Can I apply exp function directly on a list or matrix?
up vote
-2
down vote
favorite
Can I raise a list to the power of e Like
np.exp(L)
instead of using a for loop for every single element? And does it apply to Arrays and Matrices too?
python exponential
asked Nov 12 at 10:46
Fariman Kashani
3928
add a comment |
up vote
-2
down vote
favorite
Can I raise a list to the power of e Like
np.exp(L)
instead of using a for loop for every single element? And does it apply to Arrays and Matrices too?
python exponential
asked Nov 12 at 10:46
Fariman Kashani
3928
4
Try it and see.
– coldspeed
Nov 12 at 10:47
add a comment |
up vote
-2
down vote
favorite
up vote
-2
down vote
favorite
Can I raise a list to the power of e Like
np.exp(L)
instead of using a for loop for every single element? And does it apply to Arrays and Matrices too?
python exponential
asked Nov 12 at 10:46
Fariman Kashani
3928
Can I raise a list to the power of e Like
np.exp(L)
instead of using a for loop for every single element? And does it apply to Arrays and Matrices too?
python exponential
python exponential
asked Nov 12 at 10:46
Fariman Kashani
3928
asked Nov 12 at 10:46
Fariman Kashani
3928
asked Nov 12 at 10:46
Fariman Kashani
3928
asked Nov 12 at 10:46
Fariman Kashani
3928
asked Nov 12 at 10:46
Fariman Kashani
3928
3928
4
Try it and see.
– coldspeed
Nov 12 at 10:47
add a comment |
4
Try it and see.
– coldspeed
Nov 12 at 10:47
4
4
Try it and see.
– coldspeed
Nov 12 at 10:47
Try it and see.
– coldspeed
Nov 12 at 10:47
add a comment |
2 Answers
2
active
oldest
votes
up vote
1
down vote
accepted
looks like yes, yes you can
>>> import numpy as np
>>> L=np.array([1,2,3,4,5])
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
even if it's just a plain list and not a numpy array:
>>> L = [1,2,3,4,5]
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
>>>
answered Nov 12 at 10:48
vencaslac
1,002217
add a comment |
up vote
1
down vote
instead of loop if think you can use np.vectorize()
Speeding up your code (2): vectorizing the loops with Numpy
answered Nov 12 at 10:52
Baptiste Gavalda
16011
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
up vote
1
down vote
accepted
looks like yes, yes you can
>>> import numpy as np
>>> L=np.array([1,2,3,4,5])
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
even if it's just a plain list and not a numpy array:
>>> L = [1,2,3,4,5]
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
>>>
answered Nov 12 at 10:48
vencaslac
1,002217
add a comment |
up vote
1
down vote
accepted
looks like yes, yes you can
>>> import numpy as np
>>> L=np.array([1,2,3,4,5])
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
even if it's just a plain list and not a numpy array:
>>> L = [1,2,3,4,5]
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
>>>
answered Nov 12 at 10:48
vencaslac
1,002217
add a comment |
up vote
1
down vote
accepted
up vote
1
down vote
accepted
looks like yes, yes you can
>>> import numpy as np
>>> L=np.array([1,2,3,4,5])
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
even if it's just a plain list and not a numpy array:
>>> L = [1,2,3,4,5]
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
>>>
answered Nov 12 at 10:48
vencaslac
1,002217
looks like yes, yes you can
>>> import numpy as np
>>> L=np.array([1,2,3,4,5])
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
even if it's just a plain list and not a numpy array:
>>> L = [1,2,3,4,5]
>>> np.exp(L)
array([ 2.71828183, 7.3890561 , 20.08553692, 54.59815003,
148.4131591 ])
>>>
answered Nov 12 at 10:48
vencaslac
1,002217
answered Nov 12 at 10:48
vencaslac
1,002217
answered Nov 12 at 10:48
vencaslac
1,002217
answered Nov 12 at 10:48
vencaslac
1,002217
1,002217
add a comment |
add a comment |
up vote
1
down vote
instead of loop if think you can use np.vectorize()
Speeding up your code (2): vectorizing the loops with Numpy
answered Nov 12 at 10:52
Baptiste Gavalda
16011
add a comment |
up vote
1
down vote
instead of loop if think you can use np.vectorize()
Speeding up your code (2): vectorizing the loops with Numpy
answered Nov 12 at 10:52
Baptiste Gavalda
16011
add a comment |
up vote
1
down vote
up vote
1
down vote
instead of loop if think you can use np.vectorize()
Speeding up your code (2): vectorizing the loops with Numpy
answered Nov 12 at 10:52
Baptiste Gavalda
16011
instead of loop if think you can use np.vectorize()
Speeding up your code (2): vectorizing the loops with Numpy
answered Nov 12 at 10:52
Baptiste Gavalda
16011
answered Nov 12 at 10:52
Baptiste Gavalda
16011
answered Nov 12 at 10:52
Baptiste Gavalda
16011
answered Nov 12 at 10:52
Baptiste Gavalda
16011
16011
add a comment |
add a comment |
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4
Try it and see.
– coldspeed
Nov 12 at 10:47