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 # SimpleTrainingPlan Struct Reference

 Last update: 16.07.2025 

TrainingPlan assigns a in a set of sample each sample a status on how the sample is to be treated during the training of a model A model is trained for a set of outputs. [More...](struct_simple_training_plan.xhtml#details)

## <a name="pub-methods"></a>Public Member Functions

virtual std::vector&lt; string &gt; [getInputNames](struct_simple_training_plan.xhtml#a4f95e721a51d6482217b85546b69b3f9) (::data\_handler::DataHandlerBase datahandler) override Returns the input names from the datahandler. [More...](#a4f95e721a51d6482217b85546b69b3f9)  
 virtual [Matrix](class_matrix.xhtml) [getInputs](struct_simple_training_plan.xhtml#afc52921c8d133bb463c1dfa5a8b7ef22) (::data\_handler::DataHandlerBase datahandler) override Returns the inputs fitting the training plan from the datahandler. [More...](#afc52921c8d133bb463c1dfa5a8b7ef22)  
 virtual string [getMOPIdent](struct_simple_training_plan.xhtml#a255c5ecec66209c6f30d3d5f15177859) () override Returns the [MOP](class_m_o_p.xhtml "a group of random fields belonging together (either a single random field, or multiple cross-correlat...") ident the TrainingPlan is created for. [More...](#a255c5ecec66209c6f30d3d5f15177859)  
 virtual std::vector&lt; string &gt; [getOutputNames](struct_simple_training_plan.xhtml#a9f69089e282ffa01fd21080139b05f8f) (::data\_handler::DataHandlerBase datahandler) override Returns the output names from the datahandler. [More...](#a9f69089e282ffa01fd21080139b05f8f)  
 virtual [Matrix](class_matrix.xhtml) [getOutputs](struct_simple_training_plan.xhtml#a11f9260c1f6f8527fb75fa5950f52dfa) (::data\_handler::DataHandlerBase datahandler) override Returns the outputs fitting the training plan from the datahandler. [More...](#a11f9260c1f6f8527fb75fa5950f52dfa)  
 virtual [SampleUsage](group__training__plan.xhtml#gafce529ac7282fd94c419e8bea8492268) [getSampleUsageInSet](struct_simple_training_plan.xhtml#a2b8e899313418568acbb9ed5b2ce6ade) (uint64\_t i, uint64\_t j) override getSampleUsage accessor of the j-th sample in the i-th training set [More...](#a2b8e899313418568acbb9ed5b2ce6ade)  
 virtual [SampleUsage](group__training__plan.xhtml#gafce529ac7282fd94c419e8bea8492268) [getSampleUsageInSetRef](struct_simple_training_plan.xhtml#a6c419ba361cd6d96b71e12bf657d940b) (uint64\_t i, uint64\_t j) override getSampleUsageRef non- accessor of the j-th sample in the i-th training set [More...](#a6c419ba361cd6d96b71e12bf657d940b)  
 virtual [ParameterImportance](group__common.xhtml#gad5ca470fd07552bf1da82219827c4ec0) [inputImportance](struct_simple_training_plan.xhtml#a7afbd5f5b1743bc2423ca855fe2603ab) (uint64\_t i) override parameter returns the ParameterImportance for the i-th parameter [More...](#a7afbd5f5b1743bc2423ca855fe2603ab)  
 virtual [ParameterImportance](group__common.xhtml#gad5ca470fd07552bf1da82219827c4ec0) [inputImportanceInSubspace](struct_simple_training_plan.xhtml#aa2ae62e6cab293f7c236e9bf273768f1) (uint64\_t i, uint64\_t j, uint64\_t o=0) override inputImportanceInSubspace returns true if the input j is in the subspace i for the given o-th output in the output-matrix. [More...](#aa2ae62e6cab293f7c236e9bf273768f1)  
 virtual bool [isValid](struct_simple_training_plan.xhtml#ad4450a95cde865da632771935f1c57b3) (::data\_handler::DataHandlerBase datahandler) override Checks if the training plan is valid for the give datahandler. [More...](#ad4450a95cde865da632771935f1c57b3)  
