(cls, yaml_str=None, str_or_buffer=None)
return seg
Create a SegmentedRegressionModel instance from a saved YAML
        configuration. Arguments are mutally exclusive.

        Parameters
        ----------
        yaml_str : str, optional
            A YAML string from which to load model.
        str_or_buffer : str or file like, optional
            File name or buffer from which to load YAML.

        Returns
        -------
        SegmentedRegressionModel
Create a SegmentedRegressionModel instance from a saved YAML
        configuration. Arguments are mutally exclusive.
Create a SegmentedRegressionModel instance from a saved YAML configuration . Arguments are mutally exclusive .
def from_yaml(cls, yaml_str=None, str_or_buffer=None):
        """
        Create a SegmentedRegressionModel instance from a saved YAML
        configuration. Arguments are mutally exclusive.

        Parameters
        ----------
        yaml_str : str, optional
            A YAML string from which to load model.
        str_or_buffer : str or file like, optional
            File name or buffer from which to load YAML.

        Returns
        -------
        SegmentedRegressionModel

        """
        cfg = yamlio.yaml_to_dict(yaml_str, str_or_buffer)

        default_model_expr = cfg['default_config']['model_expression']
        default_ytransform = cfg['default_config']['ytransform']

        seg = cls(
            cfg['segmentation_col'], cfg['fit_filters'],
            cfg['predict_filters'], default_model_expr,
            YTRANSFORM_MAPPING[default_ytransform], cfg['min_segment_size'],
            cfg['name'])

        if "models" not in cfg:
            cfg["models"] = {}

        for name, m in cfg['models'].items():
            m['model_expression'] = m.get(
                'model_expression', default_model_expr)
            m['ytransform'] = m.get('ytransform', default_ytransform)
            m['fit_filters'] = None
            m['predict_filters'] = None
            reg = RegressionModel.from_yaml(yamlio.convert_to_yaml(m, None))
            seg._group.add_model(reg)

        logger.debug(
            'loaded segmented regression model {} from yaml'.format(seg.name))
        return seg
def from_yaml ( cls , yaml_str = None , str_or_buffer = None ) : cfg = yamlio . yaml_to_dict ( yaml_str , str_or_buffer ) default_model_expr = cfg [ 'default_config' ] [ 'model_expression' ] default_ytransform = cfg [ 'default_config' ] [ 'ytransform' ] seg = cls ( cfg [ 'segmentation_col' ] , cfg [ 'fit_filters' ] , cfg [ 'predict_filters' ] , default_model_expr , YTRANSFORM_MAPPING [ default_ytransform ] , cfg [ 'min_segment_size' ] , cfg [ 'name' ] ) if "models" not in cfg : cfg [ "models" ] = { } for name , m in cfg [ 'models' ] . items ( ) : m [ 'model_expression' ] = m . get ( 'model_expression' , default_model_expr ) m [ 'ytransform' ] = m . get ( 'ytransform' , default_ytransform ) m [ 'fit_filters' ] = None m [ 'predict_filters' ] = None reg = RegressionModel . from_yaml ( yamlio . convert_to_yaml ( m , None ) ) seg . _group . add_model ( reg ) logger . debug ( 'loaded segmented regression model {} from yaml' . format ( seg . name ) ) return seg