# Documentation of visuminmaxdiff

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## Function Synopsis

`[DataMin, DataMax, DataDiffScaled] = visuminmaxdiff(DataIn, OptMinMax)`

## Help text

``` Compute minimum and maximum of provided data and a scaling difference between both

Compute minimum, maximum and difference between both of provided data,
employ some special scalings to the difference value. Additionally,
only a certain percentage of the data points can be used to compute the
maximum, thus excluding the worst points during minimization.
The results are used for scaling the axes limits in a very tight manner
and adding a small (empty) area around the data (preventing data points
to lay exactly on the axes).
All possible exceptions (minimum and maximum are identical, NaN, Inf, or 0
at the same time) are handled here. This function returns even for these
cases "useful" values (DataMin = 0, DataMax = 1, DataDiffScaled = 0.02).

Synatx: [DataMin, DataMax, DataDiffScaled] = visuminmaxdiff(DataIn, OptMinMax)

Input parameters:
DataIn    - Vector/Matrix with variables
OptMinMax - (optional) Options (both options may be omitted):
OptMinMax(1): Data2Use4Max, scalar
OptMinMax(2): scalar with scaling value for difference (used for small area of
axes added to maximum/subtracted from minimum value)
if omitted, 0.02 (2%) is used
OptMinMax(3): scalar with scaling value, if no difference between minimum and
maximum (this ensures error free axes scaling)
if omitted, 1e-5 is used
- (optional) Structure containing non-standard options

Output parameters:
DataMin  - Scalar containing minimum of whole vector/matrix
DataMax  - Scalar containing maximum of whole vector/matrix
DataDiffScaled  - Scalar containing scaled difference between minimum
and maximum, checked for zero minimum and scaled accordingly

Examples:
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