How do I select elements of an array given condition

Question

Suppose I have a numpy array x    5  2  3  1  4  5   y     f    o    o    b    a    r    I want to select the elements in y corresponding to elements in x that are greater than 1 and less than 5   I tried  x   array  5  2  3  1  4  5   y   array   f   o   o   b   a   r    output   y x  gt  1  amp  x  lt  5    desired output is   o   o   a     but this doesn t work  How would I do this

User · Accepted Answer

Your expression works if you add parentheses    gt  gt  gt  y  1  lt  x   amp   x  lt  5   array   o    o    a           dtype   S1

User · Answer

I like to use np vectorize for such tasks  Consider the following    gt  gt  gt    Arrays  gt  gt  gt  x   np array  5  2  3  1  4  5    gt  gt  gt  y   np array   f   o   o   b   a   r      gt  gt  gt    Function containing the constraints  gt  gt  gt  func   np vectorize lambda t  t gt 1 and t lt 5    gt  gt  gt    Call function on x  gt  gt  gt  y func x    gt  gt  gt  array   o    o    a    dtype   lt U1     The advantage is you can add many more types of constraints in the vectorized function   Hope it helps

User · Answer

IMO OP does not actually want np bitwise and    aka  amp   but actually wants np logical and   because they are comparing logical values such as True and False - see this SO post on logical vs  bitwise to see the difference    gt  gt  gt  x   array  5  2  3  1  4  5    gt  gt  gt  y   array   f   o   o   b   a   r     gt  gt  gt  output   y np logical and x  gt  1  x  lt  5     desired output is   o   o   a    gt  gt  gt  output array   o    o    a          dtype   S1     And equivalent way to do this is with np all   by setting the axis argument appropriately    gt  gt  gt  output   y np all  x  gt  1  x  lt  5   axis 0     desired output is   o   o   a    gt  gt  gt  output array   o    o    a          dtype   S1     by the numbers    gt  gt  gt   timeit  a  lt  b   amp   b  lt  c  The slowest run took 32 97 times longer than the fastest  This could mean that an intermediate result is being cached  100000 loops  best of 3  1 15   s per loop   gt  gt  gt   timeit np logical and a  lt  b  b  lt  c  The slowest run took 32 59 times longer than the fastest  This could mean that an intermediate result is being cached  1000000 loops  best of 3  1 17   s per loop   gt  gt  gt   timeit np all  a  lt  b  b  lt  c   0  The slowest run took 67 47 times longer than the fastest  This could mean that an intermediate result is being cached  100000 loops  best of 3  5 06   s per loop   so using np all   is slower  but  amp  and logical and are about the same

User · Answer

For 2D arrays  you can do this  Create a 2D mask using the condition  Typecast the condition mask to int or float  depending on the array  and multiply it with the original array   In  8   arr Out 8    array    1    2    3    4    5             6    7    8    9   10      In  9   arr  arr   2    0  astype np int   Out 9    array    0    2    0    4    0             6    0    8    0   10

User · Answer

Add one detail to  J F  Sebastian s and  Mark Mikofski s answers  If one wants to get the corresponding indices  rather than the actual values of array   the following code will do   For satisfying multiple  all  conditions   select indices   np where  np logical and  x  gt  1  x  lt  5    0      1  lt  x  lt 5   For satisfying multiple  or  conditions   select indices   np where  np logical or  x  lt  1  x  gt  5     0    x  lt 1 or x  gt 5

User · Answer

Actually I would do it this way   L1 is the index list of elements satisfying condition 1  maybe you can use somelist index condition1  or np where condition1  to get L1    Similarly  you get L2  a list of elements satisfying condition 2   Then you find intersection using intersect L1 L2    You can also find intersection of multiple lists if you get multiple conditions to satisfy   Then you can apply index in any other array  for example  x

[python] How do I select elements of an array given condition?

Examples related to python

Examples related to numpy