Count all values in a matrix greater than a value

Question

I have to count all the values in a matrix  2-d array  that are greater than 200   The code I wrote down for this is   za 0    p31   numpy asarray o31     for i in range o31 size 0           for j in range o32 size 1               if p31 i j  lt 200                 za za 1    print za   o31 is an image and I am converting it into a matrix and then finding the values   My question is  is there a simpler way to do this

User · Answer

Here s a variant that uses fancy indexing and has the actual values as an intermediate   p31   numpy asarray o31  values   p31 p31 lt 200  za   len values

User · Answer

To count the number of values larger than x in any numpy array you can use   n   len matrix matrix  gt  x     The boolean indexing returns an array that contains only the elements where the condition  matrix   x  is met  Then len   counts these values

User · Answer

This is very straightforward with boolean arrays   p31   numpy asarray o31  za    p31  lt  200  sum     p31 lt 200 is a boolean array  so  sum  counts the number of True elements

User · Answer

There are many ways to achieve this  like flatten-and-filter or simply enumerate  but I think using Boolean mask array is the easiest one  and iirc a much faster one     gt  gt  gt  y   np array   123 24123 32432    234 24 23    array     123  24123  32432             234     24     23     gt  gt  gt  b   y  gt  200  gt  gt  gt  b array   False   True   True            True  False  False    dtype bool   gt  gt  gt  y b  array  24123  32432    234    gt  gt  gt  len y b   3  gt  gt  gt  gt  y b  sum   56789   Update   As nneonneo has answered  if all you want is the number of elements that passes threshold  you can simply do    gt  gt  gt  gt   y gt 200  sum   3   which is a simpler solution     Speed comparison with filter       use boolean mask array      b   y  gt  200   timeit y b  100000 loops  best of 3  3 31 us per loop   timeit y y gt 200  100000 loops  best of 3  7 57 us per loop      use filter      x   y ravel    timeit filter lambda x x gt 200  x  100000 loops  best of 3  9 33 us per loop   timeit np array filter lambda x x gt 200  x   10000 loops  best of 3  21 7 us per loop   timeit filter lambda x x gt 200  y ravel    100000 loops  best of 3  11 2 us per loop   timeit np array filter lambda x x gt 200  y ravel     10000 loops  best of 3  22 9 us per loop      use numpy where      nb   np where y gt 200   timeit y nb  100000 loops  best of 3  2 42 us per loop   timeit y np where y gt 200   100000 loops  best of 3  10 3 us per loop

User · Answer

The numpy where function is your friend  Because it s implemented to take full advantage of the array datatype  for large images you should notice a speed improvement over the pure python solution you provide   Using numpy where directly will yield a boolean mask indicating whether certain values match your conditions     gt  gt  gt  data array   1  8           3  4     gt  gt  gt  numpy where  data  gt  3    array  0  1    array  1  1      And the mask can be used to index the array directly to get the actual values    gt  gt  gt  data  numpy where  data  gt  3     array  8  4     Exactly where you take it from there will depend on what form you d like the results in

User · Answer

You can use numpy count nonzero  converting the whole into a one-liner  za   numpy count nonzero numpy asarray o31  lt 200    as written in the code

[python] Count all values in a matrix greater than a value

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