Exponent an arbitrary number by a numpy array












2















I know np.exp2(x) exists that calculates 2^x where x is a numpy array, however, I am looking for a method that does K^x where K is any arbitrary number.
Is there any elegant way of doing it rather than stretching out K to the shape of x and doing a piecewise exponent?






python numpy







share|improve this question

























  • @tel: The "piecewise" seems to make things more confusing rather than less.

    – user2357112
    Nov 22 '18 at 8:24
















2















I know np.exp2(x) exists that calculates 2^x where x is a numpy array, however, I am looking for a method that does K^x where K is any arbitrary number.
Is there any elegant way of doing it rather than stretching out K to the shape of x and doing a piecewise exponent?






python numpy







share|improve this question

























  • @tel: The "piecewise" seems to make things more confusing rather than less.

    – user2357112
    Nov 22 '18 at 8:24














2












2








2








I know np.exp2(x) exists that calculates 2^x where x is a numpy array, however, I am looking for a method that does K^x where K is any arbitrary number.
Is there any elegant way of doing it rather than stretching out K to the shape of x and doing a piecewise exponent?






python numpy







share|improve this question
















I know np.exp2(x) exists that calculates 2^x where x is a numpy array, however, I am looking for a method that does K^x where K is any arbitrary number.
Is there any elegant way of doing it rather than stretching out K to the shape of x and doing a piecewise exponent?






python numpy




python numpy






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 22 '18 at 8:23









user2357112

155k12167260




155k12167260










asked Nov 22 '18 at 5:01









Vj-Vj-

656617




656617













  • @tel: The "piecewise" seems to make things more confusing rather than less.

    – user2357112
    Nov 22 '18 at 8:24



















  • @tel: The "piecewise" seems to make things more confusing rather than less.

    – user2357112
    Nov 22 '18 at 8:24

















@tel: The "piecewise" seems to make things more confusing rather than less.

– user2357112
Nov 22 '18 at 8:24





@tel: The "piecewise" seems to make things more confusing rather than less.

– user2357112
Nov 22 '18 at 8:24












2 Answers
2






active

oldest

votes


















2














Just use the standard Python exponentiation operator **:



K**x


For example, if you have:



x = np.array([1,2,3])

K = 3



print(K**x)


The output is:



[ 3  9 27]


Notes



For Python classes, the behavior of the binary ** operator is implemented via the __pow__, __rpow__, and __ipow__ magic methods (the reality for np.ndarray is slightly more complicated since it's implemented in the C layer, but that's not actually important here). For Numpy arrays, these magic methods in turn appear to call numpy.power, so you can expect that ** will have the same behavior as documented for numpy.power. In particular,




Note that an integer type raised to a negative integer power will raise a ValueError.







share|improve this answer


























  • small note: cast K to a float or else negative numbers in the array will throw an error.

    – Vj-
    Nov 22 '18 at 5:14













  • @Vj- I added a note about the implementation of **, including where it mentions that particular error in the documentation

    – tel
    Nov 22 '18 at 5:32



















2














With numpy you can just use numpy.power



arr = numpy.array([1,2,3])

print(numpy.power(3,arr)) # Outputs [ 3  9 27]





share|improve this answer























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    2 Answers
    2






    active

    oldest

    votes








    2 Answers
    2






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    2














    Just use the standard Python exponentiation operator **:



    K**x


    For example, if you have:



    x = np.array([1,2,3])
    
K = 3
    

    
print(K**x)


    The output is:



    [ 3  9 27]


    Notes



    For Python classes, the behavior of the binary ** operator is implemented via the __pow__, __rpow__, and __ipow__ magic methods (the reality for np.ndarray is slightly more complicated since it's implemented in the C layer, but that's not actually important here). For Numpy arrays, these magic methods in turn appear to call numpy.power, so you can expect that ** will have the same behavior as documented for numpy.power. In particular,




    Note that an integer type raised to a negative integer power will raise a ValueError.







    share|improve this answer


























    • small note: cast K to a float or else negative numbers in the array will throw an error.

