Extract value from 1x3 numpy array given other two values
I have a 1x3 numpy vector of integers. Given a pair of integers, how can I extract the third integer. Each integer in the numpy vector is unique, and the pair will not include itself (e.g. 3 and 3).
for example:
>>> nodes
array([3, 5, 7], dtype=int16)
>>> n1 = 3
>>> n2 = 7
Given n1, n2, and the 1x3 array, I want the middle value, 5.
numpy
asked Nov 25 '18 at 1:00
EarthIsHomeEarthIsHome
17313
add a comment |
I have a 1x3 numpy vector of integers. Given a pair of integers, how can I extract the third integer. Each integer in the numpy vector is unique, and the pair will not include itself (e.g. 3 and 3).
for example:
>>> nodes
array([3, 5, 7], dtype=int16)
>>> n1 = 3
>>> n2 = 7
Given n1, n2, and the 1x3 array, I want the middle value, 5.
numpy
asked Nov 25 '18 at 1:00
EarthIsHomeEarthIsHome
17313
add a comment |
I have a 1x3 numpy vector of integers. Given a pair of integers, how can I extract the third integer. Each integer in the numpy vector is unique, and the pair will not include itself (e.g. 3 and 3).
for example:
>>> nodes
array([3, 5, 7], dtype=int16)
>>> n1 = 3
>>> n2 = 7
Given n1, n2, and the 1x3 array, I want the middle value, 5.
numpy
asked Nov 25 '18 at 1:00
EarthIsHomeEarthIsHome
17313
I have a 1x3 numpy vector of integers. Given a pair of integers, how can I extract the third integer. Each integer in the numpy vector is unique, and the pair will not include itself (e.g. 3 and 3).
for example:
>>> nodes
array([3, 5, 7], dtype=int16)
>>> n1 = 3
>>> n2 = 7
Given n1, n2, and the 1x3 array, I want the middle value, 5.
numpy
numpy
asked Nov 25 '18 at 1:00
EarthIsHomeEarthIsHome
17313
asked Nov 25 '18 at 1:00
EarthIsHomeEarthIsHome
17313
asked Nov 25 '18 at 1:00
EarthIsHomeEarthIsHome
17313
asked Nov 25 '18 at 1:00
EarthIsHomeEarthIsHome
17313
asked Nov 25 '18 at 1:00
EarthIsHomeEarthIsHome
17313
17313
add a comment |
add a comment |
2 Answers
2
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oldest
votes
Use np.in1d to filter out n1 and n2 from nodes:
nodes[~np.in1d(nodes, [n1, n2])]
# array([5])
answered Nov 25 '18 at 1:03
PsidomPsidom
126k1291136
add a comment |
>>> arr = np.array([3, 5, 7])
>>> n1 = 3
>>> n2 = 7
>>> arr[(arr != n1) & (arr != n2)][0]
5
This works through boolean masking. First exclude values that match the two known values. Since you know there will only be one value left, just take the first element.
answered Nov 25 '18 at 1:40
MannerPotsMannerPots
475
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
Use np.in1d to filter out n1 and n2 from nodes:
nodes[~np.in1d(nodes, [n1, n2])]
# array([5])
answered Nov 25 '18 at 1:03
PsidomPsidom
126k1291136
add a comment |
Use np.in1d to filter out n1 and n2 from nodes:
nodes[~np.in1d(nodes, [n1, n2])]
# array([5])
answered Nov 25 '18 at 1:03
PsidomPsidom
126k1291136
add a comment |
Use np.in1d to filter out n1 and n2 from nodes:
nodes[~np.in1d(nodes, [n1, n2])]
# array([5])
answered Nov 25 '18 at 1:03
PsidomPsidom
126k1291136
Use np.in1d to filter out n1 and n2 from nodes:
nodes[~np.in1d(nodes, [n1, n2])]
# array([5])
answered Nov 25 '18 at 1:03
PsidomPsidom
126k1291136
answered Nov 25 '18 at 1:03
PsidomPsidom
126k1291136
answered Nov 25 '18 at 1:03
PsidomPsidom
126k1291136
answered Nov 25 '18 at 1:03
PsidomPsidom
126k1291136
126k1291136
add a comment |
add a comment |
>>> arr = np.array([3, 5, 7])
>>> n1 = 3
>>> n2 = 7
>>> arr[(arr != n1) & (arr != n2)][0]
5
This works through boolean masking. First exclude values that match the two known values. Since you know there will only be one value left, just take the first element.
answered Nov 25 '18 at 1:40
MannerPotsMannerPots
475
add a comment |
>>> arr = np.array([3, 5, 7])
>>> n1 = 3
>>> n2 = 7
>>> arr[(arr != n1) & (arr != n2)][0]
5
This works through boolean masking. First exclude values that match the two known values. Since you know there will only be one value left, just take the first element.
answered Nov 25 '18 at 1:40
MannerPotsMannerPots
475
add a comment |
>>> arr = np.array([3, 5, 7])
>>> n1 = 3
>>> n2 = 7
>>> arr[(arr != n1) & (arr != n2)][0]
5
This works through boolean masking. First exclude values that match the two known values. Since you know there will only be one value left, just take the first element.
answered Nov 25 '18 at 1:40
MannerPotsMannerPots
475
>>> arr = np.array([3, 5, 7])
>>> n1 = 3
>>> n2 = 7
>>> arr[(arr != n1) & (arr != n2)][0]
5
This works through boolean masking. First exclude values that match the two known values. Since you know there will only be one value left, just take the first element.
answered Nov 25 '18 at 1:40
MannerPotsMannerPots
475
answered Nov 25 '18 at 1:40
MannerPotsMannerPots
475
answered Nov 25 '18 at 1:40
MannerPotsMannerPots
475
answered Nov 25 '18 at 1:40
MannerPotsMannerPots
475
475
add a comment |
add a comment |
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