trapz

Trapezoidal numerical integration

Syntax

Q = trapz(Y)

Q = trapz(X,Y)

Q = trapz(___,dim)

Description

Q = trapz(Y) computes the approximate integral of Y via the trapezoidal method with unit spacing. The size of Y determines the dimension to integrate along:

• If Y is a vector, then trapz(Y) is the approximate integral of Y.

• If Y is a matrix, then trapz(Y) integrates over each column and returns a row vector of integration values.

• If Y is a multidimensional array, then trapz(Y) integrates over the first dimension whose size does not equal 1. The size of this dimension becomes 1, and the sizes of other dimensions remain unchanged.

Q = trapz(X,Y) integrates Y with respect to the coordinates or scalar spacing specified by X.

• If X is a vector of coordinates, then length(X) must be equal to the size of the first dimension of Y whose size does not equal 1.

• If X is a scalar spacing, then trapz(X,Y) is equivalent to X*trapz(Y).

Q = trapz(___,dim) integrates along the dimension dim using any of the previous syntaxes. You must specify Y, and optionally can specify X. If you specify X, then it can be a scalar or a vector with length equal to size(Y,dim). For example, if Y is a matrix, then trapz(X,Y,2) integrates each row of Y.

Examples

Integrate Vector of Data with Unit Spacing

Calculate the integral of a vector where the spacing between data points is 1.

Create a numeric vector of data.

Y = [1 4 9 16 25];

Y contains function values for $$f(x)=x^2$$ in the domain [1, 5].

Use trapz to integrate the data with unit spacing.

Q = trapz(Y)

Q = 
42

This approximate integration yields a value of 42. In this case, the exact answer is a little less, $$41\frac{1}{3}$$. The trapz function overestimates the value of the integral because f(x) is concave up.

Integrate Vector of Data with Nonunit Spacing

Calculate the integral of a vector where the spacing between data points is uniform, but not equal to 1.

Create a domain vector.

X = 0:pi/100:pi;

Calculate the sine of X.

Y = sin(X);

Integrate Y using trapz.

Q = trapz(X,Y)

Q = 
1.9998

When the spacing between points is constant, but not equal to 1, an alternative to creating a vector for X is to specify the scalar spacing value. In that case, trapz(pi/100,Y) is the same as pi/100*trapz(Y).

Integrate Matrix with Nonuniform Spacing

Integrate the rows of a matrix where the data has a nonuniform spacing.

Create a vector of x-coordinates and a matrix of observations that take place at the irregular intervals. The rows of Y represent velocity data, taken at the times contained in X, for three different trials.

X = [1 2.5 7 10];
Y = [5.2   7.7   9.6   13.2;
     4.8   7.0  10.5   14.5;
     4.9   6.5  10.2   13.8];

Use trapz to integrate each row independently and find the total distance traveled in each trial. Since the data is not evaluated at constant intervals, specify X to indicate the spacing between the data points. Specify dim = 2 since the data is in the rows of Y.

Q1 = trapz(X,Y,2)

Q1 = 3×1

   82.8000
   85.7250
   82.1250

The result is a column vector of integration values, one for each row in Y.

Multiple Numerical Integrations

Create a grid of domain values.

x = -3:.1:3; 
y = -5:.1:5; 
[X,Y] = meshgrid(x,y);

Calculate the function $$f(x,y)=x^2+y^2$$ on the grid.

F = X.^2 + Y.^2;

trapz integrates numeric data rather than functional expressions, so in general the expression does not need to be known to use trapz on a matrix of data. In cases where the functional expression is known, you can instead use integral, integral2, or integral3.

Use trapz to approximate the double integral

$$I={\int }_{-5}^5{\int }_{-3}^3(x^2+y^2)dxdy$$

To perform double or triple integrations on an array of numeric data, nest function calls to trapz.

I = trapz(y,trapz(x,F,2))

I = 
680.2000

trapz performs the integration over x first, producing a column vector. Then, the integration over y reduces the column vector to a single scalar. trapz slightly overestimates the exact answer of 680 because f(x,y) is concave up.

Input Arguments

Y — Numeric data

vector | matrix | multidimensional array

Numeric data, specified as a vector, matrix, or multidimensional array. By default, trapz integrates along the first dimension of Y whose size does not equal 1.

Data Types: single | double
Complex Number Support: Yes

X — Point spacing

1 (default) | uniform scalar spacing | vector of coordinates

Point spacing, specified as 1 (default), a uniform scalar spacing, or a vector of coordinates.

• If X is a scalar, then it specifies a uniform spacing between the data points and trapz(X,Y) is equivalent to X*trapz(Y).

• If X is a vector, then it specifies x-coordinates for the data points and length(X) must be the same as the size of the integration dimension in Y.

Data Types: single | double

dim — Dimension to operate along

positive integer scalar

Dimension to operate along, specified as a positive integer scalar. If you do not specify the dimension, then the default is the first array dimension whose size does not equal 1.

Consider a two-dimensional input array, Y:

• trapz(Y,1) works on successive elements in the columns of Y and returns a row vector.

  

• trapz(Y,2) works on successive elements in the rows of Y and returns a column vector.

  

If dim is greater than ndims(Y), then trapz returns an array of zeros of the same size as Y.

More About

Trapezoidal Method

trapz performs numerical integration via the trapezoidal method. This method approximates the integration over an interval by breaking the area down into trapezoids with more easily computable areas. For example, here is a trapezoidal integration of the sine function using eight evenly-spaced trapezoids:

For an integration with N+1 evenly spaced points, the approximation is

$$\begin{array}{c}{\displaystyle \underset{a}{\overset{b}{\int }}f\left(x\right)dx\approx }\frac{b-a}{2N}{\displaystyle \sum _{n=1}^N\left(f\left(x_n\right)+f\left(x_{n+1}\right)\right)}\\ =\frac{b-a}{2N}\left[f\left(x_1\right)+2f\left(x_2\right)+\mathrm{...}+2f\left(x_N\right)+f\left(x_{N+1}\right)\right],\end{array}$$

where the spacing between each point is equal to the scalar value $$\frac{b-a}{N}$$. By default MATLAB^® uses a spacing of 1.

If the spacing between the N+1 points is not constant, then the formula generalizes to

$${\displaystyle \underset{a}{\overset{b}{\int }}f\left(x\right)dx\approx \frac{1}{2}{\displaystyle \sum _{n=1}^N\left(x_{n+1}-x_n\right)}}\left[f\left(x_n\right)+f\left(x_{n+1}\right)\right],$$

where $$a=x_1<x_2<\mathrm{...}<x_N<x_{N+1}=b$$, and $$\left(x_{n+1}-x_n\right)$$ is the spacing between each consecutive pair of points.

Tips

• Use trapz and cumtrapz to perform numerical integrations on discrete data sets. Use integral, integral2, or integral3 instead if a functional expression for the data is available.

• trapz reduces the size of the dimension it operates on to 1, and returns only the final integration value. cumtrapz also returns the intermediate integration values, preserving the size of the dimension it operates on.

Extended Capabilities

C/C++ Code Generation

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

Usage notes and limitations:

• If you supply dim, then it must be a constant.

• See Variable-Sizing Restrictions for Code Generation of Toolbox Functions (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™.

The trapz function fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray (Parallel Computing Toolbox). 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