python - replace multiple if elif statements and conditions with numpy function such as numpy.where











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Radio_index, n_x and n_y are integers
I wrote a if/elif code that can be run.
The purpose is to find x,y position for a radio_index
Am I able to do with np.where



def radio_index2xy(radio_index,n_x,n_y): 

con1 = radio_index <= n_x
con2 = (radio_index > n_x) & (radio_index <= n_x+n_y-1)
con3 = (radio_index > n_x+n_y-1) & (radio_index <= 2*n_x+n_y-2)
con4 = (radio_index > 2*n_x+n_y-2) & (radio_index <= 2*n_x+2*n_y-4)
condlist = [[con1],[con2],[con3],[con4]]
choicelist = [[x_pos = radio_index -1 ,y_pos = 0],
[(x_pos = n_x -1),(y_pos = radio_index - n_x)],
[(x_pos = (n_x-1)-(radio_index-n_x-n_y+1)),(y_pos = n_y -1)],
[(x_pos = 0),(y_pos = 2*n_x+2*n_y-4-radio_index+1)]]
np.select(condlist,choicelist)

return x_pos,y_pos





if radio_index <= n_x:
x_pos = radio_index -1
y_pos = 0
elif radio_index > n_x and radio_index <= n_x+n_y-1:
x_pos = n_x -1
y_pos = radio_index - n_x
elif radio_index > n_x+n_y-1 and radio_index <= 2*n_x+n_y-2:
x_pos = (n_x-1)-(radio_index-n_x-n_y+1)
y_pos = n_y -1
elif radio_index > 2*n_x+n_y-2 and radio_index <= 2*n_x+2*n_y-4:
x_pos = 0
y_pos = 2*n_x+2*n_y-4-radio_index+1









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  • 3




    Please tell us what the code is supposed to do, I don't think anybody is going to reverse engineer it.
    – timgeb
    Nov 10 at 21:40






  • 1




    Also there's not a single if/elif in this code.
    – timgeb
    Nov 10 at 21:41










  • This is used to find the x(vertical axis) and y(horizontal axis) from the given radio_index
    – Yci Meow
    Nov 11 at 4:37










  • The if/elif method can be run.
    – Yci Meow
    Nov 11 at 4:37















up vote
-1
down vote

favorite












Radio_index, n_x and n_y are integers
I wrote a if/elif code that can be run.
The purpose is to find x,y position for a radio_index
Am I able to do with np.where



def radio_index2xy(radio_index,n_x,n_y): 

con1 = radio_index <= n_x
con2 = (radio_index > n_x) & (radio_index <= n_x+n_y-1)
con3 = (radio_index > n_x+n_y-1) & (radio_index <= 2*n_x+n_y-2)
con4 = (radio_index > 2*n_x+n_y-2) & (radio_index <= 2*n_x+2*n_y-4)
condlist = [[con1],[con2],[con3],[con4]]
choicelist = [[x_pos = radio_index -1 ,y_pos = 0],
[(x_pos = n_x -1),(y_pos = radio_index - n_x)],
[(x_pos = (n_x-1)-(radio_index-n_x-n_y+1)),(y_pos = n_y -1)],
[(x_pos = 0),(y_pos = 2*n_x+2*n_y-4-radio_index+1)]]
np.select(condlist,choicelist)

return x_pos,y_pos





if radio_index <= n_x:
x_pos = radio_index -1
y_pos = 0
elif radio_index > n_x and radio_index <= n_x+n_y-1:
x_pos = n_x -1
y_pos = radio_index - n_x
elif radio_index > n_x+n_y-1 and radio_index <= 2*n_x+n_y-2:
x_pos = (n_x-1)-(radio_index-n_x-n_y+1)
y_pos = n_y -1
elif radio_index > 2*n_x+n_y-2 and radio_index <= 2*n_x+2*n_y-4:
x_pos = 0
y_pos = 2*n_x+2*n_y-4-radio_index+1









share|improve this question




















  • 3




    Please tell us what the code is supposed to do, I don't think anybody is going to reverse engineer it.
    – timgeb
    Nov 10 at 21:40






  • 1




    Also there's not a single if/elif in this code.
    – timgeb
    Nov 10 at 21:41










  • This is used to find the x(vertical axis) and y(horizontal axis) from the given radio_index
    – Yci Meow
    Nov 11 at 4:37










