lists), and I want to access the three diagonal elements in it. I have the array created, but how do I access the three diagonal elements in it?
from numpy import *
test1 = arange(27).reshape(3,3,3)
test1
Result:
array([[[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8]],
[[ 9, 10, 11],
[12, 13, 14],
[15, 16, 17]],
[[18, 19, 20],
[21, 22, 23],
[24, 25, 26]]])
python numpy
python numpy
asked Nov 22 '18 at 1:58
blarghblargh
63
asked Nov 22 '18 at 1:58
blarghblargh
63
edited Nov 22 '18 at 2:24
blargh
asked Nov 22 '18 at 1:58
blarghblargh
63
asked Nov 22 '18 at 1:58
blarghblargh
63
asked Nov 22 '18 at 1:58
blarghblargh
63
63
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
Here is a list comprehension approach:
>>> [np.diagonal(i) for i in test1]
[array([0, 4, 8]), array([ 9, 13, 17]), array([18, 22, 26])]
answered Nov 22 '18 at 2:10
Siong Thye GohSiong Thye Goh
908412
Sorry I had to re edit my code, and the np.diag(test1) does not work now : (
– blargh
Nov 22 '18 at 2:24
add a comment |
There are several ways to achieve your goal. Here, I will highlight the use of a boolean mask.
First create the boolean 3x3 identity matrix : i.e. the diagonal is True whilst 2. every off diagonal entry is False.
Then overlay the boolean mask over your original ndarray to get the diagonals.
import numpy as np
test1 = np.arange(27).reshape(3,3,3)
>>> diag = np.eye(3, dtype=bool)
>>> test1[:, diag]
array([[ 0, 4, 8],
[ 9, 13, 17],
[18, 22, 26]])
As you can see, this gives a 2d array where each row is the corresponding diagonal of the zeroth, first and second
2d array in your 3d array.
As an aside, avoid import *, it is the cause of many a headache because if destroys the namespace abstraction you
have. In the above example, what if numpy had a diag function or variable defined? same if you import another package after numpy and it happens to have it's own arange function, you will looes numpy's arange function.
Prefer explicit imports to star imports.
answered Nov 22 '18 at 3:06
Xero SmithXero Smith
8861514
I see! Thank you and I will def keep the asterisk in mind. I have a follow up question, what is a constant array?
– blargh
Nov 22 '18 at 3:39
Please accept the solution if it answers your question. A constant array is an array that is constant i.e. in a mathematical context it can be an array of coefficients where the coefficients are constant.
– Xero Smith
Nov 22 '18 at 3:46
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
Here is a list comprehension approach:
>>> [np.diagonal(i) for i in test1]
[array([0, 4, 8]), array([ 9, 13, 17]), array([18, 22, 26])]
answered Nov 22 '18 at 2:10
Siong Thye GohSiong Thye Goh
908412
Sorry I had to re edit my code, and the np.diag(test1) does not work now : (
– blargh
Nov 22 '18 at 2:24
add a comment |
Here is a list comprehension approach:
>>> [np.diagonal(i) for i in test1]
[array([0, 4, 8]), array([ 9, 13, 17]), array([18, 22, 26])]
answered Nov 22 '18 at 2:10
Siong Thye GohSiong Thye Goh
908412
Sorry I had to re edit my code, and the np.diag(test1) does not work now : (
– blargh
Nov 22 '18 at 2:24
add a comment |
Here is a list comprehension approach:
>>> [np.diagonal(i) for i in test1]
[array([0, 4, 8]), array([ 9, 13, 17]), array([18, 22, 26])]
answered Nov 22 '18 at 2:10
Siong Thye GohSiong Thye Goh
908412
Here is a list comprehension approach:
>>> [np.diagonal(i) for i in test1]
[array([0, 4, 8]), array([ 9, 13, 17]), array([18, 22, 26])]
answered Nov 22 '18 at 2:10
Siong Thye GohSiong Thye Goh
908412
edited Nov 22 '18 at 2:43
answered Nov 22 '18 at 2:10
Siong Thye GohSiong Thye Goh
908412
answered Nov 22 '18 at 2:10
Siong Thye GohSiong Thye Goh
908412
answered Nov 22 '18 at 2:10
Siong Thye GohSiong Thye Goh
908412
908412
Sorry I had to re edit my code, and the np.diag(test1) does not work now : (
– blargh
Nov 22 '18 at 2:24
add a comment |
Sorry I had to re edit my code, and the np.diag(test1) does not work now : (
– blargh
Nov 22 '18 at 2:24
Sorry I had to re edit my code, and the np.diag(test1) does not work now : (
– blargh
Nov 22 '18 at 2:24
Sorry I had to re edit my code, and the np.diag(test1) does not work now : (
– blargh
Nov 22 '18 at 2:24
add a comment |
There are several ways to achieve your goal. Here, I will highlight the use of a boolean mask.
First create the boolean 3x3 identity matrix : i.e. the diagonal is True whilst 2. every off diagonal entry is False.
Then overlay the boolean mask over your original ndarray to get the diagonals.
import numpy as np
test1 = np.arange(27).reshape(3,3,3)
>>> diag = np.eye(3, dtype=bool)
>>> test1[:, diag]
array([[ 0, 4, 8],
[ 9, 13, 17],
[18, 22, 26]])
As you can see, this gives a 2d array where each row is the corresponding diagonal of the zeroth, first and second
2d array in your 3d array.
As an aside, avoid import *, it is the cause of many a headache because if destroys the namespace abstraction you
have. In the above example, what if numpy had a diag function or variable defined? same if you import another package after numpy and it happens to have it's own arange function, you will looes numpy's arange function.
