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NAG Library Manual

# NAG Library Routine DocumentS10AAF

Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

## 1  Purpose

S10AAF returns a value for the hyperbolic tangent, $\mathrm{tanh}x$, via the function name.

## 2  Specification

 FUNCTION S10AAF ( X, IFAIL)
 REAL (KIND=nag_wp) S10AAF
 INTEGER IFAIL REAL (KIND=nag_wp) X

## 3  Description

S10AAF calculates an approximate value for the hyperbolic tangent of its argument, $\mathrm{tanh}x$.
For $\left|x\right|\le 1$ it is based on the Chebyshev expansion
 $tanh⁡x=x×yt=x∑′r=0arTrt$
where $-1\le x\le 1\text{, }-1\le t\le 1\text{, and }t=2{x}^{2}-1$.
For $1<\left|x\right|<{E}_{1}$ (see the Users' Note for your implementation for value of ${E}_{1}$)
 $tanh⁡x=e2x-1 e2x+1 .$
For $\left|x\right|\ge {E}_{1}$, $\mathrm{tanh}x=\mathrm{sign}x$ to within the representation accuracy of the machine and so this approximation is used.

## 4  References

Abramowitz M and Stegun I A (1972) Handbook of Mathematical Functions (3rd Edition) Dover Publications

## 5  Parameters

1:     X – REAL (KIND=nag_wp)Input
On entry: the argument $x$ of the function.
2:     IFAIL – INTEGERInput/Output
On entry: IFAIL must be set to $0$, $-1\text{​ or ​}1$. If you are unfamiliar with this parameter you should refer to Section 3.3 in the Essential Introduction for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value $-1\text{​ or ​}1$ is recommended. If the output of error messages is undesirable, then the value $1$ is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is $0$. When the value $-\mathbf{1}\text{​ or ​}\mathbf{1}$ is used it is essential to test the value of IFAIL on exit.
On exit: ${\mathbf{IFAIL}}={\mathbf{0}}$ unless the routine detects an error or a warning has been flagged (see Section 6).

None.

## 7  Accuracy

If $\delta$ and $\epsilon$ are the relative errors in the argument and the result respectively, then in principle,
 $ε≃ 2x sinh⁡2x δ .$
That is, a relative error in the argument, $x$, is amplified by a factor approximately $\frac{2x}{\mathrm{sinh}2x}$, in the result.
The equality should hold if $\delta$ is greater than the machine precision ($\delta$ due to data errors etc.) but if $\delta$ is due simply to the round-off in the machine representation it is possible that an extra figure may be lost in internal calculation round-off.
The behaviour of the amplification factor is shown in the following graph:
Figure 1
It should be noted that this factor is always less than or equal to $1.0$ and away from $x=0$ the accuracy will eventually be limited entirely by the precision of machine representation.

None.

## 9  Example

This example reads values of the argument $x$ from a file, evaluates the function at each value of $x$ and prints the results.

### 9.1  Program Text

Program Text (s10aafe.f90)

### 9.2  Program Data

Program Data (s10aafe.d)

### 9.3  Program Results

Program Results (s10aafe.r)