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setxor

Exclusive OR of two sets of data

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Syntax

C = setxor(A,B)
C = setxor(A,B,setOrder)
C = setxor(A,B,___,'rows')
C = setxor(A,B,'rows',___)
[C,ia,ib] = setxor(___)
[C,ia,ib] = setxor(A,B,'legacy')
[C,ia,ib] = setxor(A,B,'rows','legacy')

Description

C = setxor(A,B) returns the data of A and B that are not in their intersection (the symmetric difference), with no repetitions. That is, setxor returns the data that occurs in A or B, but not both. C is in sorted order.

  • If A and B are tables or timetables, then setxor returns the rows that occur in one or the other of the two tables, but not both. For timetables, setxor takes row times into account to determine equality, and sorts the output timetable C by row times.

example

C = setxor(A,B,setOrder) returns C in a specific order. setOrder can be 'sorted' or 'stable'.

example

C = setxor(A,B,___,'rows') and C = setxor(A,B,'rows',___) treat each row of A and each row of B as single entities and returns the rows of A and B that are not in their intersection, with no repetitions. You must specify A and B and optionally can specify setOrder.

The 'rows' option does not support cell arrays, unless one of the inputs is either a categorical array or a datetime array.

[C,ia,ib] = setxor(___) also returns index vectors ia and ib using any of the previous syntaxes.

  • Generally, the values in C are a sorted combination of the elements of A(ia) and B(ib).

  • If the 'rows' option is specified, then C is a sorted combination of the rows of A(ia,:) and B(ib,:).

  • If A and B are tables or timetables, then C is a sorted combination of the rows of A(ia,:) and B(ib,:).

example

[C,ia,ib] = setxor(A,B,'legacy') and [C,ia,ib] = setxor(A,B,'rows','legacy') preserve the behavior of the setxor function from R2012b and prior releases.

The 'legacy' option does not support categorical arrays, datetime arrays, duration arrays, tables, or timetables.

example

Examples

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Open Live Script

Define two vectors with a value in common. 

A = [5 1 3 3 3]; B = [4 1 2];

Find the values of A and B that are not in their intersection. 

C = setxor(A,B)
C = 1×4

     2     3     4     5
Open Live Script

Define two tables with rows in common. 

A = table([1:5]',['A';'B';'C';'D';'E'],logical([0;1;0;1;0]))
A=5×3 table
    Var1    Var2    Var3 
    ____    ____    _____

     1       A      false
     2       B      true 
     3       C      false
     4       D      true 
     5       E      false


B = table([1:2:10]',['A';'C';'E';'G';'I'],logical(zeros(5,1)))
B=5×3 table
    Var1    Var2    Var3 
    ____    ____    _____

     1       A      false
     3       C      false
     5       E      false
     7       G      false
     9       I      false

Find the rows of A and B that are not in their intersection. 

C = setxor(A,B)
C=4×3 table
    Var1    Var2    Var3 
    ____    ____    _____

     2       B      true 
     4       D      true 
     7       G      false
     9       I      false
Open Live Script

Define two vectors with a value in common. 

A = [5 1 3 3 3]; B = [4 1 2];

Find the values of A and B that are not in their intersection as well as the index vectors ia and ib. 

[C,ia,ib] = setxor(A,B)
C = 1×4

     2     3     4     5


ia = 2×1

     3
     1


ib = 2×1

     3
     1

C is a sorted combination of the elements A(ia) and B(ib).

Open Live Script

Define a table, A, of gender, age, and height for five people. 

A = table(['M';'M';'F'],[27;52;31],[74;68;64],...
'VariableNames',{'Gender' 'Age' 'Height'},...
'RowNames',{'Ted' 'Fred' 'Betty'})
A=3×3 table
             Gender    Age    Height
             ______    ___    ______

    Ted        M       27       74  
    Fred       M       52       68  
    Betty      F       31       64

Define a table, B, with the same variables as A. 

B = table(['F';'M'],[64;68],[31;47],...
'VariableNames',{'Gender' 'Height' 'Age'},...
'RowNames',{'Meg' 'Joe'})
B=2×3 table
           Gender    Height    Age
           ______    ______    ___

    Meg      F         64      31 
    Joe      M         68      47

Find the rows of A and B that are not in their intersection, as well as the index vectors ia and ib. 

