Need a way of removing shape on a layer NOT of a specific di

I am trying to find a way in DIVA/SKILL to remove a specific layer that
is NOT of a given dimension. Can anyone help?


thanks

 

[vdvalk@rogers.com]

I assume that your data is essetially flat!

One way of doing this is to split the task into two separate tasks.

1) delete all data that is smaller
2) delete all data that is larger.

Here is one method I like to employ.

( it is not foolproof, but works on most cases!)

Size the data by -1/2 of thet target data amount per edge
Then size this resuly by +1/2 of the target data. This data represents
areas where the data was too big.

carefully process these areas to delete the areas that are too big.
( Note that several choices need to be made here )...

With the resulting data, undersize by 1/2 of the target (less the
smallest resolution the tool works with) and ovesize the resulting
data. All of the sub-minimum data will be gone.

This works for generic data, but has a few issues on boundary cases.
Data that is
almost right ( 1 dbu off of target) may get left behind. Also data that
has spacings smaller than root2 of width can get merged in degenerate
cases ...

But this works for most data.

i.e diva code could looks something like:
bigdata = geomSize( geomSize( data, (-0.5*target) , (0.5*target )
notbigdata = geomAndNot( data bigdata )
notsmallnotbigdata = geomSize( geomSize( notbigdata,
((-0.5.target)+.01), ((0.5*target )-.01 ) ) )



YMMV
-- Gerry

 

Gerry,

Thnks... worked like a charm.... althought you were right that it would
not process the boundary cases...

Som
vdvalk@rogers.com wrote:

I assume that your data is essetially flat!

One way of doing this is to split the task into two separate tasks.

1) delete all data that is smaller
2) delete all data that is larger.

Here is one method I like to employ.

( it is not foolproof, but works on most cases!)

Size the data by -1/2 of thet target data amount per edge
Then size this resuly by +1/2 of the target data. This data represents
areas where the data was too big.

carefully process these areas to delete the areas that are too big.
( Note that several choices need to be made here )...

With the resulting data, undersize by 1/2 of the target (less the
smallest resolution the tool works with) and ovesize the resulting
data. All of the sub-minimum data will be gone.

This works for generic data, but has a few issues on boundary cases.
Data that is
almost right ( 1 dbu off of target) may get left behind. Also data that
has spacings smaller than root2 of width can get merged in degenerate
cases ...

But this works for most data.

i.e diva code could looks something like:
bigdata = geomSize( geomSize( data, (-0.5*target) , (0.5*target )
notbigdata = geomAndNot( data bigdata )
notsmallnotbigdata = geomSize( geomSize( notbigdata,
((-0.5.target)+.01), ((0.5*target )-.01 ) ) )



YMMV
-- Gerry