code: # -*- coding: utf-8 -*-
  # Licensed under a 3-clause BSD style license - see LICENSE.rst
  
  """This module contains functions and methods that relate to the DataInfo class
  which provides a container for informational attributes as well as summary info
  methods.
  
  A DataInfo object is attached to the Quantity, SkyCoord, and Time classes in
  astropy.  Here it allows those classes to be used in Tables and uniformly carry
  table column attributes such as name, format, dtype, meta, and description.
  """
  
  # Note: these functions and classes are tested extensively in astropy table
  # tests via their use in providing mixin column info, and in
  # astropy/tests/test_info for providing table and column info summary data.
  
  
  import os
  import re
  import sys
  import weakref
  import warnings
  from io import StringIO
  from copy import deepcopy
  from functools import partial
  from collections import OrderedDict
  from contextlib import contextmanager
  
  import numpy as np
  
  from . import metadata
  
  
  __all__ = ['data_info_factory', 'dtype_info_name', 'BaseColumnInfo',
             'DataInfo', 'MixinInfo', 'ParentDtypeInfo']
  
  # Tuple of filterwarnings kwargs to ignore when calling info
  IGNORE_WARNINGS = (dict(category=RuntimeWarning, message='All-NaN|'
                          'Mean of empty slice|Degrees of freedom <= 0|'
                          'invalid value encountered in sqrt'),)
  
  STRING_TYPE_NAMES = {(False, 'S'): 'str',  # not PY3
                       (False, 'U'): 'unicode',
                       (True, 'S'): 'bytes',  # PY3
                       (True, 'U'): 'str'}
  
  
  @contextmanager
  def serialize_context_as(context):
      """Set context for serialization.
  
      This will allow downstream code to understand the context in which a column
      is being serialized.  Objects like Time or SkyCoord will have different
      default serialization representations depending on context.
  
      Parameters
      ----------
      context : str
          Context name, e.g. 'fits', 'hdf5', 'ecsv', 'yaml'
      """
      old_context = BaseColumnInfo._serialize_context
      BaseColumnInfo._serialize_context = context
      yield
      BaseColumnInfo._serialize_context = old_context
  
  
  def dtype_info_name(dtype):
      """Return a human-oriented string name of the ``dtype`` arg.
      This can be use by astropy methods that present type information about
      a data object.
  
      The output is mostly equivalent to ``dtype.name`` which takes the form
      <type_name>[B] where <type_name> is like ``int`` or ``bool`` and [B] is an
      optional number of bits which gets included only for numeric types.
  
      For bytes, string and unicode types, the output is shown below, where <N>
      is the number of characters.  This representation corresponds to the Python
      type that matches the dtype::
  
        Numpy          S<N>      U<N>
        Python      bytes<N>   str<N>
  
      Parameters
      ----------
      dtype : str, np.dtype, type
          Input dtype as an object that can be converted via np.dtype()
  
      Returns
      -------
      dtype_info_name : str
          String name of ``dtype``
      """
      dtype = np.dtype(dtype)
      if dtype.kind in ('S', 'U'):
          length = re.search(r'(\d+)', dtype.str).group(1)
          type_name = STRING_TYPE_NAMES[(True, dtype.kind)]
          out = type_name + length
      else:
          out = dtype.name
  
      return out
  
  
  def data_info_factory(names, funcs):
      """
      Factory to create a function that can be used as an ``option``
      for outputting data object summary information.
  
      Examples
      --------
      >>> from astropy.utils.data_info import data_info_factory
      >>> from astropy.table import Column
      >>> c = Column([4., 3., 2., 1.])
      >>> mystats = data_info_factory(names=['min', 'median', 'max'],
      ...                             funcs=[np.min, np.median, np.max])
      >>> c.info(option=mystats)
      min = 1.0
      median = 2.5
      max = 4.0
      n_bad = 0
      length = 4
  
      Parameters
      ----------
      names : list
          List of information attribute names
      funcs : list
          List of functions that compute the corresponding information attribute
  
