code: def _check_possible_tree_participation(
      num_participation: int,
      min_separation: int,
      start: int,
      end: int,
      steps: int,
  ) -> bool:
      """Check if participation is possible with `min_separation` in `steps`.
  
      This function checks if it is possible for a sample to appear
      `num_participation` in `steps`, assuming there are at least `min_separation`
      nodes between the appearance of the same sample in the streaming data (leaf
      nodes in tree aggregation). The first appearance of the sample is after
      `start` steps, and the sample won't appear in the `end` steps after the given
      `steps`.
  
      Args:
        num_participation: The number of times a sample will appear.
        min_separation: The minimum number of nodes between two appearance of a
          sample. If a sample appears in consecutive x, y steps in a streaming
          setting, then `min_separation=y-x-1`.
        start:  The first appearance of the sample is after `start` steps.
        end: The sample won't appear in the `end` steps after the given `steps`.
        steps: Total number of steps (leaf nodes in tree aggregation).
  
      Returns:
        True if a sample can appear `num_participation` with given conditions.
      """
      return (
          start + (min_separation + 1) * num_participation
          <= steps + end
      )
  
file_path: privacy/tensorflow_privacy/privacy/analysis/tree_aggregation_accountant.py
imports: import functools
  import math
  from typing import Collection, Optional, Union
  import dp_accounting
  import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: _check_possible_tree_participation(num_participation, min_separation, start, end, steps) and returns: unknown