 virtual uint64\_t [numInputs](struct_simple_training_plan.xhtml#aae989fb2bbddfd907494bed60516e03d) () override numInputs returns the number of inputs used and defined in this training plan [More...](#aae989fb2bbddfd907494bed60516e03d)  
 virtual uint64\_t [numOutputs](struct_simple_training_plan.xhtml#a762eb06ef18a50d3041ce79215855763) () override numOutputs returns the number of outputs used in this training plan [More...](#a762eb06ef18a50d3041ce79215855763)  
 virtual uint64\_t [numSamplesInSet](struct_simple_training_plan.xhtml#ad3ec25fce42515bda59cd6e7154a8258) (uint64\_t i) override numSamplesInSet returns the number of elements (samples) in the training set [More...](#ad3ec25fce42515bda59cd6e7154a8258)  
 virtual uint64\_t [numSets](struct_simple_training_plan.xhtml#a76d26675967b395d8924915b06fd44f9) () override numSets returns the number of training sets in the training plan [More...](#a76d26675967b395d8924915b06fd44f9)  
 virtual uint64\_t [numSubspaces](struct_simple_training_plan.xhtml#a52bd33805e42f83fcad54b402b9d4ced) (uint64\_t i=0) override numSubspaces returns the number of filtered subspaces available in the Training Plan to the i-th output in the output matrix [More...](#a52bd33805e42f83fcad54b402b9d4ced)  
 virtual uint64\_t [numTestSamplesInSet](struct_simple_training_plan.xhtml#aacc683995d55549d854c2d2420aef90c) (uint64\_t i) override numTestSamplesInSet returns the number of elements (samples) in the training set [More...](#aacc683995d55549d854c2d2420aef90c)  
 virtual uint64\_t [numTrainingSamplesInSet](struct_simple_training_plan.xhtml#ad37730c1466388aa53eaeccc3be698d8) (uint64\_t i) override numTrainingSamplesInSet returns the number of elements (samples) in the training set [More...](#ad37730c1466388aa53eaeccc3be698d8)  
 <a id="a7ed6ac9232f95cc9f4f7871fc0531bb2"></a>[SimpleTrainingPlan](struct_simple_training_plan.xhtml) [operator=](struct_simple_training_plan.xhtml#a7ed6ac9232f95cc9f4f7871fc0531bb2) ([SimpleTrainingPlan](struct_simple_training_plan.xhtml))=default Copy-Assignment.   
 virtual uint64\_t [output](struct_simple_training_plan.xhtml#a233e0c56c9d1e12b9bc6503a37bc3d8c) (uint64\_t i) override parameter returns the index of the i-th output in the output matrix [More...](#a233e0c56c9d1e12b9bc6503a37bc3d8c)  
 virtual [setInputs](struct_simple_training_plan.xhtml#a9e3f96174684a90e8567342ca3ef171a) (::data\_handler::DataHandlerBase datahandler, [Matrix](class_matrix.xhtml) inputs) Inserts the inputs fitting the training plan from the datahandler. [More...](#a9e3f96174684a90e8567342ca3ef171a)  
 virtual [setOutputs](struct_simple_training_plan.xhtml#a1a337403848bc684e14fc40d51f42813) (::data\_handler::DataHandlerBase datahandler, [Matrix](class_matrix.xhtml) outputs) Inserts the outputs fitting the training plan from the datahandler. [More...](#a1a337403848bc684e14fc40d51f42813)  
 <a id="ab2d903e7c07dc51458d25391ea5c3bf2"></a> [SimpleTrainingPlan](struct_simple_training_plan.xhtml#ab2d903e7c07dc51458d25391ea5c3bf2) ()=default Constructor.   
  [SimpleTrainingPlan](struct_simple_training_plan.xhtml#aa7b5914712bf07337eb081fc3ac51321) (TrainingPlanVector plan, ParameterImportanceVector params, IndexVector output\_map, SubspaceMatrixList subspace\_matrix\_list, uint64\_t num\_inputs, string mop\_ident=handler::defaultMOPIdent) Initializing Constructor. [More...](#aa7b5914712bf07337eb081fc3ac51321)  
 <a id="a148ac409e6a636e27a0a5babd033e340"></a> [SimpleTrainingPlan](struct_simple_training_plan.xhtml#a148ac409e6a636e27a0a5babd033e340) ([SimpleTrainingPlan](struct_simple_training_plan.xhtml))=default Copy-Contructor.   
 ## <a name="pub-attribs"></a>Public Attributes