      Returns
      -------
      func : function
          Function that can be used as a data info option
      """
      def func(dat):
          outs = []
          for name, func in zip(names, funcs):
              try:
                  if isinstance(func, str):
                      out = getattr(dat, func)()
                  else:
                      out = func(dat)
              except Exception:
                  outs.append('--')
              else:
                  outs.append(str(out))
  
          return OrderedDict(zip(names, outs))
      return func
  
  
  def _get_obj_attrs_map(obj, attrs):
      """
      Get the values for object ``attrs`` and return as a dict.  This
      ignores any attributes that are None and in Py2 converts any unicode
      attribute names or values to str.  In the context of serializing the
      supported core astropy classes this conversion will succeed and results
      in more succinct and less python-specific YAML.
      """
      out = {}
      for attr in attrs:
          val = getattr(obj, attr, None)
  
          if val is not None:
              out[attr] = val
      return out
  
  
  def _get_data_attribute(dat, attr=None):
      """
      Get a data object attribute for the ``attributes`` info summary method
      """
      if attr == 'class':
          val = type(dat).__name__
      elif attr == 'dtype':
          val = dtype_info_name(dat.info.dtype)
      elif attr == 'shape':
          datshape = dat.shape[1:]
          val = datshape if datshape else ''
      else:
          val = getattr(dat.info, attr)
      if val is None:
          val = ''
      return str(val)
  
  
  class InfoAttribute:
      def __init__(self, attr, default=None):
          self.attr = attr
          self.default = default
  
      def __get__(self, instance, owner_cls):
          if instance is None:
              return self
  
          return instance._attrs.get(self.attr, self.default)
  
      def __set__(self, instance, value):
          if instance is None:
              # This is an unbound descriptor on the class
              raise ValueError('cannot set unbound descriptor')
  
          instance._attrs[self.attr] = value
  
  
  class ParentAttribute:
      def __init__(self, attr):
          self.attr = attr
  
      def __get__(self, instance, owner_cls):
          if instance is None:
              return self
  
          return getattr(instance._parent, self.attr)
  
      def __set__(self, instance, value):
          if instance is None:
              # This is an unbound descriptor on the class
              raise ValueError('cannot set unbound descriptor')
  
          setattr(instance._parent, self.attr, value)
  
  
  class DataInfoMeta(type):
      def __new__(mcls, name, bases, dct):
          # Ensure that we do not gain a __dict__, which would mean
          # arbitrary attributes could be set.
          dct.setdefault('__slots__', [])
          return super().__new__(mcls, name, bases, dct)
  
      def __init__(cls, name, bases, dct):
          super().__init__(name, bases, dct)
  
          # Define default getters/setters for attributes, if needed.
          for attr in cls.attr_names:
              if attr not in dct:
                  # If not defined explicitly for this class, did any of
                  # its superclasses define it, and, if so, was this an
                  # automatically defined look-up-on-parent attribute?
                  cls_attr = getattr(cls, attr, None)
                  if attr in cls.attrs_from_parent:
                      # If the attribute is supposed to be stored on the parent,
                      # and that is stated by this class yet it was not the case
                      # on the superclass, override it.
                      if 'attrs_from_parent' in dct and not isinstance(cls_attr, ParentAttribute):
                          setattr(cls, attr, ParentAttribute(attr))
                  elif not cls_attr or isinstance(cls_attr, ParentAttribute):
                      # If the attribute is not meant to be stored on the parent,
                      # and if it was not defined already or was previously defined
                      # as an attribute on the parent, define a regular
                      # look-up-on-info attribute
                      setattr(cls, attr,
                              InfoAttribute(attr, cls._attr_defaults.get(attr)))
  
  
  class DataInfo(metaclass=DataInfoMeta):
      """
      Descriptor that data classes use to add an ``info`` attribute for storing
      data attributes in a uniform and portable way.  Note that it *must* be
      called ``info`` so that the DataInfo() object can be stored in the
      ``instance`` using the ``info`` key.  Because owner_cls.x is a descriptor,
      Python doesn't use __dict__['x'] normally, and the descriptor can safely
      store stuff there.  Thanks to http://nbviewer.ipython.org/urls/gist.github.com/ChrisBeaumont/5758381/raw/descriptor_writeup.ipynb
      for this trick that works for non-hashable classes.
  
      Parameters
      ----------
      bound : bool
          If True this is a descriptor attribute in a class definition, else it
          is a DataInfo() object that is bound to a data object instance. Default is False.
      """
      _stats = ['mean', 'std', 'min', 'max']
      attrs_from_parent = set()
      attr_names = set(['name', 'unit', 'dtype', 'format', 'description', 'meta'])
      _attr_defaults = {'dtype': np.dtype('O')}
      _attrs_no_copy = set()
      _info_summary_attrs = ('dtype', 'shape', 'unit', 'format', 'description', 'class')
      __slots__ = ['_parent_cls', '_parent_ref', '_attrs']
      # This specifies the list of object attributes which must be stored in
      # order to re-create the object after serialization.  This is independent
      # of normal `info` attributes like name or description.  Subclasses will
      # generally either define this statically (QuantityInfo) or dynamically
      # (SkyCoordInfo).  These attributes may be scalars or arrays.  If arrays
      # that match the object length they will be serialized as an independent
      # column.
      _represent_as_dict_attrs = ()
  
