Find logical OR
performs a logical OR of
B and returns an array or a table
containing elements set to either logical
true) or logical
false). An element of the output is set to logical
true) if either
B contain a nonzero element at that same location. Otherwise,
the element is set to
For bit-wise logical OR operations, see
Locate Zeros in Matrices
Find the logical OR of two matrices. The result contains logical
true) where either matrix contains a nonzero value. The zeros in the result indicate spots where both arrays have a value of zero.
A = [5 7 0; 0 2 9; 5 0 0]
A = 3×3 5 7 0 0 2 9 5 0 0
B = [6 6 0; 1 3 5; -1 0 0]
B = 3×3 6 6 0 1 3 5 -1 0 0
A | B
ans = 3x3 logical array 1 1 0 1 1 1 1 0 0
Truth Table for Logical OR
Create a truth table for
A = [true false]
A = 1x2 logical array 1 0
B = [true; false]
B = 2x1 logical array 1 0
C = A|B
C = 2x2 logical array 1 1 1 0
Logical OR of Tables
Create two tables and perform a logical OR of them. The row names (if present in both) and variable names must be the same, but do not need to be in the same orders. Rows and variables of the output are in the same orders as the first input.
A = table([0;2],[0;4],VariableNames=["V1","V2"],RowNames=["R1","R2"])
A=2×2 table V1 V2 __ __ R1 0 0 R2 2 4
B = table([4;2],[3;0],VariableNames=["V2","V1"],RowNames=["R2","R1"])
B=2×2 table V2 V1 __ __ R2 4 3 R1 2 0
A | B
ans=2×2 table V1 V2 _____ _____ R1 false true R2 true true
B — Operands
scalars | vectors | matrices | multidimensional arrays | tables | timetables
Operands, specified as scalars, vectors, matrices, multidimensional
arrays, tables, or timetables. Inputs
B must either be the same size or have sizes that are
compatible (for example,
A is an
N matrix and
B is a scalar or
N row vector). For more
information, see Compatible Array Sizes for Basic Operations.
Inputs that are tables or timetables must meet the following conditions: (since R2023a)
If an input is a table or timetable, then all its variables must have data types that support the operation.
If only one input is a table or timetable, then the other input must be a numeric or logical array.
If both inputs are tables or timetables, then:
Both inputs must have the same size, or one of them must be a one-row table.
Both inputs must have variables with the same names. However, the variables in each input can be in a different order.
If both inputs are tables and they both have row names, then their row names must be the same. However, the row names in each input can be in a different order.
If both inputs are timetables, then their row times must be the same. However, the row times in each input can be in a different order.
You can chain together several logical operations, for example,
A & B | C.
||perform different operations in MATLAB®. The element-wise OR operator described here is
|. The short-circuit OR operator is
When you use the element-wise
|operators in the context of an
whileloop expression (and only in that context), they use short-circuiting to evaluate expressions. Otherwise, you must specify
||to opt-in to short-circuiting behavior. See
Short-Circuit ORfor more information.
Calculate with arrays that have more rows than fit in memory.
This function fully supports tall arrays. For more information, see Tall Arrays.
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.
HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.
Run code in the background using MATLAB®
backgroundPool or accelerate code with Parallel Computing Toolbox™
This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.
This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).
Version HistoryIntroduced before R2006a
R2023a: Perform operations directly on tables and timetables
or operator supports operations directly on tables and
timetables without indexing to access their variables. All variables must have data types
that support the operation. For more information, see Direct Calculations on Tables and Timetables.
R2016b: Implicit expansion change affects arguments for operators
Starting in R2016b with the addition of implicit expansion, some combinations of arguments for basic operations that previously returned errors now produce results. For example, you previously could not add a row and a column vector, but those operands are now valid for addition. In other words, an expression like
[1 2] + [1; 2] previously returned a size mismatch error, but now it executes.
If your code uses element-wise operators and relies on the errors that MATLAB previously returned for mismatched sizes, particularly within a
catch block, then your code might no longer catch those errors.
For more information on the required input sizes for basic array operations, see Compatible Array Sizes for Basic Operations.