  • The if/elif method can be run.
    – Yci Meow
    Nov 11 at 4:37













up vote
-1
down vote

favorite









up vote
-1
down vote

favorite











Radio_index, n_x and n_y are integers
I wrote a if/elif code that can be run.
The purpose is to find x,y position for a radio_index
Am I able to do with np.where



def radio_index2xy(radio_index,n_x,n_y): 

con1 = radio_index <= n_x
con2 = (radio_index > n_x) & (radio_index <= n_x+n_y-1)
con3 = (radio_index > n_x+n_y-1) & (radio_index <= 2*n_x+n_y-2)
con4 = (radio_index > 2*n_x+n_y-2) & (radio_index <= 2*n_x+2*n_y-4)
condlist = [[con1],[con2],[con3],[con4]]
choicelist = [[x_pos = radio_index -1 ,y_pos = 0],
[(x_pos = n_x -1),(y_pos = radio_index - n_x)],
[(x_pos = (n_x-1)-(radio_index-n_x-n_y+1)),(y_pos = n_y -1)],
[(x_pos = 0),(y_pos = 2*n_x+2*n_y-4-radio_index+1)]]
np.select(condlist,choicelist)

return x_pos,y_pos





if radio_index <= n_x:
x_pos = radio_index -1
y_pos = 0
elif radio_index > n_x and radio_index <= n_x+n_y-1:
x_pos = n_x -1
y_pos = radio_index - n_x
elif radio_index > n_x+n_y-1 and radio_index <= 2*n_x+n_y-2:
x_pos = (n_x-1)-(radio_index-n_x-n_y+1)
y_pos = n_y -1
elif radio_index > 2*n_x+n_y-2 and radio_index <= 2*n_x+2*n_y-4:
x_pos = 0
y_pos = 2*n_x+2*n_y-4-radio_index+1









share|improve this question















Radio_index, n_x and n_y are integers
I wrote a if/elif code that can be run.
The purpose is to find x,y position for a radio_index
Am I able to do with np.where



def radio_index2xy(radio_index,n_x,n_y): 

con1 = radio_index <= n_x
con2 = (radio_index > n_x) & (radio_index <= n_x+n_y-1)
con3 = (radio_index > n_x+n_y-1) & (radio_index <= 2*n_x+n_y-2)
con4 = (radio_index > 2*n_x+n_y-2) & (radio_index <= 2*n_x+2*n_y-4)
condlist = [[con1],[con2],[con3],[con4]]
choicelist = [[x_pos = radio_index -1 ,y_pos = 0],
[(x_pos = n_x -1),(y_pos = radio_index - n_x)],
[(x_pos = (n_x-1)-(radio_index-n_x-n_y+1)),(y_pos = n_y -1)],
[(x_pos = 0),(y_pos = 2*n_x+2*n_y-4-radio_index+1)]]
np.select(condlist,choicelist)

return x_pos,y_pos





if radio_index <= n_x:
x_pos = radio_index -1
y_pos = 0
elif radio_index > n_x and radio_index <= n_x+n_y-1:
x_pos = n_x -1
y_pos = radio_index - n_x
elif radio_index > n_x+n_y-1 and radio_index <= 2*n_x+n_y-2:
x_pos = (n_x-1)-(radio_index-n_x-n_y+1)
y_pos = n_y -1
elif radio_index > 2*n_x+n_y-2 and radio_index <= 2*n_x+2*n_y-4:
x_pos = 0
y_pos = 2*n_x+2*n_y-4-radio_index+1






python numpy if-statement






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share|improve this question













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share|improve this question








edited Nov 11 at 4:40

























asked Nov 10 at 21:37









Yci Meow

83




83








  • 3




    Please tell us what the code is supposed to do, I don't think anybody is going to reverse engineer it.
    – timgeb
    Nov 10 at 21:40






  • 1




    Also there's not a single if/elif in this code.
    – timgeb
    Nov 10 at 21:41










  • This is used to find the x(vertical axis) and y(horizontal axis) from the given radio_index
    – Yci Meow
    Nov 11 at 4:37