      # This specifies attributes which are to be provided to the class
      # initializer as ordered args instead of keyword args.  This is needed
      # for Quantity subclasses where the keyword for data varies (e.g.
      # between Quantity and Angle).
      _construct_from_dict_args = ()
  
      # This specifies the name of an attribute which is the "primary" data.
      # Then when representing as columns
      # (table.serialize._represent_mixin_as_column) the output for this
      # attribute will be written with the just name of the mixin instead of the
      # usual "<name>.<attr>".
      _represent_as_dict_primary_data = None
  
      def __init__(self, bound=False):
          # If bound to a data object instance then create the dict of attributes
          # which stores the info attribute values. Default of None for "unset"
          # except for dtype where the default is object.
          if bound:
              self._attrs = {}
  
      @property
      def _parent(self):
          try:
              parent = self._parent_ref()
          except AttributeError:
              return None
  
          if parent is None:
              raise AttributeError("""\
  failed access "info" attribute on a temporary object.
  
  It looks like you have done something like ``col[3:5].info``, i.e.
  you accessed ``info`` from a temporary slice object ``col[3:5]`` that
  only exists momentarily.  This has failed because the reference to
  that temporary object is now lost.  Instead force a permanent
  reference with ``c = col[3:5]`` followed by ``c.info``.""")
  
          return parent
  
      def __get__(self, instance, owner_cls):
          if instance is None:
              # This is an unbound descriptor on the class
              self._parent_cls = owner_cls
              return self
  
          info = instance.__dict__.get('info')
          if info is None:
              info = instance.__dict__['info'] = self.__class__(bound=True)
          # We set _parent_ref on every call, since if one makes copies of
          # instances, 'info' will be copied as well, which will lose the
          # reference.
          info._parent_ref = weakref.ref(instance)
          return info
  
      def __set__(self, instance, value):
          if instance is None:
              # This is an unbound descriptor on the class
              raise ValueError('cannot set unbound descriptor')
  
          if isinstance(value, DataInfo):
              info = instance.__dict__['info'] = self.__class__(bound=True)
              for attr in info.attr_names - info.attrs_from_parent - info._attrs_no_copy:
                  info._attrs[attr] = deepcopy(getattr(value, attr))
  
          else:
              raise TypeError('info must be set with a DataInfo instance')
  
      def __getstate__(self):
          return self._attrs
  
      def __setstate__(self, state):
          self._attrs = state
  
      def _represent_as_dict(self, attrs=None):
          """Get the values for the parent ``attrs`` and return as a dict.
  
          By default, uses '_represent_as_dict_attrs'.
          """
          if attrs is None:
              attrs = self._represent_as_dict_attrs
          return _get_obj_attrs_map(self._parent, attrs)
  
      def _construct_from_dict(self, map):
          args = [map.pop(attr) for attr in self._construct_from_dict_args]
          return self._parent_cls(*args, **map)
  
      info_summary_attributes = staticmethod(
          data_info_factory(names=_info_summary_attrs,
                            funcs=[partial(_get_data_attribute, attr=attr)
                                   for attr in _info_summary_attrs]))
  
      # No nan* methods in numpy < 1.8
      info_summary_stats = staticmethod(
          data_info_factory(names=_stats,
                            funcs=[getattr(np, 'nan' + stat)
                                   for stat in _stats]))
  
      def __call__(self, option='attributes', out=''):
          """
          Write summary information about data object to the ``out`` filehandle.
          By default this prints to standard output via sys.stdout.
  
          The ``option`` argument specifies what type of information
          to include.  This can be a string, a function, or a list of
          strings or functions.  Built-in options are:
  
          - ``attributes``: data object attributes like ``dtype`` and ``format``
          - ``stats``: basic statistics: min, mean, and max
  
          If a function is specified then that function will be called with the
          data object as its single argument.  The function must return an
          OrderedDict containing the information attributes.
  
          If a list is provided then the information attributes will be
          appended for each of the options, in order.
  
