class_docstr: Implementation of Effective complexity metric by Nguyen at el., 2020.
  
  Effective complexity measures how many attributions in absolute values are exceeding a certain threshold (eps)
  where a value above the specified threshold implies that the features are important and under indicates it is not.
  
  References:
      1) An-phi Nguyen and María Rodríguez Martínez.: "On quantitative aspects of model
      interpretability." arXiv preprint arXiv:2007.07584 (2020).
  
  Attributes:
      -  _name: The name of the metric.
      - _data_applicability: The data types that the metric implementation currently supports.
      - _models: The model types that this metric can work with.
      - score_direction: How to interpret the scores, whether higher/ lower values are considered better.
      - evaluation_category: What property/ explanation quality that this metric measures.
docstr: Evaluate instance gets model and data for a single instance as input and returns the evaluation result.
  
  Parameters
  ----------
  a: np.ndarray
      The explanation to be evaluated on an instance-basis.
  
  Returns
  -------
  integer
      The evaluation results.
code: def evaluate_instance(self, a: np.ndarray) -> int:
      """
      Evaluate instance gets model and data for a single instance as input and returns the evaluation result.
  
      Parameters
      ----------
      a: np.ndarray
          The explanation to be evaluated on an instance-basis.
  
      Returns
      -------
      integer
          The evaluation results.
      """
  
      a = a.flatten()
      return int(np.sum(a > self.eps))
  
file_path: Quantus/quantus/metrics/complexity/effective_complexity.py
imports: import sys
  from typing import Any, Callable, Dict, List, Optional
  import numpy
  from quantus.helpers import warn
  from quantus.helpers.enums import DataType, EvaluationCategory, ModelType, ScoreDirection
  from quantus.metrics.base import Metric
label_desc: Use image node_id 3 for calling the EffectiveComplexity obj's underlying member method code with example usage: obj.evaluate_instance(a) and returns: int