treetime/utils.py
def from_regression(cls, clock_model):
        """
        Create the conversion object automatically from the tree

        Parameters
        ----------

         clock_model : dict
            dictionary as returned from TreeRegression with fields intercept and slope

        """
        dc = cls()
        dc.clock_rate = clock_model['slope']
        dc.intercept = clock_model['intercept']
        dc.chisq = clock_model['chisq'] if 'chisq' in clock_model else None
        dc.valid_confidence = clock_model['valid_confidence'] if 'valid_confidence' in clock_model else False
        if 'cov' in clock_model and dc.valid_confidence:
            dc.cov = clock_model['cov']
        dc.r_val = clock_model['r_val']
        return dc
def from_regression(cls, clock_model):
        dc = cls()
        dc.clock_rate = clock_model['slope']
        dc.intercept = clock_model['intercept']
        dc.chisq = clock_model['chisq'] if 'chisq' in clock_model else None
        dc.valid_confidence = clock_model['valid_confidence'] if 'valid_confidence' in clock_model else False
        if 'cov' in clock_model and dc.valid_confidence:
            dc.cov = clock_model['cov']
        dc.r_val = clock_model['r_val']
        return dc
def from_regression ( cls , clock_model ) : dc = cls ( ) dc . clock_rate = clock_model [ 'slope' ] dc . intercept = clock_model [ 'intercept' ] dc . chisq = clock_model [ 'chisq' ] if 'chisq' in clock_model else None dc . valid_confidence = clock_model [ 'valid_confidence' ] if 'valid_confidence' in clock_model else False if 'cov' in clock_model and dc . valid_confidence : dc . cov = clock_model [ 'cov' ] dc . r_val = clock_model [ 'r_val' ] return dc
Create the conversion object automatically from the tree

        Parameters
        ----------

         clock_model : dict
            dictionary as returned from TreeRegression with fields intercept and slope
Create the conversion object automatically from the tree