<a id="a60d4ce785dc80f084f8aef0f6fc32ac9"></a>ParameterImportanceVector **m\_input\_importance** <a id="a29cdeff4c0854e3f29a8e933974cda97"></a>string **m\_mop\_ident** <a id="ab9b71b61a67b18665895e943bdc3a172"></a>uint64\_t **m\_num\_inputs** <a id="aa603e63bcc57491f9fe42cb2af9fba3d"></a>IndexVector **m\_output\_mapping** <a id="af68dafed0a8bfe0617e1e68e1cecd647"></a>SubspaceMatrixList **m\_subspace\_matrix\_list** <a id="a3768372cdbae9882fdff823579f8ba73"></a>TrainingPlanVector **m\_training** <a id="details" name="details"></a>## Detailed Description

TrainingPlan assigns a in a set of sample each sample a status on how the sample is to be treated during the training of a model A model is trained for a set of outputs.

- if the set is a singleton (one element), the trained model is a scalar one
- if the set has more than one element the output dimension should be consistent for all samples. if it is not consistent, we are dealing with incomplete samples. Either the model itself has then to decide how to handle this or this should be handled before the competition is defined i.e. by the (Scalar)[MOP](class_m_o_p.xhtml "a group of random fields belonging together (either a single random field, or multiple cross-correlat...") The training plan is *not* concerned with failed/incomplete inputs. It should always handle a consistent input/output pair



## Constructor &amp; Destructor Documentation

<a id="aa7b5914712bf07337eb081fc3ac51321"></a>## [◆ ](#aa7b5914712bf07337eb081fc3ac51321)SimpleTrainingPlan()

 [SimpleTrainingPlan](struct_simple_training_plan.xhtml)  ( TrainingPlanVector  *plan*,    ParameterImportanceVector  *params*,    IndexVector  *output\_map*,    SubspaceMatrixList  *subspace\_matrix\_list*,    uint64\_t  *num\_inputs*,    string  *mop\_ident* = `handler::defaultMOPIdent`   ) 

Initializing Constructor.

Parameters planA collection of lists that describe for each sample if its used for training, testing or is ignored Multiple lists are used for instance in the Leave-One-Out or cross-validation scenario paramsDefines for each input parameter its importance (if it is ignored, mandatory or optional) output\_mapDefines how the vectors in the output matrix are mapped to the actual output in the training subspace\_matrix\_listDefines a list of possible input subspaces for each output (after output mapping). This may be used by model for increased approximation quality. num\_inputsThe number of inputs for the training mop\_dentThe mops ident 



## Member Function Documentation

<a id="a4f95e721a51d6482217b85546b69b3f9"></a>## [◆ ](#a4f95e721a51d6482217b85546b69b3f9)getInputNames()

 virtual std::vector&lt;string&gt; getInputNames  ( ::data\_handler::DataHandlerBase  *datahandler*)   overridevirtual 

Returns the input names from the datahandler.

Parameters datahandlerThe datahandler to get the data from ReturnsThe input data names Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a15234ce024e1b13e596ff9c38df3be71).





<a id="afc52921c8d133bb463c1dfa5a8b7ef22"></a>## [◆ ](#afc52921c8d133bb463c1dfa5a8b7ef22)getInputs()

 virtual [Matrix](class_matrix.xhtml) getInputs  ( ::data\_handler::DataHandlerBase  *datahandler*)   overridevirtual 

Returns the inputs fitting the training plan from the datahandler.

Parameters datahandlerThe datahandler to get the data from ReturnsThe (scalar) input data Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a6e262334d7e27b9f05121454531fa5b6).





<a id="a255c5ecec66209c6f30d3d5f15177859"></a>## [◆ ](#a255c5ecec66209c6f30d3d5f15177859)getMOPIdent()

 virtual string getMOPIdent  ( )   overridevirtual 

Returns the [MOP](class_m_o_p.xhtml "a group of random fields belonging together (either a single random field, or multiple cross-correlat...") ident the TrainingPlan is created for.

ReturnsThe ident for the [MOP](class_m_o_p.xhtml "a group of random fields belonging together (either a single random field, or multiple cross-correlat...")Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a5df8016765ccb017b2ff5778e3e81558).





<a id="a9f69089e282ffa01fd21080139b05f8f"></a>## [◆ ](#a9f69089e282ffa01fd21080139b05f8f)getOutputNames()

 virtual std::vector&lt;string&gt; getOutputNames  ( ::data\_handler::DataHandlerBase  *datahandler*)   overridevirtual 

Returns the output names from the datahandler.

