Add column to a matrix

Hello, I wanted to ask about how you might concatenate two vectors or matrices under conditions , ie comparing the elements. For example I have a matrix such that:

a =

         0
    1.0000
    2.0000
    2.4000
    2.5000
    3.0000
    3.5000
    4.8000
    5.0000
    5.5000

and another:

b =

         0 1.0000
    2.4000 2.0000
    4.8000 3.0000

And I want to have such a result that :

result =

         0 1.0000
    1.0000 1.0000
    2.0000 1.0000
    2.4000 2.0000
    2.5000 2.0000
    3.0000 2.0000
    3.5000 2.0000
    4.8000 3.0000
    5.0000 3.0000
    5.5000 3.0000

That is, comparing with the first column of b assign the value 1, 2,3 .. depending on whether the value is greater or is between two numeros.Por example 2.4 is greater and equal to the second element b but less the third and so .... Thanks in advanced.

[Mario Martos]

Hello, first thanks . What I 'm looking for is that when comparing the elements of the two vectors , for example when a (2) = 1.0000 is between the interval b(1) = 0 and b (2) = 2.4 in that row add a column value of 1 as it is between that range. That is, if the condition is met , for example a(2) is greater than or equal b(1) and less than b(2) corresponds to the first interval 1 comparing all elements of the row of the two matrices fulfilled those conditions

Answer 1

[Andrei Bobrov]

a =[     0
    1.0000
    2.0000
    2.4000
    2.5000
    3.0000
    3.5000
    4.8000
    5.0000
    5.5000];

b =[      0 1.0000
    2.4000 2.0000
    4.8000 3.0000];

out = [a, b(cumsum(ismember(a,b(:,1))),2)]

or

[~,ii] = histc(a,[b(:,1);inf]);
out = [a, b(ii,2)]

[Mario Martos]

Hello, first thanks . What I 'm looking for is that when comparing the elements of the two vectors , for example when a (2) = 1.0000 is between the interval b(1) = 0 and b (2) = 2.4 in that row add a column value of 1 as it is between that range. That is, if the condition is met , for example a(2) is greater than or equal b(1) and less than b(2) corresponds to the first interval 1 comparing all elements of the row of the two matrices fulfilled those conditions

[Andrei Bobrov]

see after word 'or'

[Mario Martos]

Hello again, I do not know why when I will run the process with larger matrices (length (b) = 25 and length (a = 684) ) makes me : out = [a, b ( cumSum ( IsMember (a, b ( : , 1) ) ) , 2) ] Index Exceeds matrix dimensions .

Why?

[Andrei Bobrov]

I do not know, I do not see your data

[Mario Martos]

my data would be the nmat matrix (Interested in column 6 are the data shown in column 1 of the Bach matrix.) to which I want to add the column compared with the Bach matrix are as follows :

