Python: Doing Calculations on array elements in a list

Question

I have a list of arrays, in which each array represents a cell and the array elements are the coordinates x,y and z, the time point and the cell id. Here a sector of it:

cells=[   ..., 
   [ 264.847,  121.056,   30.868,   42.   ,  375.   ],
   [ 259.24 ,  116.875,   29.973,   43.   ,  375.   ],
   [ 260.757,  118.574,   32.772,   44.   ,  375.   ]]), array([[ 263.967,  154.089,   55.5  ,   38.   ,  376.   ],
   [ 260.744,  152.924,   55.5  ,   39.   ,  376.   ],
   [ 258.456,  151.373,   55.5  ,   40.   ,  376.   ],
   ..., 
   [ 259.086,  159.564,   48.521,   53.   ,  376.   ],
   [ 258.933,  159.796,   48.425,   54.   ,  376.   ],
   [ 259.621,  158.719,   51.606,   55.   ,  376.   ]]), array([[ 291.647,   57.582,   28.178,   38.   ,  377.   ],
   [ 284.625,   59.221,   30.028,   39.   ,  377.   ],
   [ 282.915,   59.37 ,   30.402,   40.   ,  377.   ],
   ..., 
   [ 271.224,   58.534,   23.166,   42.   ,  377.   ],
   [ 270.048,   58.738,   21.749,   43.   ,  377.   ],
   [ 268.38 ,   58.138,   20.606,   44.   ,  377.   ]]), array([[  87.83 ,  222.144,   26.258,   39.   ,  378.   ],
   [  99.779,  223.631,   24.98 ,   40.   ,  378.   ],
   [ 104.107,  224.177,   23.728,   41.   ,  378.   ],
   ..., 
   [ 127.778,  222.205,   23.123,   63.   ,  378.   ],
   [ 126.815,  222.347,   23.934,   64.   ,  378.   ],
   [ 127.824,  221.048,   25.508,   65.   ,  378.   ]]),...]

minimumCellCoors = cells
maximumCellCoors = cells
centoEdge = radius+fcr_size

Now i want to change the coordinates x, y and z, so the 0.,1. and 2. element of the arrays in the list to get them in a specific grid. The user gives the spacing for x,y and z and then the operation could look like:

 x_Coo=round(x_element/x)*x
 y_Coo=round(y_element/y)*y         
 z_Coo=round(z_element/z)*z

So the real question here is, how could i do a operation on all of the elements in the array ( or in this case the first three elements in the array in the list)?

EDIT

If i use list comprehension to the list like:

[np.round((cellID[:,0]-(centoEdge+1))/x)*x  for cellID in minimumCellCoors]
[np.round((cellID[:,1]-(centoEdge+1))/y)*y  for cellID in minimumCellCoors]
[np.round((cellID[:,2]-(centoEdge+1))/z)*z  for cellID in minimumCellCoors]

[np.round((cellID[:,0]+(centoEdge+1))/x)*x  for cellID in maximumCellCoors]
[np.round((cellID[:,1]+(centoEdge+1))/x)*y  for cellID in maximumCellCoors]
[np.round((cellID[:,2]+(centoEdge+1))/x)*z  for cellID in maximumCellCoors]

How could i fusion the single lists of arrays to one array again?

Best regards!

Can you please provide some usable data, this looks a cutoff of your print? — zipa
– zipa, Commented May 9, 2017 at 9:24

Kasravnd · Accepted Answer · 2017-05-09 09:25:35Z

1

First off you need to convert your list to a numpy array. It's more proper to create a numpy array instead of a list at first place. Then you can take advantage of numpy's vectorized operation support:

Here is an example:

In [45]: arr = np.arange(100).reshape(4, 5, 5)

In [46]: arr
Out[46]: 
array([[[ 0,  1,  2,  3,  4],
        [ 5,  6,  7,  8,  9],
        [10, 11, 12, 13, 14],
        [15, 16, 17, 18, 19],
        [20, 21, 22, 23, 24]],

       [[25, 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]]])


In [51]: arr[:,:,:3] = np.round(arr[:,:,:3]/5)*5 

In [52]: arr
Out[52]: 
array([[[ 0,  0,  0,  3,  4],
        [ 5,  5,  5,  8,  9],
        [10, 10, 10, 13, 14],
        [15, 15, 15, 18, 19],
        [20, 20, 20, 23, 24]],

       [[25, 25, 25, 28, 29],
        [30, 30, 30, 33, 34],
        [35, 35, 35, 38, 39],
        [40, 40, 40, 43, 44],
        [45, 45, 45, 48, 49]],

       [[50, 50, 50, 53, 54],
        [55, 55, 55, 58, 59],
        [60, 60, 60, 63, 64],
        [65, 65, 65, 68, 69],
        [70, 70, 70, 73, 74]],

       [[75, 75, 75, 78, 79],
        [80, 80, 80, 83, 84],
        [85, 85, 85, 88, 89],
        [90, 90, 90, 93, 94],
        [95, 95, 95, 98, 99]]])

Note that you can also perform the operations with same length arrays as well as scalars:

For instance you could also do the following:

In [53]: arr[:,:,:3] = np.round(arr[:,:,:3]/5)*[4, 5, 6]

answered May 9, 2017 at 9:25

Kasravnd

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4 Comments

Varlor Over a year ago

Ok, nice. But how do i do this. There would be two possibilieties. I have my data in an array but it is not splitted for each cell. How can i do this. My approach was to create a list of arrays whenever a new cell id begins, but this seems to be not a good idea in relation to your answer. Is there another possibility to split my array whenever a new cell id begins without creating a list and get directly the shape of your array?

Kasravnd Over a year ago

@Varlor If the splitting doesn't return left an even result you won't be able to do this approach and probably you should go with the list and maybe at the best level using a list comprehension and changing the first 3 items.

Varlor Over a year ago

Ok if i use the list comprhension, how could i fusion them together after it, see edit :)

Kasravnd Over a year ago

@Varlor If they're not in the same size you can just convert them to and array by putting them in a list and passing to np.array() but if they are in the same shape you can use np.concatenate() to concatenate them along a specific axis. But if they are in same shape you'd go with the verctorized recipe ;)

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