Prefer explicit imports to star imports.
answered Nov 22 '18 at 3:06
Xero SmithXero Smith
8861514
I see! Thank you and I will def keep the asterisk in mind. I have a follow up question, what is a constant array?
– blargh
Nov 22 '18 at 3:39
Please accept the solution if it answers your question. A constant array is an array that is constant i.e. in a mathematical context it can be an array of coefficients where the coefficients are constant.
– Xero Smith
Nov 22 '18 at 3:46
add a comment |
There are several ways to achieve your goal. Here, I will highlight the use of a boolean mask.
First create the boolean 3x3 identity matrix : i.e. the diagonal is True whilst 2. every off diagonal entry is False.
Then overlay the boolean mask over your original ndarray to get the diagonals.
import numpy as np
test1 = np.arange(27).reshape(3,3,3)
>>> diag = np.eye(3, dtype=bool)
>>> test1[:, diag]
array([[ 0, 4, 8],
[ 9, 13, 17],
[18, 22, 26]])
As you can see, this gives a 2d array where each row is the corresponding diagonal of the zeroth, first and second
2d array in your 3d array.
As an aside, avoid import *, it is the cause of many a headache because if destroys the namespace abstraction you
have. In the above example, what if numpy had a diag function or variable defined? same if you import another package after numpy and it happens to have it's own arange function, you will looes numpy's arange function.
Prefer explicit imports to star imports.
answered Nov 22 '18 at 3:06
Xero SmithXero Smith
8861514
I see! Thank you and I will def keep the asterisk in mind. I have a follow up question, what is a constant array?
– blargh
Nov 22 '18 at 3:39
Please accept the solution if it answers your question. A constant array is an array that is constant i.e. in a mathematical context it can be an array of coefficients where the coefficients are constant.
– Xero Smith
Nov 22 '18 at 3:46
add a comment |
There are several ways to achieve your goal. Here, I will highlight the use of a boolean mask.
First create the boolean 3x3 identity matrix : i.e. the diagonal is True whilst 2. every off diagonal entry is False.
Then overlay the boolean mask over your original ndarray to get the diagonals.
import numpy as np
test1 = np.arange(27).reshape(3,3,3)
>>> diag = np.eye(3, dtype=bool)
>>> test1[:, diag]
array([[ 0, 4, 8],
[ 9, 13, 17],
[18, 22, 26]])
As you can see, this gives a 2d array where each row is the corresponding diagonal of the zeroth, first and second
2d array in your 3d array.
As an aside, avoid import *, it is the cause of many a headache because if destroys the namespace abstraction you
have. In the above example, what if numpy had a diag function or variable defined? same if you import another package after numpy and it happens to have it's own arange function, you will looes numpy's arange function.
Prefer explicit imports to star imports.
answered Nov 22 '18 at 3:06
Xero SmithXero Smith
8861514
There are several ways to achieve your goal. Here, I will highlight the use of a boolean mask.
First create the boolean 3x3 identity matrix : i.e. the diagonal is True whilst 2. every off diagonal entry is False.
Then overlay the boolean mask over your original ndarray to get the diagonals.
import numpy as np
test1 = np.arange(27).reshape(3,3,3)
>>> diag = np.eye(3, dtype=bool)
>>> test1[:, diag]
array([[ 0, 4, 8],
[ 9, 13, 17],
[18, 22, 26]])
As you can see, this gives a 2d array where each row is the corresponding diagonal of the zeroth, first and second
2d array in your 3d array.
As an aside, avoid import *, it is the cause of many a headache because if destroys the namespace abstraction you
have. In the above example, what if numpy had a diag function or variable defined? same if you import another package after numpy and it happens to have it's own arange function, you will looes numpy's arange function.
Prefer explicit imports to star imports.
answered Nov 22 '18 at 3:06
Xero SmithXero Smith
8861514
answered Nov 22 '18 at 3:06
Xero SmithXero Smith
8861514
answered Nov 22 '18 at 3:06
Xero SmithXero Smith
8861514
answered Nov 22 '18 at 3:06
Xero SmithXero Smith
8861514
8861514
I see! Thank you and I will def keep the asterisk in mind. I have a follow up question, what is a constant array?
– blargh
Nov 22 '18 at 3:39
Please accept the solution if it answers your question. A constant array is an array that is constant i.e. in a mathematical context it can be an array of coefficients where the coefficients are constant.
– Xero Smith
Nov 22 '18 at 3:46
add a comment |
I see! Thank you and I will def keep the asterisk in mind. I have a follow up question, what is a constant array?
– blargh
Nov 22 '18 at 3:39
Please accept the solution if it answers your question. A constant array is an array that is constant i.e. in a mathematical context it can be an array of coefficients where the coefficients are constant.
– Xero Smith
Nov 22 '18 at 3:46
I see! Thank you and I will def keep the asterisk in mind. I have a follow up question, what is a constant array?
– blargh
Nov 22 '18 at 3:39
I see! Thank you and I will def keep the asterisk in mind. I have a follow up question, what is a constant array?
– blargh
Nov 22 '18 at 3:39
Please accept the solution if it answers your question. A constant array is an array that is constant i.e. in a mathematical context it can be an array of coefficients where the coefficients are constant.
– Xero Smith
Nov 22 '18 at 3:46
Please accept the solution if it answers your question. A constant array is an array that is constant i.e. in a mathematical context it can be an array of coefficients where the coefficients are constant.
– Xero Smith
Nov 22 '18 at 3:46
add a comment |
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