Query object for finding all linearized blocks
linqueryAllBlocks creates a custom query object for finding
all the linearized blocks listed in a
When you linearize a Simulink® model, you can create a
LinearizationAdvisor object that contains diagnostic information about individual
block linearizations. To find block linearizations that satisfy specific criteria, you can use
with custom query objects. Alternatively, you can analyze linearization diagnostics using the
Linearization Advisor in the Model Linearizer. For more information on finding
specific blocks in linearization results, see Find Blocks in Linearization Results Matching Specific Criteria.
When you use this query object with the
find command, the
LinearizationAdvisor object returned by
contains the same blocks as the input
Therefore, it is not necessary to use
linqueryAllBlocks. This command
is a utility function used by the Linearization Advisor in the Model
query object for finding all the linearized blocks listed in a
query = linqueryAllBlocks
QueryType — Query type
'All Blocks' (default) | character vector
Query type, specified as
Description — Query description
'All Linearized Blocks' (default) | character vector
Query description, specified as
|Find blocks in linearization results that match specific criteria|
Find All Linearized Blocks
Load the Simulink model.
mdl = 'scdpwm'; load_system(mdl)
Linearize the model and obtain the
opts = linearizeOptions('StoreAdvisor',true); [sys,op,info] = linearize(mdl,getlinio(mdl),opts); advisor = info.Advisor;
Create query object, and find all the linearized blocks.
qAll = linqueryAllBlocks; advAll = find(advisor,qAll)
advAll = LinearizationAdvisor with properties: Model: 'scdpwm' OperatingPoint: [1x1 opcond.OperatingPoint] BlockDiagnostics: [1x10 linearize.advisor.BlockDiagnostic] QueryType: 'All Blocks'
You can also create custom queries for finding specific blocks in linearization results using the Linearization Advisor in the Model Linearizer. For more information, see Find Blocks in Linearization Results Matching Specific Criteria.
Introduced in R2017b