linspace - Generate linearly spaced vector - MATLAB (original) (raw)

Generate linearly spaced vector

Syntax

Description

y = linspace([x1,x2](#bud27em-x1x2)) returns a row vector of evenly spaced points between x1 and x2. By default,linspace generates 100 points.

example

y = linspace([x1,x2](#bud27em-x1x2),[n](#bud27em-n)) generates n points. The spacing between the points is(x2-x1)/(n-1).

linspace is similar to the colon operator, “:”, but gives direct control over the number of points and always includes the endpoints. “lin” in the name “linspace” refers to generating linearly spaced values as opposed to the sibling function logspace, which generates logarithmically spaced values.

example

Examples

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Vector of Evenly Spaced Numbers

Create a vector of 100 evenly spaced points in the interval [-5,5].

Vector with Specified Number of Values

Create a vector of 7 evenly spaced points in the interval [-5,5].

y1 = 1×7

-5.0000 -3.3333 -1.6667 0 1.6667 3.3333 5.0000

Vector of Evenly Spaced Complex Numbers

Create a vector of complex numbers with 8 evenly spaced points between 1+2i and 10+10i.

y = linspace(1+2i,10+10i,8)

y = 1×8 complex

1.0000 + 2.0000i 2.2857 + 3.1429i 3.5714 + 4.2857i 4.8571 + 5.4286i 6.1429 + 6.5714i 7.4286 + 7.7143i 8.7143 + 8.8571i 10.0000 +10.0000i

Input Arguments

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x1,x2 — Point interval

pair of scalars

Point interval, specified as a pair of scalars. x1 andx2 define the interval over which linspace generates points. x2 can be either larger or smaller thanx1. If x2 is smaller than x1, then the vector contains descending values.

Data Types: single | double | datetime | duration
Complex Number Support: Yes

n — Number of points

100 (default) | real numeric scalar | NaN

Number of points, specified as a real numeric scalar orNaN.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

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™.

The linspace function supports GPU array input with these usage notes and limitations:

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™.

Usage notes and limitations:

For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a