Numpy find index of the elements within range

Question

I have a numpy array of numbers  for example     a   np array  1  3  5  6  9  10  14  15  56       I would like to find all the indexes of the elements within a specific range  For instance  if the range is  6  10   the answer should be  3  4  5   Is there a built-in function to do this

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Other way is with   np vectorize lambda x  6  lt   x  lt   10  a    which returns   array  False  False  False   True   True   True  False  False  False     It is sometimes useful for masking time series  vectors  etc

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You can use np clip   to achieve the same   a    1  3  5  6  9  10  14  15  56    np clip a 6 10    However  it holds the values less than and greater than 6 and 10 respectively

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Wanted to add numexpr into the mix   import numpy as np import numexpr as ne  a   np array  1  3  5  6  9  10  14  15  56      np where ne evaluate   6  lt   a   amp   a  lt   10     0    array  3  4  5   dtype int64    Would only make sense for larger arrays with millions    or if you hitting a memory limits

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a   np array  1  3  5  6  9  10  14  15  56   np argwhere  a gt  6   amp   a lt  10

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Summary of the answers  For understanding what is the best answer we can do some timing using the different solution  Unfortunately  the question was not well-posed so there are answers to different questions  here I try to point the answer to the same question   Given the array   a   np array  1  3  5  6  9  10  14  15  56     The answer should be the indexes of the elements between a certain range  we assume inclusive  in this case  6 and 10   answer    3  4  5    Corresponding to the values 6 9 10   To test the best answer we can use this code   import timeit setup       import numpy as np import numexpr as ne  a   np array  1  3  5  6  9  10  14  15  56     we define the left and right limit ll   6 rl   10  def sorted slice a l r       start   np searchsorted a  l   left       end   np searchsorted a  r   right       return np arange start end       functions     sorted slice a ll rl      works only for sorted values  np where np logical and a gt  ll  a lt  rl   0     np where  a  gt   ll   amp   a  lt  rl   0     np where  a gt  ll   a lt  rl   0     np where np vectorize lambda x  ll  lt   x  lt   rl  a   0     np argwhere  a gt  ll   amp   a lt  rl   T 0      we traspose for getting a single row  np where ne evaluate   ll  lt   a   amp   a  lt   rl     0      functions2         a np logical and a gt  ll  a lt  rl         a  a gt  ll   amp   a lt  rl         a  a gt  ll   a lt  rl         a np vectorize lambda x  ll  lt   x  lt   rl  a         a ne evaluate   ll  lt   a   amp   a  lt   rl           Results  The results are reported in the following plot  On the top the fastest solutions   If instead of the indexes you want to extract the values you can perform the tests using functions2 but the results are almost the same

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You can use np where to get indices and np logical and to set two conditions   import numpy as np a   np array  1  3  5  6  9  10  14  15  56    np where np logical and a gt  6  a lt  10     returns  array  3  4  5

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This code snippet returns all the numbers in a numpy array between two values   a   np array  1  3  5  6  9  10  14  15  56    a  a gt 6   a lt 10     It works as following   a 6  returns a numpy array with True  1  and False  0   so does  a lt 10   By multiplying these two together you get an array with either a True  if both statements are True  because 1x1   1  or False  because 0x0   0 and 1x0   0    The part a      returns all values of array a where the array between brackets returns a True statement   Of course you can make this more complicated by saying for instance        1-a lt 10     which is similar to an  and Not  statement

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a   np array  1 2 3 4 5 6 7 8 9   b   a  a gt 2   amp   a lt 8

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I thought I would add this because the a in the example you gave is sorted   import numpy as np a    1  3  5  6  9  10  14  15  56   start   np searchsorted a  6   left   end   np searchsorted a  10   right   rng   np arange start  end  rng   array  3  4  5

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This may not be the prettiest  but works for any dimension  a   np array   -1 2    1 5    6 7    5 2    3 4    0  0    -1 -1    ranges    0 4    0 4    def conditionRange X   np ndarray  ranges   list  - gt  np ndarray      idx   set       for column  r in enumerate ranges           tmp   np where np logical and X    column   gt   r 0   X    column   lt   r 1    0          if idx              idx   idx  amp  set tmp          else              idx   set tmp      idx   np array list idx       return X idx      b   conditionRange a  ranges  print b

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s  52  33  70  39  57  59  7  2  46  69  11  74  58  60  63  43  75  92  65  19  1  79  22  38  26  3  66  88  9  15  28  44  67  87  21  49  85  32  89  77  47  93  35  12  73  76  50  45  5  29  97  94  95  56  48  71  54  55  51  23  84  80  62  30  13  34   dic     for i in range 0 len s  10       dic i i 10  list filter lambda x   x gt  i  amp  x lt i 10   s   print dic   for keys values in dic items        print keys      print values    Output       0  10   7  2  1  3  9  5   20  30   22  26  28  21  29  23   30  40   33  39  38  32  35  30  34   10  20   11  19  15  12  13   40  50   46  43  44  49  47  45  48   60  70   69  60  63  65  66  67  62   50  60   52  57  59  58  50  56  54  55  51

User · Answer

As in  deinonychusaur s reply  but even more compact   In  7   np where  a  gt   6   amp   a  lt  10   Out 7    array  3  4  5

[python] Numpy: find index of the elements within range

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