How does python numpy where work

Question

I am playing with numpy and digging through documentation and I have come across some magic  Namely I am talking about numpy where      gt  gt  gt  x   np arange 9   reshape 3  3   gt  gt  gt  np where  x  gt  5    array  2  2  2    array  0  1  2      How do they achieve internally that you are able to pass something like x  gt  5 into a method  I guess it has something to do with   gt   but I am looking for a detailed explanation

User · Answer

Old Answer it is kind of confusing   It gives you the LOCATIONS  all of them  of where your statment is true   so    gt  gt  gt  a   np arange 100   gt  gt  gt  np where a  gt  30   array  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47         48  49  50  51  52  53  54  55  56  57  58  59  60  61  62  63  64         65  66  67  68  69  70  71  72  73  74  75  76  77  78  79  80  81         82  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97  98         99      gt  gt  gt  np where a    90   array  90      a   a 40  gt  gt  gt  np where a  gt  1000   array  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42         43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59         60  61  62  63  64  65  66  67  68  69  70  71  72  73  74  75  76         77  78  79  80  81  82  83  84  85  86  87  88  89  90  91  92  93         94  95  96  97  98  99      gt  gt  gt  a 25  1000  gt  gt  gt  a 26  1040   I use it as an alternative to list index    but it has many other uses as well   I have never used it with 2D arrays   http   docs scipy org doc numpy reference generated numpy where html  New Answer It seems that the person was asking something more fundamental   The question was how could YOU implement something that allows a function  such as where  to know what was requested   First note that calling any of the comparison operators do an interesting thing   a  gt  1000 array  False  False  False  False  False  False  False  False  False         False  False  False  False  False  False  False  False  False         False  False  False  False  False  False  False  False   True          True   True   True   True   True   True   True   True   True          True   True   True   True   True   True   True   True   True          True   True   True   True   True   True   True   True   True          True   True   True   True   True   True   True   True   True          True   True   True   True   True   True   True   True   True          True   True   True   True   True   True   True   True   True          True   True   True   True   True   True   True   True   True          True    True   True   True   True   True   True   True   True   True   dtype bool     This is done by overloading the    gt    method   For instance    gt  gt  gt  class demo object       def   gt   self  item           print item    gt  gt  gt  a   demo    gt  gt  gt  a  gt  4 4   As you can see   a   4  was valid code   You can get a full list and documentation of all overloaded functions here  http   docs python org reference datamodel html  Something that is incredible is how simple it is to do this   ALL operations in python are done in such a way   Saying a   b is equivalent to a gt b

User · Answer

np where returns a tuple of length equal to the dimension of the numpy ndarray on which it is called  in other words ndim  and each item of tuple is a numpy ndarray of indices of all those values in the initial ndarray for which the condition is True   Please don t confuse dimension with shape   For example   x np arange 9  reshape 3 3  print x  array   0  1  2          3  4  5          6  7  8    y   np where x gt 4  print y  array  1  2  2  2   dtype int64   array  2  0  1  2   dtype int64      y is a tuple of length 2 because x ndim is 2  The 1st item in tuple contains row numbers of all elements greater than 4 and the 2nd item contains column numbers of all items greater than 4  As you can see   1 2 2 2  corresponds to row numbers of 5 6 7 8 and  2 0 1 2  corresponds to column numbers of 5 6 7 8 Note that the ndarray is traversed along first dimension row-wise    Similarly   x np arange 27  reshape 3 3 3  np where x gt 4     will return a tuple of length 3 because x has 3 dimensions   But wait  there s more to np where   when two additional arguments are added to np where  it will do a replace operation for all those pairwise row-column combinations which are obtained by the above tuple    x np arange 9  reshape 3 3  y   np where x gt 4  1  0  print y  array   0  0  0       0  0  1       1  1  1

User · Answer

How do they achieve internally that you are able to pass something like x   5 into a method    The short answer is that they don t   Any sort of logical operation on a numpy array returns a boolean array   i e    gt      lt    etc all return boolean arrays where the given condition is true    E g    x   np arange 9  reshape 3 3  print x  gt  5   yields   array   False  False  False           False  False  False            True   True   True    dtype bool    This is the same reason why something like if x  gt  5  raises a ValueError if x is a numpy array   It s an array of True False values  not a single value   Furthermore  numpy arrays can be indexed by boolean arrays  E g  x x gt 5  yields  6 7 8   in this case   Honestly  it s fairly rare that you actually need numpy where but it just returns the indicies where a boolean array is True   Usually you can do what you need with simple boolean indexing

[python] How does python numpy.where() work?

Examples related to python

Examples related to numpy

Examples related to magic-methods