  • The if/elif method can be run.
    – Yci Meow
    Nov 11 at 4:37














  • 3




    Please tell us what the code is supposed to do, I don't think anybody is going to reverse engineer it.
    – timgeb
    Nov 10 at 21:40






  • 1




    Also there's not a single if/elif in this code.
    – timgeb
    Nov 10 at 21:41










  • This is used to find the x(vertical axis) and y(horizontal axis) from the given radio_index
    – Yci Meow
    Nov 11 at 4:37










  • The if/elif method can be run.
    – Yci Meow
    Nov 11 at 4:37








3




3




Please tell us what the code is supposed to do, I don't think anybody is going to reverse engineer it.
– timgeb
Nov 10 at 21:40




Please tell us what the code is supposed to do, I don't think anybody is going to reverse engineer it.
– timgeb
Nov 10 at 21:40




1




1




Also there's not a single if/elif in this code.
– timgeb
Nov 10 at 21:41




Also there's not a single if/elif in this code.
– timgeb
Nov 10 at 21:41












This is used to find the x(vertical axis) and y(horizontal axis) from the given radio_index
– Yci Meow
Nov 11 at 4:37




This is used to find the x(vertical axis) and y(horizontal axis) from the given radio_index
– Yci Meow
Nov 11 at 4:37












The if/elif method can be run.
– Yci Meow
Nov 11 at 4:37




The if/elif method can be run.
– Yci Meow
Nov 11 at 4:37












1 Answer
1






active

oldest

votes

















up vote
0
down vote



accepted










np.searchsorted is useful for this kind of logic:



def radio_index2xy_v(radio_index, n_x, n_y):
sgn = np.array([0, 1, 1, -1, -1, 0])
col = np.array([-1, 1, 0, 1, 0, -1])
coeffs = np.array([[-1, -1],
[0, -1],
[-n_x, n_x - 1],
[n_y - 1, 2*n_x + n_y - 2],
[2*n_x + 2*n_y - 3, 0],
[-1, -1]])
cusps = np.cumsum([0, n_x, n_y-1, n_x-1, n_y-2])
idx = cusps.searchsorted(radio_index)
out = coeffs[idx]
out[np.arange(idx.size), col[idx]] += sgn[idx] * radio_index
return out


Demo:



>>> radio_index2xy_v(np.arange(20), 5, 4)
array([[-1, -1],
[ 0, 0],
[ 0, 1],
[ 0, 2],
[ 0, 3],
[ 0, 4],
[ 1, 4],
[ 2, 4],
[ 3, 4],
[ 3, 3],
[ 3, 2],
[ 3, 1],
[ 3, 0],
[ 2, 0],
[ 1, 0],
[-1, -1],
[-1, -1],
[-1, -1],
[-1, -1],
[-1, -1]])





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    1 Answer
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    active

    oldest

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    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes








    up vote
    0
    down vote



    accepted










    np.searchsorted is useful for this kind of logic:



    def radio_index2xy_v(radio_index, n_x, n_y):
    sgn = np.array([0, 1, 1, -1, -1, 0])
    col = np.array([-1, 1, 0, 1, 0, -1])
    coeffs = np.array([[-1, -1],
    [0, -1],
    [-n_x, n_x - 1],
    [n_y - 1, 2*n_x + n_y - 2],
    [2*n_x + 2*n_y - 3, 0],
    [-1, -1]])
    cusps = np.cumsum([0, n_x, n_y-1, n_x-1, n_y-2])
    idx = cusps.searchsorted(radio_index)
    out = coeffs[idx]
    out[np.arange(idx.size), col[idx]] += sgn[idx] * radio_index
    return out


    Demo:



