Source code for astropy.utils.metadata.utils

# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""This module contains helper functions handling metadata."""

import numpy as np

from .exceptions import MergeConflictError

__all__ = ["common_dtype"]


def dtype(arr):
    return getattr(arr, "dtype", np.dtype("O"))


[docs] def common_dtype(arrs): """ Use numpy to find the common dtype for a list of ndarrays. Only allow arrays within the following fundamental numpy data types: ``np.bool_``, ``np.object_``, ``np.number``, ``np.character``, ``np.void`` Parameters ---------- arrs : list of ndarray Arrays for which to find the common dtype Returns ------- dtype_str : str String representation of dytpe (dtype ``str`` attribute) """ dt = result_type(arrs) return dt.str if dt.names is None else dt.descr
def result_type(arrs): """ Use numpy to find the common type for a list of ndarray. The difference with `numpy.result_type` is that all arrays should share the same fundamental numpy data type, one of: ``np.bool_``, ``np.object_``, ``np.number``, ``np.character``, ``np.void`` Hence, a mix like integer and string will raise instead of resulting in a string type. Parameters ---------- arrs : list of ndarray Array likes for which to find the common dtype. Anything not an array (e.g, |Time|), will be considered an object array. Returns ------- dtype : ~numpy.dtype The common type. """ dtypes = [dtype(arr) for arr in arrs] np_types = (np.bool_, np.object_, np.number, np.character, np.void) uniq_types = { tuple(issubclass(dt.type, np_type) for np_type in np_types) for dt in dtypes } if len(uniq_types) > 1: # Embed into the exception the actual list of incompatible types. incompat_types = [dt.name for dt in dtypes] tme = MergeConflictError(f"Arrays have incompatible types {incompat_types}") tme._incompat_types = incompat_types raise tme return np.result_type(*dtypes)