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