Grid `ureal`

parameters uniformly over
their range

`B = gridureal(A,N)`

[B,SampleValues] = gridureal(A,N)

[B,SampleValues] = gridureal(A,NAMES,N)

[B,SampleValues] = gridureal(A,NAMES1,N1,NAMES2,N2,...)

`B = gridureal(A,N)`

substitutes `N`

uniformly-spaced
samples of the uncertain real parameters in `A`

.
The samples are chosen to cut "diagonally" across the
cube of real parameter uncertainty space. The array `B`

has
size equal to `[size(A) N]`

. For example, suppose `A`

has
3 uncertain real parameters, say `X`

, `Y`

and `Z`

.
Let (`x1, x2 , , and xN`

) denote `N`

uniform
samples of `X`

across its range. Similar for `Y`

and `Z`

.
Then sample `A`

at the points ```
(x1, y1,
z1)
```

, `(x2, y2, z2)`

, and ```
(xN,
yN, zN)
```

to obtain the result `B`

.

If `A`

depends on additional uncertain objects,
then `B`

will be an uncertain object.

`[B,SampleValues] = gridureal(A,N)`

additionally
returns the specific sampled values (as a `structure`

whose
fieldnames are the names of `A'`

s uncertain elements)
of the uncertain reals. Hence, `B`

is the same as `usubs(A,SampleValues)`

.

`[B,SampleValues] = gridureal(A,NAMES,N)`

samples
only the uncertain reals listed in the `NAMES`

variable
(`cell`

, or `char`

array). Any entries
of `NAMES`

that are not elements of `A`

are
simply ignored. Note that `gridureal(A, fieldnames(A.Uncertainty),N)`

is
the same as `gridureal(A,N)`

.

`[B,SampleValues] = gridureal(A,NAMES1,N1,NAMES2,N2,...)`

takes `N1`

samples
of the uncertain real parameters listed in `NAMES1`

,
and `N2`

samples of the uncertain real parameters
listed in `NAMES2`

and so on. `size(B)`

will
equal `[size(A) N1 N2 ...]`

.

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