Пример #1
0
    def load_yaml(self,
                  config_files,
                  file_names_as_key=False,
                  return_config=False):
        """Load file (or files).

        Args:
            config_files: Preferably list of file paths
            file_names_as_key: False | True
            return_config: False | True
        """
        if not isinstance(config_files, (list, np.ndarray)):
            config_files = [config_files]

        for config_file in config_files:
            with open(config_file, encoding='cp1252') as fd:
                try:
                    file = yaml.load(fd, Loader=yaml.FullLoader)
                except yaml.YAMLError:
                    file = yaml.safe_load(fd)
                if file_names_as_key:
                    file_name = self.get_file_name(config_file)
                    self.config[file_name] = file
                else:
                    self.config = utils.recursive_dict_update(
                        self.config, file)

        if return_config:
            return self.config
Пример #2
0
    def get_metadata(self, serie, map_keys=True, **kwargs):
        """Return dictionary with metadata."""
        meta_dict = {}
        data = self.get_meta_dict(
            serie,
            identifier=self.settings.datasets['vp2'].get('identifier_metadata'),
            separator=self.settings.datasets['vp2'].get('separator_metadata'),
            keys=self.settings.datasets['vp2'].get('keys_metadata'),
        )

        meta_dict = utils.recursive_dict_update(meta_dict, data)

        if map_keys:
            meta_dict = {self.settings.pmap.get(key): meta_dict[key] for key in meta_dict}

        return meta_dict
Пример #3
0
    def get_metadata(self, serie, map_keys=True, filename=None):
        """Return dictionary with metadata."""
        meta_dict = {}
        for ident, sep in zip(['identifier_metadata', 'identifier_metadata_2'],
                              ['separator_metadata', 'separator_metadata_2']):
            data = self.get_meta_dict(serie,
                                      identifier=self.settings.datasets['cnv'].get(ident),
                                      separator=self.settings.datasets['cnv'].get(sep),
                                      keys=self.settings.datasets['cnv'].get('keys_metadata'))

            meta_dict = utils.recursive_dict_update(meta_dict, data)

        if map_keys:
            meta_dict = {self.settings.pmap.get(key): meta_dict[key] for key in meta_dict}

        return meta_dict