qcodes/utils/numpy_utils.py
def list_of_data_to_maybe_ragged_nd_array(
    column_data: Sequence[Any],
    dtype: Optional[type] = None,
) -> np.ndarray:
    """
    Convert a (nested) Sequence of data to numpy arrays. Handle that
    the elements of the sequence may not have the same length in which
    case the returned array will be of dtype object.

    """
    try:
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore",
                category=VisibleDeprecationWarning,
                message="Creating an ndarray from ragged nested sequences",
            )
            # numpy warns here and coming versions
            # will eventually raise
            # for ragged arrays if you don't explicitly set
            # dtype=object
            # It is time consuming to detect ragged arrays here
            # and it is expected to be a relatively rare situation
            # so fallback to object if the regular dtype fail
            data = np.array(column_data, dtype=dtype)
    except:
        # Not clear which error to catch here. This will only be clarified
        # once numpy actually starts to raise here.
        data = np.array(column_data, dtype=object)
    return data

    Convert a (nested) Sequence of data to numpy arrays. Handle that
    the elements of the sequence may not have the same length in which
    case the returned array will be of dtype object.

    
Convert a (nested) Sequence of data to numpy arrays. Handle that
the elements of the sequence may not have the same length in which
case the returned array will be of dtype object.
Convert a ( nested ) Sequence of data to numpy arrays . Handle that the elements of the sequence may not have the same length in which case the returned array will be of dtype object .
def list_of_data_to_maybe_ragged_nd_array(
    column_data: Sequence[Any],
    dtype: Optional[type] = None,
) -> np.ndarray:
    try:
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore",
                category=VisibleDeprecationWarning,
                message="Creating an ndarray from ragged nested sequences",
            )
            data = np.array(column_data, dtype=dtype)
    except:
        data = np.array(column_data, dtype=object)
    return data
def list_of_data_to_maybe_ragged_nd_array ( column_data : Sequence [ Any ] , dtype : Optional [ type ] = None , ) -> np . ndarray : try : with warnings . catch_warnings ( ) : warnings . filterwarnings ( "ignore" , category = VisibleDeprecationWarning , message = "Creating an ndarray from ragged nested sequences" , ) data = np . array ( column_data , dtype = dtype ) except : data = np . array ( column_data , dtype = object ) return data
Convert a (nested) Sequence of data to numpy arrays.
Convert a ( nested ) Sequence of data to numpy arrays .
"""
    Convert a (nested) Sequence of data to numpy arrays. Handle that
    the elements of the sequence may not have the same length in which
    case the returned array will be of dtype object.

    """ # numpy warns here and coming versions # will eventually raise # for ragged arrays if you don't explicitly set # dtype=object # It is time consuming to detect ragged arrays here # and it is expected to be a relatively rare situation # so fallback to object if the regular dtype fail # Not clear which error to catch here. This will only be clarified # once numpy actually starts to raise here.
column_data
Sequence[Any]
dtype
Optional[type]