          Examples
          --------
  
          >>> from astropy.table import Column
          >>> c = Column([1, 2], unit='m', dtype='int32')
          >>> c.info()
          dtype = int32
          unit = m
          class = Column
          n_bad = 0
          length = 2
  
          >>> c.info(['attributes', 'stats'])
          dtype = int32
          unit = m
          class = Column
          mean = 1.5
          std = 0.5
          min = 1
          max = 2
          n_bad = 0
          length = 2
  
          Parameters
          ----------
          option : str, function, list of (str or function)
              Info option, defaults to 'attributes'.
          out : file-like object, None
              Output destination, defaults to sys.stdout.  If None then the
              OrderedDict with information attributes is returned
  
          Returns
          -------
          info : OrderedDict if out==None else None
          """
          if out == '':
              out = sys.stdout
  
          dat = self._parent
          info = OrderedDict()
          name = dat.info.name
          if name is not None:
              info['name'] = name
  
          options = option if isinstance(option, (list, tuple)) else [option]
          for option in options:
              if isinstance(option, str):
                  if hasattr(self, 'info_summary_' + option):
                      option = getattr(self, 'info_summary_' + option)
                  else:
                      raise ValueError('option={} is not an allowed information type'
                                       .format(option))
  
              with warnings.catch_warnings():
                  for ignore_kwargs in IGNORE_WARNINGS:
                      warnings.filterwarnings('ignore', **ignore_kwargs)
                  info.update(option(dat))
  
          if hasattr(dat, 'mask'):
              n_bad = np.count_nonzero(dat.mask)
          else:
              try:
                  n_bad = np.count_nonzero(np.isinf(dat) | np.isnan(dat))
              except Exception:
                  n_bad = 0
          info['n_bad'] = n_bad
  
          try:
              info['length'] = len(dat)
          except (TypeError, IndexError):
              pass
  
          if out is None:
              return info
  
          for key, val in info.items():
              if val != '':
                  out.write(f'{key} = {val}' + os.linesep)
  
      def __repr__(self):
          if self._parent is None:
              return super().__repr__()
  
          out = StringIO()
          self.__call__(out=out)
          return out.getvalue()
  
  
  class BaseColumnInfo(DataInfo):
      """
      Base info class for anything that can be a column in an astropy
      Table.  There are at least two classes that inherit from this:
  
        ColumnInfo: for native astropy Column / MaskedColumn objects
        MixinInfo: for mixin column objects
  
      Note that this class is defined here so that mixins can use it
      without importing the table package.
      """
      attr_names = DataInfo.attr_names.union(['parent_table', 'indices'])
      _attrs_no_copy = set(['parent_table'])
  
      # Context for serialization.  This can be set temporarily via
      # ``serialize_context_as(context)`` context manager to allow downstream
      # code to understand the context in which a column is being serialized.
      # Typical values are 'fits', 'hdf5', 'ecsv', 'yaml'.  Objects like Time or
      # SkyCoord will have different default serialization representations
      # depending on context.
      _serialize_context = None
      __slots__ = ['_format_funcs', '_copy_indices']
  
      @property
      def parent_table(self):
          value = self._attrs.get('parent_table')
          if callable(value):
              value = value()
          return value
  
      @parent_table.setter
      def parent_table(self, parent_table):
          if parent_table is None:
              self._attrs.pop('parent_table', None)
          else:
              parent_table = weakref.ref(parent_table)
              self._attrs['parent_table'] = parent_table
  
      def __init__(self, bound=False):
          super().__init__(bound=bound)
  
          # If bound to a data object instance then add a _format_funcs dict
          # for caching functions for print formatting.
          if bound:
              self._format_funcs = {}
  
      def iter_str_vals(self):
          """
          This is a mixin-safe version of Column.iter_str_vals.
          """
          col = self._parent
          if self.parent_table is None:
              from astropy.table.column import FORMATTER as formatter
          else:
              formatter = self.parent_table.formatter
  
          _pformat_col_iter = formatter._pformat_col_iter
          for str_val in _pformat_col_iter(col, -1, False, False, {}):
              yield str_val
  
      def adjust_indices(self, index, value, col_len):
          '''
          Adjust info indices after column modification.
  
          Parameters
          ----------
          index : slice, int, list, or ndarray
              Element(s) of column to modify. This parameter can
              be a single row number, a list of row numbers, an
              ndarray of row numbers, a boolean ndarray (a mask),
              or a column slice.
          value : int, list, or ndarray
              New value(s) to insert
          col_len : int
              Length of the column
          '''
          if not self.indices:
              return
  
          if isinstance(index, slice):
              # run through each key in slice
              t = index.indices(col_len)
              keys = list(range(*t))
          elif isinstance(index, np.ndarray) and index.dtype.kind == 'b':
              # boolean mask
              keys = np.where(index)[0]
          else:  # single int
              keys = [index]
  
          value = np.atleast_1d(value)  # turn array(x) into array([x])
          if value.size == 1:
              # repeat single value
              value = list(value) * len(keys)
  
          for key, val in zip(keys, value):
              for col_index in self.indices:
                  col_index.replace(key, self.name, val)
  
      def slice_indices(self, col_slice, item, col_len):
          '''
          Given a sliced object, modify its indices
          to correctly represent the slice.
  
