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@(@\newcommand{\B}[1]{{\bf #1}} \newcommand{\R}[1]{{\rm #1}}@)@

Syntax

Purpose

x_k

y_k

f

p

x_p

y_p

Example

*y_p* = *f*.forward(*p*, *x_p*)

We use @(@ F : \B{R}^n \rightarrow \B{R}^m @)@ to denote the function corresponding to the

`adfun`

object f
.
Given the *p*

-th order Taylor expansion for a function
@(@
X : \B{R} \rightarrow \B{R}^n
@)@, this function can be used
to compute the *p*

-th order Taylor expansion for the function
@(@
Y : \B{R} \rightarrow \B{R}^m
@)@ defined by
@[@
Y(t) = F [ X(t) ]
@]@
For @(@ k = 0 , \ldots , p @)@, we use @(@ x^{(k)} @)@ to denote the value of

*x_k*

in the
most recent call to

*f*.forward(*k*, *x_k*)

including @(@
x^{(p)}
@)@ as the value
*x_p*

in this call.
We define the function @(@
X(t)
@)@ by
@[@
X(t) = x^{(0)} + x^{(1)} * t + \cdots + x^{(p)} * t^p
@]@
For @(@ k = 0 , \ldots , p @)@, we use @(@ y^{(k)} @)@ to denote the Taylor coefficients for @(@ Y(t) = F[ X(t) ] @)@ expanded about zero; i.e., @[@ \begin{array}{rcl} y^{(k)} & = & Y^{(k)} (0) / k ! \\ Y(t) & = & y^{(0)} + y^{(1)} * t + \cdots + y^{(p)} * t^p + o( t^p ) \end{array} @]@ where @(@ o( t^p ) / t^p \rightarrow 0 @)@ as @(@ t \rightarrow 0 @)@. The coefficient @(@ y^{(p)} @)@ is equal to the value

*y_p*

returned by this call.
The object

*f*

must be an adfun
object.
We use level
for the AD ad
level of
this object.
The argument

*p*

is a non-negative `int`

.
It specifies the order of the Taylor coefficient for @(@
Y(t)
@)@
that is computed.
The argument

*x_p*

is a `numpy.array`

with one dimension
(i.e., a vector) with length equal to the domain size n
for the function
*f*

.
It specifies the *p*

-th order Taylor coefficient for @(@
X(t)
@)@.
If the AD level
for
*f*

is zero,
all the elements of
*x_p*

must be either `int`

or instances
of `float`

.
If the AD level
for
*f*

is one,
all the elements of
*x_p*

must be `a_float`

objects.
The return value

*y_p*

is a `numpy.array`

with one dimension
(i.e., a vector) with length equal to the range size m
for the function
*f*

.
It is set to the *p*

-th order Taylor coefficient for @(@
Y(t)
@)@.
If the AD level
for
*f*

is zero,
all the elements of
*y_p*

will be instances of `float`

.
If the AD level
for
*f*

is one,
all the elements of
*y_p*

will be `a_float`

objects.
forward_0.py | Forward Order Zero: Example and Test |

forward_1.py | Forward Order One: Example and Test |

Input File: pycppad/adfun.cpp