code: def convert_np_to_UvS_as_Series(
      obj: np.ndarray, store=None
  ) -> pd.Series:
      if not isinstance(obj, np.ndarray) or obj.ndim > 2:
          raise TypeError(
              "input must be a one-column np.ndarray of dim 1 or 2"
          )
  
      if obj.ndim == 2 and obj.shape[1] != 1:
          raise TypeError(
              "input must be a one-column np.ndarray of dim 1 or 2"
          )
  
      res = pd.Series(obj.flatten())
  
      # add index from store if stored and length fits
      if (
          isinstance(store, dict)
          and "index" in store.keys()
          and len(store["index"]) == obj.shape[0]
      ):
          res.index = store["index"]
  
      if isinstance(store, dict) and "name" in store.keys():
          res.name = store["name"]
  
      return res
  
file_path: sktime/sktime/datatypes/_series/_convert.py
imports: import numpy
  import pandas
  from sktime.datatypes._convert_utils._coerce import _coerce_df_dtypes
  from sktime.datatypes._convert_utils._convert import _extend_conversions
  from sktime.datatypes._registry import MTYPE_LIST_SERIES
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 7 for calling a global function with example usage: convert_np_to_UvS_as_Series(obj, store) and returns: res