model.batch().create(<tag>,jobtype); creates a batch job tagged
<tag> of type
jobtype, where
jobtype is
Parametric,
Batch, or
Cluster.
model.batch().size() returns number of batch jobs.
model.batch().tags() returns the tags of the batch jobs.
model.batch(<tag>).attach(<stag>) attaches a batch job with tag
<tag> to a study with tag
<stag>, which makes it visible under that study.
model.batch(<tag>).create(<jtag>,<oper>) creates a batch job sequence.
model.batch(<tag>).detach(<stag>) detaches a batch job from a study with tag
<stag>.
model.batch(<tag>).run() runs the batch job. The
run method can take an additional Boolean input argument
createPlots, which, when set to true, generates the corresponding default plots when computing a solution.
model.batch(<tag>).study(<stag>) assigns a batch job to a study tag
<stag>.
model.batch(<tag>).study() returns the study tag of batch job with tag
<tag>.
model.batch(<tag>).feature(<ttag>)).getAllowedPropertyValues(property) returns the set of allowed values for a property if the set is a finite set of strings; otherwise, it returns null.
The Parametric job type has the following properties:
The Optimization job type sets its property through the
Optimization study node, which has the following properties:
The Batch job type has the following properties:
The Cluster job type has the following properties:
model.batch(<tag>).feature(<ttag>).set(ttprop,<tpvalue>) sets the task type property
ttprop to the value
<tpvalue>.
The Data task type contains child nodes with process information of type
Process; see
Table 2-7.
model.batch(<tag>).feature(<ttag>).feature(<ptag>).set(ptype, <pvalue>) sets the property
ptype to the value
<pvalue>.
ptype can have the values listed in
Table 2-8
where pname is the name of the parametric sweep feature that ran and
fname is the name of the solution feature that stored the solutions. Use
where pname is the name of the parametric sweep feature that ran and
fname is the name of the solution feature that stored the solutions. Use