[C,ia,ib] = setxor(A,B)
C=3×3 table
            Gender    Age    Height
            ______    ___    ______

    Ted       M       27       74  
    Joe       M       47       68  
    Fred      M       52       68  


ia = 2×1

     1
     2


ib = 
2

C is a sorted combination of the elements A(ia,:) and B(ib,:).

Open Live Script

Define two matrices with rows in common. 

A = [7 8 9; 7 7 1; 7 7 1; 1 2 3; 4 5 6];
B = [1 2 3; 4 5 6; 7 7 2];

Find the rows of A and B that are not in their intersection as well as the index vectors ia and ib. 

[C,ia,ib] = setxor(A,B,'rows')
C = 3×3

     7     7     1
     7     7     2
     7     8     9


ia = 2×1

     2
     1


ib = 
3

C is a sorted combination of the rows of A(ia,:) and B(ib,:).

Open Live Script

Use the setOrder argument to specify the ordering of the values in C.

Specify 'stable' if you want the values in C to have the same order as A and B. 

A = [5 1 3 3 3]; B = [4 1 2];
[C,ia,ib] = setxor(A,B,'stable')
C = 1×4

     5     3     4     2


ia = 2×1

     1
     3


ib = 2×1

     1
     3

Alternatively, you can specify 'sorted' order. 

[C,ia,ib] = setxor(A,B,'sorted')
C = 1×4

     2     3     4     5


ia = 2×1

     3
     1


ib = 2×1

     3
     1
Open Live Script

Define two vectors containing NaN. 

A = [5 NaN NaN]; B = [5 NaN NaN];

Find the symmetric difference of vectors A and B. 

C = setxor(A,B)
C = 1×4

   NaN   NaN   NaN   NaN

The setxor function treats NaN values as distinct.

Open Live Script

Create a cell array of character vectors, A. 

A = {'dog','cat','fish','horse'};

Create a cell array of character vectors, B, where some of the vectors have trailing white space.

B = {'dog ','cat','fish ','horse'};

Find the character vectors that are not in the intersection of A and B.

[C,ia,ib] = setxor(A,B)
C = 1x4 cell
    {'dog'}    {'dog '}    {'fish'}    {'fish '}


ia = 2×1

     1
     3


ib = 2×1

     1
     3

setxor treats trailing white space in cell arrays of character vectors as distinct characters.

Open Live Script

Create a column vector character array. 

A = ['A';'B';'C'], class(A)
A = 3x1 char array
    'A'
    'B'
    'C'


ans = 
'char'

Create a row vector containing elements of numeric type double. 

B = [66 67 68], class(B)
B = 1×3

    66    67    68


ans = 
'double'

Find the symmetric difference of A and B. 

C = setxor(A,B)
C = 2x1 char array
    'A'
    'D'

The result is a column vector character array. 

class(C)
ans = 
'char'
Open Live Script

Create a character vector, A. 

A = ['cat';'dog';'fox';'pig'];
class(A)
ans = 
'char'

Create a cell array of character vectors, B. 

B={'dog','cat','fish','horse'};
class(B)
ans = 
'cell'

Find the character vectors that are not in the intersection of A and B.

C = setxor(A,B)
C = 4x1 cell
    {'fish' }
    {'fox'  }
    {'horse'}
    {'pig'  }

The result, C, is a cell array of character vectors. 

class(C)
ans = 
'cell'
Open Live Script

Use the 'legacy' flag to preserve the behavior of setxor from R2012b and prior releases in your code.

Find the symmetric difference of A and B with the current behavior. 

A = [5 1 3 3 3]; B = [4 1 2 2];
[C1,ia1,ib1] = setxor(A,B)
C1 = 1×4

     2     3     4     5


ia1 = 2×1

     3
     1


ib1 = 2×1

     3
     1

Find the symmetric difference and preserve the legacy behavior. 

