class_docstr: Abstract base class for time series clusterer.
  
  Parameters
  ----------
  n_clusters: int, defaults = None
      Number of clusters for model.
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docstr: Check the capabilities of the clusterer matches input data requirements.
  
  Parameters
  ----------
  missing : boolean
      Defines if the data has missing value. True if data has missing values,
      False if no missing.
  multivariate : boolean
      Defines if the data is multivariate. True if data is multivariate, False
      if the data is univariate
  unequal : boolean
      Defines if the data is unequal length. True if data is unequal length,
      False if the data is equal length.
  
  Raises
  ------
  ValueError
      if the capabilities in self._tags do not handle the data.
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code: def _check_capabilities(
      self, missing: bool, multivariate: bool, unequal: bool
  ):
      """Check the capabilities of the clusterer matches input data requirements.
  
      Parameters
      ----------
      missing : boolean
          Defines if the data has missing value. True if data has missing values,
          False if no missing.
      multivariate : boolean
          Defines if the data is multivariate. True if data is multivariate, False
          if the data is univariate
      unequal : boolean
          Defines if the data is unequal length. True if data is unequal length,
          False if the data is equal length.
  
      Raises
      ------
      ValueError
          if the capabilities in self._tags do not handle the data.
      """
      allow_multivariate = self.get_tag("capability:multivariate")
      allow_missing = self.get_tag("capability:missing_values")
      allow_unequal = self.get_tag("capability:unequal_length")
      if missing and not allow_missing:
          raise ValueError(
              "The data has missing values, this clusterer cannot handle missing "
              "values"
          )
      if multivariate and not allow_multivariate:
          raise ValueError(
              "X must be univariate, this clusterer cannot deal with "
              "multivariate input."
          )
      if unequal and not allow_unequal:
          raise ValueError(
              "The data has unequal length series, this clusterer cannot handle "
              "unequal length series"
          )
  
imports: import time
  from typing import Any, Union
  import numpy
  import pandas
  from sktime.base import BaseEstimator
  from sktime.datatypes import check_is_scitype, convert_to, scitype_to_mtype
  from sktime.utils.sklearn import is_sklearn_transformer
  from sktime.utils.validation import check_n_jobs
  from sktime.utils.validation._dependencies import _check_estimator_deps
label_desc: Use image node_id 12 for calling the BaseClusterer obj's underlying member method code with example usage: obj._check_capabilities(missing, multivariate, unequal) without return types