Attributes¶

An attribute is defined as a fixed value that does not take part in the fitting process (i.e. not part of parameter space). For example, the number of iterations of an internal loop would be a good candidate for a function attribute. Unlike parameters, attributes can have one of the following Python types: int, float, string, boolean.

Attributes should be declared along with the parameters within the init function:

# Remember to choose either IFunction1D or IPeakFunction
class Example1DFunction(IFunction1D): # or IPeakFunction

    def init(self):
        self.declareParameter("A0", 0.0)
        self.declareParameter("A1", 0.0)

        self.declareAttribute("NLoops", 10)

The value of an attribute does not change throughout the fitting so it is best to store it locally once after it has been set by the user. A method called setAttributeValue is defined by the super class and is called automatically by the framework when a user sets an attribute.

If defined in your class then you can use it to set a python attribute on your object, e.g.

class Example1DFunction(IFunction1D):

    def init(self):
        self.declareParameter("A0", 0.0)
        self.declareParameter("A1", 0.0)

        self.declareAttribute("NLoops", 10)

    def setAttributeValue(self, name, value):
        if name == "NLoops":
            # Can the be accessed quicker later using self._nloops
            self._nloops = value

Attribute Validators¶

If desired, the possible values that an attribute can take can be restricted through the use of a Function Attribute Validator. Such a validator must derive from the IValidator abstract class; a number of these are currently provided in the Mantid Kernel such as: - List Validator (attribute value must be specified from a provided list of values). - Bounded Validator (numeric attribute value must be between two provided bounds). - String contrains validator (string attribute value must contain a provided sub-string/s)

In python, attributes can be declared with a validator using the following syntax:

from mantid.kernel import StringListValidator, StringContainsValidator, FloatBoundedValidator

class Example1DFunction(IFunction1D): # or IPeakFunction

    def init(self):
        self.declareParameter("StrAttr", "acceptable", StringListValidator(["acceptable","values"]))
        self.declareAttribute("FloatAtt", 3.0, FloatBoundedValidator(0.0, 5.0))
        self.declareAttribute("StringContainsAtt", "StringContains",
                                                    StringContainsValidator(["Contains"]))

If a string list validator is used for any function called from the FitPropertyBrowser, the attribute value can be input through the browser using a combo box.