Parameters datahandlerThe datahandler to get the data from ReturnsThe output data names Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a32c9c6dc56f9b1b5ad2aa3e686d172c7).





<a id="a11f9260c1f6f8527fb75fa5950f52dfa"></a>## [◆ ](#a11f9260c1f6f8527fb75fa5950f52dfa)getOutputs()

 virtual [Matrix](class_matrix.xhtml) getOutputs  ( ::data\_handler::DataHandlerBase  *datahandler*)   overridevirtual 

Returns the outputs fitting the training plan from the datahandler.

Parameters datahandlerThe datahandler to get the data from ReturnsThe (scalar) output data Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a8de106670ace9e349ee9c149741b8e44).





<a id="a2b8e899313418568acbb9ed5b2ce6ade"></a>## [◆ ](#a2b8e899313418568acbb9ed5b2ce6ade)getSampleUsageInSet()

 virtual [SampleUsage](group__training__plan.xhtml#gafce529ac7282fd94c419e8bea8492268) getSampleUsageInSet  ( uint64\_t  *i*,    uint64\_t  *j*   )   overridevirtual 

getSampleUsage accessor of the j-th sample in the i-th training set

Parameters iIndex of the training set jIndex of the sample in training set i ReturnsThe sample at the given indices Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a1c4be324fc1e91c3039a49631f6e2cc9).





<a id="a6c419ba361cd6d96b71e12bf657d940b"></a>## [◆ ](#a6c419ba361cd6d96b71e12bf657d940b)getSampleUsageInSetRef()

 virtual [SampleUsage](group__training__plan.xhtml#gafce529ac7282fd94c419e8bea8492268) getSampleUsageInSetRef  ( uint64\_t  *i*,    uint64\_t  *j*   )   overridevirtual 

getSampleUsageRef non- accessor of the j-th sample in the i-th training set

Parameters iIndex of the training set jIndex of the sample in training set i ReturnsThe sample at the given indices Implements [TrainingPlanBase](struct_training_plan_base.xhtml#af67b70402c8a7610ce4a99c252f53681).





<a id="a7afbd5f5b1743bc2423ca855fe2603ab"></a>## [◆ ](#a7afbd5f5b1743bc2423ca855fe2603ab)inputImportance()

 virtual [ParameterImportance](group__common.xhtml#gad5ca470fd07552bf1da82219827c4ec0) inputImportance  ( uint64\_t  *i*)   overridevirtual 

parameter returns the ParameterImportance for the i-th parameter

Parameters iThe index of the parameter ReturnsThe ParameterUsage of parameter i Implements [TrainingPlanBase](struct_training_plan_base.xhtml#ab9acd4287a8208fa9a32867cafaf8e46).





<a id="aa2ae62e6cab293f7c236e9bf273768f1"></a>## [◆ ](#aa2ae62e6cab293f7c236e9bf273768f1)inputImportanceInSubspace()

 virtual [ParameterImportance](group__common.xhtml#gad5ca470fd07552bf1da82219827c4ec0) inputImportanceInSubspace  ( uint64\_t  *i*,    uint64\_t  *j*,    uint64\_t  *o* = `0`   )   overridevirtual 

inputImportanceInSubspace returns true if the input j is in the subspace i for the given o-th output in the output-matrix.

Parameters iIndex of the subspace jIndex of the input parameter oThe o-th output the input is important to ReturnsParameterImportance of input j in subspace i for the given output Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a60399ab71c2fcf3a21c9a613997c4822).





<a id="ad4450a95cde865da632771935f1c57b3"></a>## [◆ ](#ad4450a95cde865da632771935f1c57b3)isValid()

 virtual bool isValid  ( ::data\_handler::DataHandlerBase  *datahandler*)   overridevirtual 

Checks if the training plan is valid for the give datahandler.

Returnstrue iff the training plan is valid Implements [TrainingPlanBase](struct_training_plan_base.xhtml#aed20b1ee85452a87a9e10f39077b94a3).





<a id="aae989fb2bbddfd907494bed60516e03d"></a>## [◆ ](#aae989fb2bbddfd907494bed60516e03d)numInputs()

 virtual uint64\_t numInputs  ( )   overridevirtual 

numInputs returns the number of inputs used and defined in this training plan

ReturnsThe number of parameters the training plan is defined on Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a5c973e14b896504b0522fc953bb3b2dc).





