expint
Exponential integral function
Syntax
Description
evaluates
the exponential
integral for each element of Y
= expint(X
)X
.
Examples
Compute Exponential Integral
Plot Exponential Integral
Plot the exponential integral for X
in the interval of [0,10]
.
X = 0:0.01:10; Y = expint(X); plot(X,Y) axis([-1 10 -0.5 4]) xlabel('$x$','interpreter','latex') ylabel('$E_1(x)$','interpreter','latex') title('Exponential Integral','interpreter','latex')
Input Arguments
X
— Input array
scalar | vector | matrix | multidimensional array
Input array, specified as a scalar, vector, matrix, or multidimensional array.
Data Types: single
| double
Complex Number Support: Yes
More About
Exponential Integral
The exponential integral of x is defined as
By analytic continuation, expint
is a scalar-valued function in the
complex plane cut along the negative real axis.
There is a different function that is sometimes called the exponential integral: the Cauchy principal value integral
which, for positive real x, is related to expint
as
References
[1] Abramowitz, M. and I. A. Stegun. Handbook of Mathematical Functions. Chapter 5, New York: Dover Publications, 1965.
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™.
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™.
This function fully supports GPU arrays. 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
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