      – Vj-
      Nov 22 '18 at 5:14













    • @Vj- I added a note about the implementation of **, including where it mentions that particular error in the documentation

      – tel
      Nov 22 '18 at 5:32
















    2














    Just use the standard Python exponentiation operator **:



    K**x


    For example, if you have:



    x = np.array([1,2,3])
    
K = 3
    

    
print(K**x)


    The output is:



    [ 3  9 27]


    Notes



    For Python classes, the behavior of the binary ** operator is implemented via the __pow__, __rpow__, and __ipow__ magic methods (the reality for np.ndarray is slightly more complicated since it's implemented in the C layer, but that's not actually important here). For Numpy arrays, these magic methods in turn appear to call numpy.power, so you can expect that ** will have the same behavior as documented for numpy.power. In particular,




    Note that an integer type raised to a negative integer power will raise a ValueError.







    share|improve this answer


























    • small note: cast K to a float or else negative numbers in the array will throw an error.

      – Vj-
      Nov 22 '18 at 5:14













    • @Vj- I added a note about the implementation of **, including where it mentions that particular error in the documentation

      – tel
      Nov 22 '18 at 5:32














    2












    2








    2







    Just use the standard Python exponentiation operator **:



    K**x


    For example, if you have:



    x = np.array([1,2,3])
    
K = 3
    

    
print(K**x)


    The output is:



    [ 3  9 27]


    Notes



    For Python classes, the behavior of the binary ** operator is implemented via the __pow__, __rpow__, and __ipow__ magic methods (the reality for np.ndarray is slightly more complicated since it's implemented in the C layer, but that's not actually important here). For Numpy arrays, these magic methods in turn appear to call numpy.power, so you can expect that ** will have the same behavior as documented for numpy.power. In particular,




    Note that an integer type raised to a negative integer power will raise a ValueError.







    share|improve this answer















    Just use the standard Python exponentiation operator **:



    K**x


    For example, if you have:



    x = np.array([1,2,3])
    
K = 3
    

    
print(K**x)


    The output is:



    [ 3  9 27]


    Notes



    For Python classes, the behavior of the binary ** operator is implemented via the __pow__, __rpow__, and __ipow__ magic methods (the reality for np.ndarray is slightly more complicated since it's implemented in the C layer, but that's not actually important here). For Numpy arrays, these magic methods in turn appear to call numpy.power, so you can expect that ** will have the same behavior as documented for numpy.power. In particular,




    Note that an integer type raised to a negative integer power will raise a ValueError.








    share|improve this answer














    share|improve this answer



    share|improve this answer








    edited Nov 22 '18 at 5:37

























    answered Nov 22 '18 at 5:07









    teltel

    7,41621431




    7,41621431













    • small note: cast K to a float or else negative numbers in the array will throw an error.

      – Vj-
      Nov 22 '18 at 5:14













    • @Vj- I added a note about the implementation of **, including where it mentions that particular error in the documentation

      – tel
      Nov 22 '18 at 5:32



















    • small note: cast K to a float or else negative numbers in the array will throw an error.

      – Vj-
      Nov 22 '18 at 5:14













    • @Vj- I added a note about the implementation of **, including where it mentions that particular error in the documentation

      – tel
      Nov 22 '18 at 5:32

















    small note: cast K to a float or else negative numbers in the array will throw an error.

    – Vj-
    Nov 22 '18 at 5:14







    small note: cast K to a float or else negative numbers in the array will throw an error.

    – Vj-
    Nov 22 '18 at 5:14















    @Vj- I added a note about the implementation of **, including where it mentions that particular error in the documentation

    – tel
    Nov 22 '18 at 5:32





    @Vj- I added a note about the implementation of **, including where it mentions that particular error in the documentation

    – tel
    Nov 22 '18 at 5:32













    2














    With numpy you can just use numpy.power



    arr = numpy.array([1,2,3])
    
print(numpy.power(3,arr)) # Outputs [ 3  9 27]





    share|improve this answer




























      2














      With numpy you can just use numpy.power



      arr = numpy.array([1,2,3])
      
print(numpy.power(3,arr)) # Outputs [ 3  9 27]





      share|improve this answer


























        2












        2








        2







        With numpy you can just use numpy.power



        arr = numpy.array([1,2,3])
        
print(numpy.power(3,arr)) # Outputs [ 3  9 27]





        share|improve this answer













        With numpy you can just use numpy.power



        arr = numpy.array([1,2,3])
        
print(numpy.power(3,arr)) # Outputs [ 3  9 27]






        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 22 '18 at 5:11









        b-fgb-fg

        1,95911522




        1,95911522






























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