<a id="a762eb06ef18a50d3041ce79215855763"></a>## [◆ ](#a762eb06ef18a50d3041ce79215855763)numOutputs()

 virtual uint64\_t numOutputs  ( )   overridevirtual 

numOutputs returns the number of outputs used in this training plan

ReturnsThe number of outputs the training plan is defined on Implements [TrainingPlanBase](struct_training_plan_base.xhtml#aad28bd2bb818cf6c433e22e22768086c).





<a id="ad3ec25fce42515bda59cd6e7154a8258"></a>## [◆ ](#ad3ec25fce42515bda59cd6e7154a8258)numSamplesInSet()

 virtual uint64\_t numSamplesInSet  ( uint64\_t  *i*)   overridevirtual 

numSamplesInSet returns the number of elements (samples) in the training set

Parameters iThe index of the training set ReturnsThe number of elements in set i Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a0ef7e16a9a52c22ecb59f6148accae62).





<a id="a76d26675967b395d8924915b06fd44f9"></a>## [◆ ](#a76d26675967b395d8924915b06fd44f9)numSets()

 virtual uint64\_t numSets  ( )   overridevirtual 

numSets returns the number of training sets in the training plan

ReturnsThe number of training sets Implements [TrainingPlanBase](struct_training_plan_base.xhtml#ad536b0ba37fa27e95a51c0aa3afc96da).





<a id="a52bd33805e42f83fcad54b402b9d4ced"></a>## [◆ ](#a52bd33805e42f83fcad54b402b9d4ced)numSubspaces()

 virtual uint64\_t numSubspaces  ( uint64\_t  *i* = `0`)   overridevirtual 

numSubspaces returns the number of filtered subspaces available in the Training Plan to the i-th output in the output matrix

Parameters iThe index of the output ReturnsThe number of Subspaces Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a44682836a8190246e4db84f997a003cc).





<a id="aacc683995d55549d854c2d2420aef90c"></a>## [◆ ](#aacc683995d55549d854c2d2420aef90c)numTestSamplesInSet()

 virtual uint64\_t numTestSamplesInSet  ( uint64\_t  *i*)   overridevirtual 

numTestSamplesInSet returns the number of elements (samples) in the training set

Parameters iThe index of the training set ReturnsThe number of elements in set i Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a88109fe981a2b192eb8e09a87ae563ed).





<a id="ad37730c1466388aa53eaeccc3be698d8"></a>## [◆ ](#ad37730c1466388aa53eaeccc3be698d8)numTrainingSamplesInSet()

 virtual uint64\_t numTrainingSamplesInSet  ( uint64\_t  *i*)   overridevirtual 

numTrainingSamplesInSet returns the number of elements (samples) in the training set

Parameters iThe index of the training set ReturnsThe number of elements in set i Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a13261fec66c7bbac8c07123619300275).





<a id="a233e0c56c9d1e12b9bc6503a37bc3d8c"></a>## [◆ ](#a233e0c56c9d1e12b9bc6503a37bc3d8c)output()

 virtual uint64\_t output  ( uint64\_t  *i*)   overridevirtual 

parameter returns the index of the i-th output in the output matrix

Parameters iThe index of the parameter ReturnsThe index of output i in the output matrix Implements [TrainingPlanBase](struct_training_plan_base.xhtml#a3e0dff9e7373d9800e8abe6a61af4c16).





<a id="a9e3f96174684a90e8567342ca3ef171a"></a>## [◆ ](#a9e3f96174684a90e8567342ca3ef171a)setInputs()

 virtual setInputs  ( ::data\_handler::DataHandlerBase  *datahandler*,    [Matrix](class_matrix.xhtml)  *inputs*   )   virtual 

Inserts the inputs fitting the training plan from the datahandler.

Parameters datahandlerThe datahandler to set the data in inputsThe data to set 



<a id="a1a337403848bc684e14fc40d51f42813"></a>## [◆ ](#a1a337403848bc684e14fc40d51f42813)setOutputs()

 virtual setOutputs  ( ::data\_handler::DataHandlerBase  *datahandler*,    [Matrix](class_matrix.xhtml)  *outputs*   )   virtual 

Inserts the outputs fitting the training plan from the datahandler.

Parameters datahandlerThe datahandler to set the data in outputsThe data to set