          Parameters
          ----------
          col_slice : Column or mixin
              Sliced object
          item : slice, list, or ndarray
              Slice used to create col_slice
          col_len : int
              Length of original object
          '''
          from astropy.table.sorted_array import SortedArray
          if not getattr(self, '_copy_indices', True):
              # Necessary because MaskedArray will perform a shallow copy
              col_slice.info.indices = []
              return col_slice
          elif isinstance(item, slice):
              col_slice.info.indices = [x[item] for x in self.indices]
          elif self.indices:
              if isinstance(item, np.ndarray) and item.dtype.kind == 'b':
                  # boolean mask
                  item = np.where(item)[0]
              threshold = 0.6
              # Empirical testing suggests that recreating a BST/RBT index is
              # more effective than relabelling when less than ~60% of
              # the total number of rows are involved, and is in general
              # more effective for SortedArray.
              small = len(item) <= 0.6 * col_len
              col_slice.info.indices = []
              for index in self.indices:
                  if small or isinstance(index, SortedArray):
                      new_index = index.get_slice(col_slice, item)
                  else:
                      new_index = deepcopy(index)
                      new_index.replace_rows(item)
                  col_slice.info.indices.append(new_index)
  
          return col_slice
  
      @staticmethod
      def merge_cols_attributes(cols, metadata_conflicts, name, attrs):
          """
          Utility method to merge and validate the attributes ``attrs`` for the
          input table columns ``cols``.
  
          Note that ``dtype`` and ``shape`` attributes are handled specially.
          These should not be passed in ``attrs`` but will always be in the
          returned dict of merged attributes.
  
          Parameters
          ----------
          cols : list
              List of input Table column objects
          metadata_conflicts : str ('warn'|'error'|'silent')
              How to handle metadata conflicts
          name : str
              Output column name
          attrs : list
              List of attribute names to be merged
  
          Returns
          -------
          attrs : dict of merged attributes
  
          """
          from astropy.table.np_utils import TableMergeError
  
          def warn_str_func(key, left, right):
              out = ("In merged column '{}' the '{}' attribute does not match "
                     "({} != {}).  Using {} for merged output"
                     .format(name, key, left, right, right))
              return out
  
          def getattrs(col):
              return {attr: getattr(col.info, attr) for attr in attrs
                      if getattr(col.info, attr, None) is not None}
  
          out = getattrs(cols[0])
          for col in cols[1:]:
              out = metadata.merge(out, getattrs(col), metadata_conflicts=metadata_conflicts,
                                   warn_str_func=warn_str_func)
  
          # Output dtype is the superset of all dtypes in in_cols
          out['dtype'] = metadata.common_dtype(cols)
  
          # Make sure all input shapes are the same
          uniq_shapes = set(col.shape[1:] for col in cols)
          if len(uniq_shapes) != 1:
              raise TableMergeError('columns have different shapes')
          out['shape'] = uniq_shapes.pop()
  
          # "Merged" output name is the supplied name
          if name is not None:
              out['name'] = name
  
          return out
  
      def get_sortable_arrays(self):
          """
          Return a list of arrays which can be lexically sorted to represent
          the order of the parent column.
  
          The base method raises NotImplementedError and must be overridden.
  
          Returns
          -------
          arrays : list of ndarray
          """
          raise NotImplementedError(f'column {self.name} is not sortable')
  
  
  class MixinInfo(BaseColumnInfo):
  
      @property
      def name(self):
          return self._attrs.get('name')
  
      @name.setter
      def name(self, name):
          # For mixin columns that live within a table, rename the column in the
          # table when setting the name attribute.  This mirrors the same
          # functionality in the BaseColumn class.
          if self.parent_table is not None:
              from astropy.table.np_utils import fix_column_name
              new_name = fix_column_name(name)  # Ensure col name is numpy compatible
              self.parent_table.columns._rename_column(self.name, new_name)
  
          self._attrs['name'] = name
  
  
  class ParentDtypeInfo(MixinInfo):
      """Mixin that gets info.dtype from parent"""
  
      attrs_from_parent = set(['dtype'])  # dtype and unit taken from parent
  
apis: numpy.dtype numpy.isinf numpy.count_nonzero numpy.atleast_1d numpy.isnan numpy.where