    >>> radio_index2xy_v(np.arange(20), 5, 4)
    array([[-1, -1],
    [ 0, 0],
    [ 0, 1],
    [ 0, 2],
    [ 0, 3],
    [ 0, 4],
    [ 1, 4],
    [ 2, 4],
    [ 3, 4],
    [ 3, 3],
    [ 3, 2],
    [ 3, 1],
    [ 3, 0],
    [ 2, 0],
    [ 1, 0],
    [-1, -1],
    [-1, -1],
    [-1, -1],
    [-1, -1],
    [-1, -1]])





    share|improve this answer

























      up vote
      0
      down vote



      accepted










      np.searchsorted is useful for this kind of logic:



      def radio_index2xy_v(radio_index, n_x, n_y):
      sgn = np.array([0, 1, 1, -1, -1, 0])
      col = np.array([-1, 1, 0, 1, 0, -1])
      coeffs = np.array([[-1, -1],
      [0, -1],
      [-n_x, n_x - 1],
      [n_y - 1, 2*n_x + n_y - 2],
      [2*n_x + 2*n_y - 3, 0],
      [-1, -1]])
      cusps = np.cumsum([0, n_x, n_y-1, n_x-1, n_y-2])
      idx = cusps.searchsorted(radio_index)
      out = coeffs[idx]
      out[np.arange(idx.size), col[idx]] += sgn[idx] * radio_index
      return out


      Demo:



      >>> radio_index2xy_v(np.arange(20), 5, 4)
      array([[-1, -1],
      [ 0, 0],
      [ 0, 1],
      [ 0, 2],
      [ 0, 3],
      [ 0, 4],
      [ 1, 4],
      [ 2, 4],
      [ 3, 4],
      [ 3, 3],
      [ 3, 2],
      [ 3, 1],
      [ 3, 0],
      [ 2, 0],
      [ 1, 0],
      [-1, -1],
      [-1, -1],
      [-1, -1],
      [-1, -1],
      [-1, -1]])





      share|improve this answer























        up vote
        0
        down vote



        accepted







        up vote
        0
        down vote



        accepted






        np.searchsorted is useful for this kind of logic:



        def radio_index2xy_v(radio_index, n_x, n_y):
        sgn = np.array([0, 1, 1, -1, -1, 0])
        col = np.array([-1, 1, 0, 1, 0, -1])
        coeffs = np.array([[-1, -1],
        [0, -1],
        [-n_x, n_x - 1],
        [n_y - 1, 2*n_x + n_y - 2],
        [2*n_x + 2*n_y - 3, 0],
        [-1, -1]])
        cusps = np.cumsum([0, n_x, n_y-1, n_x-1, n_y-2])
        idx = cusps.searchsorted(radio_index)
        out = coeffs[idx]
        out[np.arange(idx.size), col[idx]] += sgn[idx] * radio_index
        return out


        Demo:



        >>> radio_index2xy_v(np.arange(20), 5, 4)
        array([[-1, -1],
        [ 0, 0],
        [ 0, 1],
        [ 0, 2],
        [ 0, 3],
        [ 0, 4],
        [ 1, 4],
        [ 2, 4],
        [ 3, 4],
        [ 3, 3],
        [ 3, 2],
        [ 3, 1],
        [ 3, 0],
        [ 2, 0],
        [ 1, 0],
        [-1, -1],
        [-1, -1],
        [-1, -1],
        [-1, -1],
        [-1, -1]])





        share|improve this answer












        np.searchsorted is useful for this kind of logic:



        def radio_index2xy_v(radio_index, n_x, n_y):
        sgn = np.array([0, 1, 1, -1, -1, 0])
        col = np.array([-1, 1, 0, 1, 0, -1])
        coeffs = np.array([[-1, -1],
        [0, -1],
        [-n_x, n_x - 1],
        [n_y - 1, 2*n_x + n_y - 2],
        [2*n_x + 2*n_y - 3, 0],
        [-1, -1]])
        cusps = np.cumsum([0, n_x, n_y-1, n_x-1, n_y-2])
        idx = cusps.searchsorted(radio_index)
        out = coeffs[idx]
        out[np.arange(idx.size), col[idx]] += sgn[idx] * radio_index
        return out


        Demo:



        >>> radio_index2xy_v(np.arange(20), 5, 4)
        array([[-1, -1],
        [ 0, 0],
        [ 0, 1],
        [ 0, 2],
        [ 0, 3],
        [ 0, 4],
        [ 1, 4],
        [ 2, 4],
        [ 3, 4],
        [ 3, 3],
        [ 3, 2],
        [ 3, 1],
        [ 3, 0],
        [ 2, 0],
        [ 1, 0],
        [-1, -1],
        [-1, -1],
        [-1, -1],
        [-1, -1],
        [-1, -1]])






        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 11 at 8:17









        Paul Panzer

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