minus, -

Subtraction

Syntax

C = A - B

C = minus(A,B)

Description

C = A - B subtracts array B from array A by subtracting corresponding elements. The sizes of A and B must be the same or be compatible.

If the sizes of A and B are compatible, then the two arrays implicitly expand to match each other. For example, if A or B is a scalar, then the scalar is combined with each element of the other array. Also, vectors with different orientations (one row vector and one column vector) implicitly expand to form a matrix.

C = minus(A,B) is an alternate way to execute A - B, but is rarely used. It enables operator overloading for classes.

Examples

Subtract Scalar from Array

Create an array, A, and subtract a scalar value from it.

A = [2 1; 3 5];
C = A - 2

C = 2×2

     0    -1
     1     3

The scalar is subtracted from each entry of A.

Subtract Two Arrays

Create two arrays, A and B, and subtract the second, B, from the first, A.

A = [1 0; 2 4];
B = [5 9; 2 1];
C = A - B

C = 2×2

    -4    -9
     0     3

The elements of B are subtracted from the corresponding elements of A.

Use the syntax -C to negate the elements of C.

-C

ans = 2×2

     4     9
     0    -3

Subtract Row and Column Vectors

Create a 1-by-2 row vector and 3-by-1 column vector and subtract them.

a = 1:2;
b = (1:3)';
a - b

ans = 3×2

     0     1
    -1     0
    -2    -1

The result is a 3-by-2 matrix, where each (i,j) element in the matrix is equal to a(j) - b(i):

$$\mathit{a}=\left[{\mathit{a}}_1{\mathit{a}}_2\right],\mathit{b}=\left[\begin{array}{c}{\mathit{b}}_1\\ {\mathit{b}}_2\\ {\mathit{b}}_3\end{array}\right],\mathit{a}-\mathit{b}=\left[\begin{array}{cc}{\mathit{a}}_1-{\mathit{b}}_1& {\mathit{a}}_2-{\mathit{b}}_1\\ {\mathit{a}}_1-{\mathit{b}}_2& {\mathit{a}}_2-{\mathit{b}}_2\\ {\mathit{a}}_1-{\mathit{b}}_3& {\mathit{a}}_2-{\mathit{b}}_3\end{array}\right].$$

Subtract Mean from Matrix

Create a matrix, A. Scale the elements in each column by subtracting the mean.

A = [1 9 3; 2 7 8]

A = 2×3

     1     9     3
     2     7     8

A - mean(A)

ans = 2×3

   -0.5000    1.0000   -2.5000
    0.5000   -1.0000    2.5000

Input Arguments

A, B — Operands

scalars | vectors | matrices | multidimensional arrays

Operands, specified as scalars, vectors, matrices, or multidimensional arrays. Inputs A and B must either be the same size or have sizes that are compatible (for example, A is an M-by-N matrix and B is a scalar or 1-by-N row vector). For more information, see Compatible Array Sizes for Basic Operations.

• Operands with an integer data type cannot be complex.

• If one input is a datetime array, duration array, or calendarDuration array, then numeric values in the other input are treated as a number of 24-hour days.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical | char | datetime | duration | calendarDuration
Complex Number Support: Yes

Extended Capabilities

Tall Arrays

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™.

Usage notes and limitations:

• If you use minus with single type and double type operands, the generated code might not produce the same result as MATLAB^®. See Binary Element-Wise Operations with Single and Double Operands (MATLAB Coder).

GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

• If you use minus with single type and double type operands, the generated code might not produce the same result as MATLAB. See Binary Element-Wise Operations with Single and Double Operands (MATLAB Coder).

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Usage notes and limitations:

• 64-bit integers are not supported.

For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

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 History

Introduced before R2006a

R2020b: Implicit expansion change affects calendarDuration, datetime, and duration arrays

Behavior changed in R2020b

Starting in R2020b, minus supports implicit expansion when the arguments are calendarDuration, datetime, or duration arrays. Between R2020a and R2016b, implicit expansion was supported only for numeric data types.

R2016b: Implicit expansion change affects arguments for operators

Behavior changed in R2016b

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 try/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.