is_scalemode
Returns if scaling mode specified in testmask is active.
unsigned char is_scalemode(lprec *lp, int testmask);
Return Value
is_scalemode returns if scaling mode specified in testmask
is active.
Parameters
lp
Pointer to previously created lp model. See return value of
make_lp, read_lp,
read_LP, read_mps, read_freemps, read_MPS, read_freeMPS, read_XLI
testmask
SCALE_EXTREME (1) 
Scale to convergence using largest absolute value 
SCALE_RANGE (2) 
Scale based on the simple numerical range 
SCALE_MEAN (3) 
Numerical rangebased scaling 
SCALE_GEOMETRIC (4) 
Geometric scaling 
SCALE_CURTISREID (7) 
Curtisreid scaling 
Additionally, the value can be ORed with any combination of one of the
following values:
SCALE_QUADRATIC (8) 

SCALE_LOGARITHMIC (16) 
Scale to convergence using logarithmic mean of all values 
SCALE_USERWEIGHT (31) 
User can specify scalars 
SCALE_POWER2 (32) 
also do Power scaling 
SCALE_EQUILIBRATE (64) 
Make sure that no scaled number is above 1 
SCALE_INTEGERS (128) 
also scaling integer variables 
SCALE_DYNUPDATE (256) 
dynamic update 
Remarks
The is_scalemode function returns if scaling mode specified in testmask.
This can influence numerical stability considerably. It is advisable to always
use some sort of scaling.
set_scaling must be called before
solve is called.
SCALE_EXTREME, SCALE_RANGE, SCALE_MEAN, SCALE_GEOMETRIC, SCALE_CURTISREID are
the possible scaling algorithms. SCALE_QUADRATIC, SCALE_LOGARITHMIC,
SCALE_USERWEIGHT, SCALE_POWER2, SCALE_EQUILIBRATE, SCALE_INTEGERS are possible
additional scaling parameters.
SCALE_POWER2 results in creating a scalar of power 2. May improve stability.
SCALE_INTEGERS results also in scaling Integer columns. Default they are not
scaled.
SCALE_DYNUPDATE is new from version 5.1.1.0
It has always been so that scaling is done only once on the original model. If a solve
is done again (most probably after changing some data in the model), the scaling factors
aren't computed again. The scalars of the original model are used. This is not always
good, especially if the data has changed considerably. One way to solve this was/is call
unscale before a next solve. In that case, scale factors are recomputed.
From version 5.1.1.0 on, there is another
way to make sure that scaling factors are recomputed and this is by settings SCALE_DYNUPDATE. In
that case, the scaling factors are recomputed also when a restart is done. Note
that they are then always recalculated with each solve, even when no change was made to the model, or
a change that doesn't influence the scaling factors like changing the RHS (Right Hand Side) values
or the bounds/ranges. This can influence performance. It is up to you to decide
if scaling factors must be recomputed or not for a new solve, but by default it still isn't so.
It is possible to set/unset this flag at each next solve and it is even allowed to choose
a new scaling algorithm between each solve. Note that the scaling done by the SCALE_DYNUPDATE is incremental
and the resulting scalars are typically different from scalars recomputed from scratch.
Example
#include <stdio.h>
#include <stdlib.h>
#include "lp_lib.h"
int main(void)
{
lprec *lp;
int scalemode;
/* Create a new LP model */
lp = make_lp(0, 0);
if(lp == NULL) {
fprintf(stderr, "Unable to create new LP model\n");
return(1);
}
scalemode = is_scalemode(lp, SCALE_MEAN);
delete_lp(lp);
return(0);
}
lp_solve API reference
See Also make_lp,
read_lp, read_LP, read_mps,
read_freemps, read_MPS, read_freeMPS, read_XLI, set_scaling,
get_scaling, set_scalelimit,
get_scalelimit, is_integerscaling, is_scaletype
