Approximation API Methods

The Approximation API handles all calls related to creating approximations, evaluating approximations, and accessing the error measures and effects on approximations.

You can use the Approximation API class to interact with approximation objects. Functionality includes creating new approximations, modifying existing approximations, evaluation using trained approximation objects, and retrieval of validation values.

This page discusses:

create(String displayName, String type, Dictionary settings, List<String> inputIdList, List<String> outputIdList, List<String> excludedInputIds, List<String> excludedDatasetIds)

This method generates a new approximation with specified attributes.

Arguments
  • displayName: String naming the current approximation.
  • type: String identifying the method used by the approximation, such as 'RSM'.
  • settings: Python dictionary-like object containing all optional parameters, matching one of the following schemas:
  • inputIdList: An optional list of input parameter IDs identifying parameters to be used as inputs for the approximation.
  • outputIdList: An optional list of output parameter IDs identifying parameters to be predicted by the approximation.
  • excludedInputIds: An optional list of input parameter IDs identifying parameters to be ignored during approximation training.
  • excludedDatasetIds: An optional list of data set IDs identifying data sets to be ignored during approximation training.
Return Value
ApproxObject(Dictionary)
You can use the ApproximationAPI.library command to retrieve all available types and settings.

evaluate(Dictionary evalJson)

This method evaluates one or more approximations at one or more points. The point options are either a single point (which uses the approxPoint argument), a list of points (supplied using approxPoints), or a sweep of points (in which point sweeps are generated as a single input parameter is varied across a supplied array of values while all other parameters are held constant.

Arguments
  • evalJson: A dictionary-like object containing all required request information.
  • Evaluate Schema
Return Value
The structure of the return value depends on the arguments you use:
  • approxPoint: Returns a nested dictionary-like object with each output value for each approximation at the specified point. For example:
    {"approx-id-1":{
  {
    "output-id-1":1.0,
    "output-id-2":2.0
  }
}}
  • approxPoints: Similar to approxPoint, but each approx-id corresponds to an array of output dictionaries. For example:
    {"approx-id-1":[
  {
   "output-id-1":1.0,
   "output-id-2":2.0
  },{
   "output-id-1":1.5,
   "output-id-2":2.5
  }
]}
  • baselinePoint and sweepValues: Similar to approxPoint; however, rather than returning a single point value for each output parameter, it returns a dictionary-like object containing a list-like object of values corresponding to each provided sweep. For example:
    #Input argument
Output = ApproximationAPI.evaluate({
"approxIds": ["approx-id-1"],
 "baselinePoint": {"input-id-1": 1.0, "input-id-2":1.8},
 "sweepValues": {"input-id-1": [0.0, 0.5, 1.0, 1.5, 2.0]
})

#Output
{"approx-id-1":{
  "output-id-1":{
    "input-id-1":[5, 10, 15, 20, 25]
  },
  "output-id-2":{
    "input-id-1":[15, 110, 115, 120, 125]
  }
}}

Only provide one of approxPoint, approxPoints, or baselinePoint/sweepValues.

Supply both baselinePoint and sweepValues together. This determines the manner in which the method evaluates the approximation.

Providing approxPoint evaluates the specified approximations at a single point. Providing approxPoints evaluates the approximations at a list of specified points.

Providing both sweepValues and baselinePoint evaluates an array of points for each input supplied in sweepValues, in which a single input is modified at a time with all other inputs held constant at the values you provide in baselinePoint.

errorMeasures(List<String> approxIds)

This method gets all error measures for a specified set of approximations.

Arguments
approxIds: List of strings identifying approximations.
Return Value
Returns a Python dictionary-like object containing all information on error measures for the specified approximations.
The approxId value is in the id attribute of an approxObject. These objects can be obtained using the select and next methods on this class, among others.

getCoefficientsData(String approxId)

This method gets approximation coefficients data for a specified approximation.

Arguments
approxId: String identifying an approximation.
Return Value
Returns the coefficients data file as a string.
The approxId value is in the id attribute of an approxObject. You can obtain these objects using the select() and next() methods, among others.

globalEffects(String approxId)

This method gets global effects for a specified approximation.

Arguments
approxId: String identifying an approximation.
Return Value
Returns global effects data for the specified approximations as a dictionary-like object
The approxId value is in the id attribute of an approxObject. You can obtain these objects using the select() and next() methods, among others.

mainEffects(String approxId)

This method gets the main effects data for a specified approximation.

Arguments
approxId: String identifying an approximation.
Return Value
Returns the main effects data for the specified approximations as a dictionary-like object.
The approxId value is in the id attribute of an approxObject. You can obtain these objects using the select() and next() methods, among others.

deleteApproximations(List<String> approxIds)

This method deletes specified approximations.

Arguments
approxIds: List-like object containing strings identifying one or more approximations.
Return Value
None.
The approxId values are the id attributes of approxObjects. You can obtain these objects using the select() and next() methods, among others.

trainApproximation(String approxId, String displayName, Dictionary settings, List<String> inputIds, List<String> outputIds, List<String>excludedInputIds, List<String>excludedDatasetIds)

This method initiates training for a specified approximation, optionally passing it updated settings, input/output parameters, and excluded parameters.

Arguments
  • approxId: A string uniquely identifying an approximation.
  • displayName: An optional string for updating the approximation name.
  • settings: Python dictionary-like object containing all optional parameters, matching one of the following schemas:
  • inputIds: An optional list of input parameter IDs identifying parameters to be used as inputs for the approximation.
  • outputIds: An optional list of output parameter IDs identifying parameters to be predicted by the approximation.
  • excludedInputIds: An optional list of input parameter IDs identifying parameters to be ignored during approximation training.
  • excludedDatasetIds: An optional list of data set IDs identifying data sets to be ignored during approximation training.
Return Value
None.

describeApproximation(String approxId)

This method gets the approximation object describing a specified approximation, containing the approximation type and settings (such as polyOrder for RSM).

Arguments
approxId: A string containing the ID of an approximation.
Return Value
Returns a dictionary-like object containing all attributes of an approximation, such as approximation type and settings.

select(Callable selector)

This method selects all approximations matching a specified callable option. This is a wrapper for the iterator method, which iterates over the collection of all approximations, passing each to the selector object and returning those for which the selector object returns true.

Arguments
selector: This is a Python callable object.
Return Value
Returns a Python list of approxObject objects (a list-like object containing dictionary-like objects).

getIterator()

This method creates an iterator and returns the ID.

Arguments
None.
Return Value
Returns a string with the ID of the created approximation iterator.

next(String iteratorId)

This method gets the next approximation object in an approximation iterator.

Arguments
iteratorId: ID string returned by the getIterator method.
Return Value
Returns an approxObject (dictionary-like object).

hasNext(String iteratorId)

This method determines if an iterator contains at least one more item. If hasNext() returns true, next() returns another approxObject.

Arguments
iteratorId: ID string returned by the getIterator() method.
Return Value
Returns true if the iterator contains at least one more item.