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n =
f.Domain()
m =
f.Range()
p =
f.Parameter(
i)
u =
f.use_VecAD()
v =
f.size_var()
size_var
returns zero.)
const ADFun<
Base>
f
(see ADFun<
Base>
constructor
).
size_t
n
and is the dimension of the domain space corresponding to f.
This is equal to the size of the vector x in the call
Independent(
x)
that starting recording the operation sequence
currently stored in f
(see FunConstruct
and Dependent
).
size_t
m
and is the dimension of the range space corresponding to f.
This is equal to the size of the vector y in syntax
ADFun<
Base>f
(x
,y
)
or
f.Dependent(
y)
depending on which stored the operation sequence currently in f
(see FunConstruct
and Dependent
).
size_t
i
and
0 \leq i < m
.
The result p has prototype
bool
p
It is true if the i-th component of range space for
F
corresponds to a
parameter
in the operation sequence.
In this case,
the i-th component of
F
is constant and
\[
\D{F_i}{x_j} (x) = 0
\]
for
j = 0 , \ldots , n-1
and all
x \in B^n
.
bool
u
If it is true, the
AD of Base
operation sequence
stored in f contains
VecAD
operands.
Otherwise u is false.
size_t
v
and is the number of variables in the operation sequence plus the following:
one for a phantom variable with tape address zero,
one for each component of the domain that is a parameter.
The amount of work and memory necessary for computing function values
and derivatives using f is roughly proportional to v.
If there is no operation sequence stored in f,
size_var
returns zero
(see default constructor
).