Adding specific elements in a vector

I have the following vector "a", where the values in the first column are the duration of rainfall and the values in the second column are the amount of rainfall.

a =

    1.0000   71.8700
    2.0000  136.1100
    3.0000   85.3200
    4.0000  139.1300
    5.0000  127.1900
    6.0000   70.5400
    7.0000   76.8900
    8.0000  113.1700
    9.0000   52.8000
   10.0000   29.6300
   11.0000   23.5300
   12.0000   99.7300
   13.0000   46.6200
   14.0000   78.9300
   15.0000   68.8000
   16.0000   35.7400
   17.0000   83.0200
   18.0000  105.4000
   19.0000   15.7200
   20.0000   13.6600
   21.0000   48.9600
   22.0000   43.8700
   23.0000    6.8100
   24.0000   39.3100
   25.0000   22.5900
   27.0000   77.1500
   29.0000   45.1900
   30.0000   17.2500
   34.0000   11.1600
   38.0000   32.1900

I would like to sum the amount of rainfall for the duration 1-2h, 21-24h and 25-38h. The results should look like:

   a =

    1-2     207.9800
    3.0000   85.3200
    4.0000  139.1300
    5.0000  127.1900
    6.0000   70.5400
    7.0000   76.8900
    8.0000  113.1700
    9.0000   52.8000
   10.0000   29.6300
   11.0000   23.5300
   12.0000   99.7300
   13.0000   46.6200
   14.0000   78.9300
   15.0000   68.8000
   16.0000   35.7400
   17.0000   83.0200
   18.0000  105.4000
   19.0000   15.7200
   20.0000   13.6600
   21-24    138.9500
   25-38    205.5300

Answer 1

[Matt J]

e=1:max(a(:,1))+1;
e([2,22:24,26:38])=[];

G=discretize(a(:,1),e);

result=accumarray(G,a(:,2))

[Queena Edwards]

Thank you. This works!!!

Answer 2

[Cris LaPierre]

I would use groupsummary with defined bin edges of [1,3:21,25,38].

a = [1.0000   71.8700
    2.0000  136.1100
    3.0000   85.3200
    4.0000  139.1300
    5.0000  127.1900
    6.0000   70.5400
    7.0000   76.8900
    8.0000  113.1700
    9.0000   52.8000
   10.0000   29.6300
   11.0000   23.5300
   12.0000   99.7300
   13.0000   46.6200
   14.0000   78.9300
   15.0000   68.8000
   16.0000   35.7400
   17.0000   83.0200
   18.0000  105.4000
   19.0000   15.7200
   20.0000   13.6600
   21.0000   48.9600
   22.0000   43.8700
   23.0000    6.8100
   24.0000   39.3100
   25.0000   22.5900
   27.0000   77.1500
   29.0000   45.1900
   30.0000   17.2500
   34.0000   11.1600
   38.0000   32.1900];

[B,BG] = groupsummary(a(:,2),a(:,1),[1,3:21,25,38],'sum');
aGrp = table(BG,B)

aGrp = 21×2 table
       BG         B   
    ________    ______

    [1, 3)      207.98
    [3, 4)       85.32
    [4, 5)      139.13
    [5, 6)      127.19
    [6, 7)       70.54
    [7, 8)       76.89
    [8, 9)      113.17
    [9, 10)       52.8
    [10, 11)     29.63
    [11, 12)     23.53
    [12, 13)     99.73
    [13, 14)     46.62
    [14, 15)     78.93
    [15, 16)      68.8
    [16, 17)     35.74
    [17, 18)     83.02

I prefer working with tables, so I would actually do it this way. You may find the Access Data in Tables page helpful.

A = array2table(a,'VariableNames',{'Duration','Amount'})

A = 30×2 table
    Duration    Amount
    ________    ______

        1        71.87
        2       136.11
        3        85.32
        4       139.13
        5       127.19
        6        70.54
        7        76.89
        8       113.17
        9         52.8
       10        29.63
       11        23.53
       12        99.73
       13        46.62
       14        78.93
       15         68.8
       16        35.74

AGrp = groupsummary(A,'Duration',[1,3:21,25,38],'sum','Amount')

AGrp = 21×3 table
    disc_Duration    GroupCount    sum_Amount
    _____________    __________    __________

      [1, 3)             2           207.98  
      [3, 4)             1            85.32  
      [4, 5)             1           139.13  
      [5, 6)             1           127.19  
      [6, 7)             1            70.54  
      [7, 8)             1            76.89  
      [8, 9)             1           113.17  
      [9, 10)            1             52.8  
      [10, 11)           1            29.63  
      [11, 12)           1            23.53  
      [12, 13)           1            99.73  
      [13, 14)           1            46.62  
      [14, 15)           1            78.93  
      [15, 16)           1             68.8  
      [16, 17)           1            35.74  
      [17, 18)           1            83.02  

[Queena Edwards]

Thank you. This works great as well!