nmat =

0         0.9979    3.0000   62.0000   75.0000         0    0.5987
0.5000    0.2479    1.0000   78.0000   75.0000    0.3000    0.1487
0.5000    0.2479    2.0000   78.0000   75.0000    0.3000    0.1487
0.7500    0.2479    1.0000   79.0000   75.0000    0.4500    0.1487
0.7500    0.2479    2.0000   79.0000   75.0000    0.4500    0.1487
1.0000    0.4979    1.0000   81.0000   75.0000    0.6000    0.2988
1.0000    0.4979    2.0000   81.0000   75.0000    0.6000    0.2988
1.5000    0.4979    1.0000   72.0000   75.0000    0.9000    0.2988
1.5000    0.4979    2.0000   72.0000   75.0000    0.9000    0.2988
1.5000    0.4979    3.0000   54.0000   75.0000    0.9000    0.2988
2.0000    0.4979    1.0000   71.0000   75.0000    1.2000    0.2988
2.0000    0.4979    2.0000   71.0000   75.0000    1.2000    0.2988
2.0000    0.9979    3.0000   55.0000   75.0000    1.2000    0.5987
2.5000    0.2479    1.0000   76.0000   75.0000    1.5000    0.1487
2.5000    0.2479    2.0000   76.0000   75.0000    1.5000    0.1487
2.7500    0.2479    1.0000   78.0000   75.0000    1.6500    0.1487
2.7500    0.2479    2.0000   78.0000   75.0000    1.6500    0.1487
3.0000    0.4979    1.0000   79.0000   75.0000    1.8000    0.2988
3.0000    0.4979    2.0000   79.0000   75.0000    1.8000    0.2988
3.5000    0.4979    1.0000   71.0000   75.0000    2.1000    0.2988
3.5000    0.4979    2.0000   71.0000   75.0000    2.1000    0.2988
3.5000    0.4979    3.0000   52.0000   75.0000    2.1000    0.2988
4.0000    0.4979    1.0000   69.0000   75.0000    2.4000    0.2988
4.0000    0.9979    3.0000   54.0000   75.0000    2.4000    0.5988
4.5000    0.2479    1.0000   74.0000   75.0000    2.7000    0.1488
4.7500    0.2479    1.0000   76.0000   75.0000    2.8500    0.1488
5.0000    0.4979    1.0000   78.0000   75.0000    3.0000    0.2988
5.5000    0.4979    1.0000   69.0000   75.0000    3.3000    0.2988
5.5000    0.4979    3.0000   50.0000   75.0000    3.3000    0.2988
6.0000    0.2479    1.0000   67.0000   75.0000    3.6000    0.1488
6.0000    0.4979    3.0000   59.0000   75.0000    3.6000    0.2988
6.2500    0.2479    1.0000   78.0000   75.0000    3.7500    0.1488
6.5000    0.2479    1.0000   76.0000   75.0000    3.9000    0.1488
6.5000    0.4979    3.0000   55.0000   75.0000    3.9000    0.2987
6.7500    0.2479    1.0000   74.0000   75.0000    4.0500    0.1487
7.0000    0.2479    1.0000   73.0000   75.0000    4.2000    0.1487
7.0000    0.4979    3.0000   57.0000   75.0000    4.2000    0.2987
7.2500    0.2479    1.0000   83.0000   75.0000    4.3500    0.1487
7.5000    0.2479    1.0000   81.0000   75.0000    4.5000    0.1487
7.5000    0.4979    3.0000   45.0000   75.0000    4.5000    0.2987
7.7500    0.2479    1.0000   79.0000   75.0000    4.6500    0.1487
8.0000    0.2479    1.0000   78.0000   62.0000    4.8000    0.1487
8.0000    0.4979    3.0000   50.0000   75.0000    4.8000    0.2987
8.2500    0.2479    1.0000   76.0000   62.0000    4.9500    0.1487
8.5000    0.2479    1.0000   74.0000   62.0000    5.1000    0.1487
8.5000    0.4979    3.0000   62.0000   75.0000    5.1000    0.2987
8.7500    0.2479    1.0000   76.0000   62.0000    5.2500    0.1487
9.0000    0.2479    1.0000   78.0000   62.0000    5.4000    0.1487
9.0000    0.4979    3.0000   61.0000   75.0000    5.4000    0.2987
9.2500    0.2479    1.0000   76.0000   62.0000    5.5500    0.1487
9.5000    0.2479    1.0000   78.0000   62.0000    5.7000    0.1487
9.5000    0.4979    3.0000   59.0000   75.0000    5.7000    0.2987
9.7500    0.2479    1.0000   80.0000   62.0000    5.8500    0.1487
10.0000    0.2479    3.0000   57.0000   75.0000    6.0000    0.1487
10.0000    0.9979    1.0000   81.0000   62.0000    6.0000    0.5987
10.2500    0.2479    3.0000   56.0000   75.0000    6.1500    0.1487
10.5000    0.2479    2.0000   73.0000   75.0000    6.3000    0.1487
10.5000    0.2479    3.0000   57.0000   75.0000    6.3000    0.1487
10.7500    0.2479    2.0000   74.0000   75.0000    6.4500    0.1487
10.7500    0.2479    3.0000   59.0000   75.0000    6.4500    0.1487
11.0000    0.2479    3.0000   61.0000   75.0000    6.6000    0.1487
11.0000    0.4979    2.0000   76.0000   75.0000    6.6000    0.2987
11.0000    1.9979    1.0000   76.0000   62.0000    6.6000    1.1987
11.2500    0.2479    3.0000   62.0000   75.0000    6.7500    0.1487
11.5000    0.2479    3.0000   61.0000   75.0000    6.9000    0.1487
11.5000    0.4979    2.0000   67.0000   75.0000    6.9000    0.2987

y Bach:

Bach =

         0    1.0000
    2.4000    2.0000
    4.8000    3.0000

[Mario Martos]

Using the second method :

[ ~ , ii ] = histc ( nmat [ Bach ( : , 1) ; inf ] ) ;

out = [ nmat , Bach (ii, 2)]

Error using horzcat Dimensions of arrays being concatenated are not consistent .

[Andrei Bobrov]

[~,ii] = histc(nmat(:,6), [Bach(:,1);inf]);
out = [nmat, Bach(ii,2)];

or (R2015a and later)

out = [nmat, discretize(nmat(:,6),[Bach(:,1);inf],Bach(:,2))];

[Mario Martos]

And if I work, many thanks! and apology for the inconvenience