[C2,ia2,ib2] = setxor(A,B,'legacy')
C2 = 1×4

     2     3     4     5


ia2 = 1×2

     5     1


ib2 = 1×2

     4     1

Input Arguments

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Input arrays. If you specify the 'rows' option, then A and B must have the same number of columns.

A and B must belong to the same class with the following exceptions:

  • logical, char, and all numeric classes can combine with double arrays.

  • String arrays can combine with character vectors and cell arrays of character vectors.

  • Categorical arrays can combine with string scalars and character vectors.

  • Datetime and duration arrays can combine with string scalars and character vectors that are formatted to represent dates and times.

There are additional requirements for A and B based on data type:

  • If A and B are both ordinal categorical arrays, they must have the same sets of categories, including their order. If neither A nor B are ordinal, they need not have the same sets of categories, and the comparison is performed using the category names. In this case, the categories of C consist of the categories of A followed by the categories of B that are not in A. The categories are in the same order as in A and B, and the category order is used for sorting C.

  • If A and B are tables or timetables, they must have the same variable names (except for order). For tables, row names are ignored, so that two rows that have the same values, but different names, are considered equal. For timetables, row times are taken into account, so that two rows that have the same values, but different times, are not considered equal.

  • If A and B are datetime arrays, then both arrays must either specify time zones or be unzoned.

A and B also can be objects with the following class methods:

  • sort (or sortrows for the 'rows' option)

  • eq

  • ne

The object class methods must be consistent with each other. These objects include heterogeneous arrays derived from the same root class. For example, A and B can be arrays of handles to graphics objects.

Order flag, specified as 'sorted' or 'stable', indicates the order of the values (or rows) in C.

FlagDescription
'sorted'

The values (or rows) in C return in sorted order as returned by sort.

Example

C = setxor([5 1 3],[4 1 2],'sorted')
C =

     2     3     4     5

'stable'

The values (or rows) in C return in the same order as they appear in A, then B.

Example

C = setxor([5 1 3],[4 1 2],'stable')
C =

     5     3     4     2

Data Types: char | string

Output Arguments

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Symmetric difference array, returned as a vector, matrix, table, or timetable. If the inputs A and B are tables or timetables, then the order of the variables in C is the same as the order of the variables in A.

The following describes the shape of C when the inputs are vectors or matrices and when the 'legacy' flag is not specified:

  • If the 'rows' flag is not specified, then C is a column vector unless both A and B are row vectors, in which case C is a row vector. For example, setxor([],[1 2]) returns a column vector.

  • If the'rows' flag is specified, then C is a matrix containing the rows of A and B that are not in the intersection.

  • If all the values (or rows) of A are also in B, then C is empty.

The class of the inputs A and B determines the class of C:

  • If the class of A and B are the same, then C is the same class.

  • If you combine a char or nondouble numeric class with double, then C is the same class as the nondouble input.

  • If you combine a logical class with double, then C is double.

  • If you combine a cell array of character vectors with char, then C is a cell array of character vectors.

  • If you combine a categorical array with a character vector, cell array of character vectors, or string, then C is a categorical array.

  • If you combine a datetime array with a cell array of date character vectors or single date character vector, then C is a datetime array.

  • If you combine a string array with a character vector or cell array of character vectors, then C is a string array.

Index to A, returned as a column vector when the 'legacy' flag is not specified. ia identifies the values (or rows) in A that contribute to the symmetric difference. If there is a repeated value (or row) appearing exclusively in A, then ia contains the index to the first occurrence of the value (or row).

Index to B, returned as a column vector when the 'legacy' flag is not specified. ib identifies the values (or rows) in B that contribute to the symmetric difference. If there is a repeated value (or row) appearing exclusively in B, then ib contains the index to the first occurrence of the value (or row).

Tips

  • To find the symmetric difference with respect to a subset of variables from a table or timetable, you can use column subscripting. For example, you can use setxor(A(:,vars),B(:,vars)), where vars is a positive integer, a vector of positive integers, a variable name, a cell array of variable names, or a logical vector. Alternatively, you can use vartype to create a subscript that selects variables of a specified type.

Extended Capabilities

Version History

Introduced before R2006a

See Also

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