code: def test_result_filter():
      filter_0 = neurovault.ResultFilter(
          query_terms={"a": 0},
          callable_filter=lambda d: len(d) < 5,
          b=1,
      )
  
      assert str(filter_0) == "ResultFilter"
      assert filter_0["a"] == 0
      assert filter_0({"a": 0, "b": 1, "c": 2})
      assert not filter_0({"a": 0, "b": 1, "c": 2, "d": 3, "e": 4})
      assert not filter_0({"b": 1, "c": 2, "d": 3})
      assert not filter_0({"a": 1, "b": 1, "c": 2})
  
      filter_1 = neurovault.ResultFilter(query_terms={"c": 2})
      filter_1["d"] = neurovault.NotNull()
  
      assert filter_1({"c": 2, "d": 1})
      assert not filter_1({"c": 2, "d": 0})
  
      filter_1["d"] = neurovault.IsIn(0, 1)
  
      assert filter_1({"c": 2, "d": 1})
      assert not filter_1({"c": 2, "d": 2})
  
      del filter_1["d"]
  
      assert filter_1({"c": 2, "d": 2})
  
      filter_1["d"] = neurovault.NotIn(0, 1)
  
      assert not filter_1({"c": 2, "d": 1})
      assert filter_1({"c": 2, "d": 3})
  
      filter_1.add_filter(lambda d: len(d) > 2)
  
      assert not filter_1({"c": 2, "d": 3})
      assert filter_1({"c": 2, "d": 3, "e": 4})
  
imports: import hashlib
  import json
  import os
  import re
  import stat
  from urllib import parse
  import numpy
  import pandas
  import pytest
  import requests
  from nilearn._utils.data_gen import generate_fake_fmri
  from nilearn.conftest import _rng
  from nilearn.datasets import neurovault
  from nilearn.image import load_img
label_desc: Use image node_id 24 for calling a global function with example usage: test_result_filter() without return types