# import modules
import myFitter as mf

# define your model class by deriving from mf.Model
class MyModel(mf.Model):
    def __init__(self):
        # First call the initialisation method of the base class.
        mf.Model.__init__(self)

        # Add a parameters named 'p1' and 'p2' to the model.
        self.addParameter('p1', default=1.0, bounds=(0.1, None))
        self.addParameter('p2', default=1.0, scale=0.5)

        # Constrain p1*p2 to be less than 1. The dependent quantity
        # 'p1 p2' must be computed in getDependentQuantities().
        self.addConstraint('p1 p2', '<', 1.0, scale=0.5)

        # Add a Gaussian chi-square contribution for observable 'obs1'
        # with measured value 2.3 and standard deviation 0.3.
        self.addGaussianCSC('obs1', 2.05, 0.05, syst=(0.2, 0.1))
        # Add a chi-square contribution of three correlated gaussian observables
        # 'obs2', 'obs3', and 'obs4. 'obs234' is the name of the chi-square
        # contribution.
        self.addCorrelatedGaussianCSC('obs234',
            [('obs2', 0.8, 0.1),    
             ('obs3', 2.3, 0.2),
             ('obs4', 0.3, 0.1)],    # measured values and standard deviations
            [('obs2', 'obs3',  0.2),
             ('obs3', 'obs4', -0.8)]) # correlation coefficients
        
    # All quantities that depend on the model parameters are calculated here.
    def getDependentQuantities(self, p):
        # Always call the method of the base class first. This essentially
        # copies the dictionary `p`, substitutes default values for any
        # parameters that have been omitted and adjust the values of parameters
        # that have been fixed (i.e. are not floating in the fit).
        q = mf.Model.getDependentQuantities(self, p)

        # Extract the parameter values from the dictionary q (*not* p).
        p1 = q['p1']
        p2 = q['p2']

        # Compute the dependent quantity 'p1 p2' (for the constraint)
        q['p1 p2'] = p1*p2
        
        # Compute the four observables.
        q['obs1'] = p1**2 + p2**2
        q['obs2'] = p2/p1
        q['obs3'] = p1 + p2
        q['obs4'] = p1 - p2

        # Return the dictionary q.
        return q