code: def test_fillna(self):
      s = SparseArray([1, np.nan, np.nan, 3, np.nan])
      res = s.fillna(-1)
      exp = SparseArray(
          [1, -1, -1, 3, -1], fill_value=-1, dtype=np.float64
      )
      tm.assert_sp_array_equal(res, exp)
  
      s = SparseArray([1, np.nan, np.nan, 3, np.nan], fill_value=0)
      res = s.fillna(-1)
      exp = SparseArray(
          [1, -1, -1, 3, -1], fill_value=0, dtype=np.float64
      )
      tm.assert_sp_array_equal(res, exp)
  
      s = SparseArray([1, np.nan, 0, 3, 0])
      res = s.fillna(-1)
      exp = SparseArray(
          [1, -1, 0, 3, 0], fill_value=-1, dtype=np.float64
      )
      tm.assert_sp_array_equal(res, exp)
  
      s = SparseArray([1, np.nan, 0, 3, 0], fill_value=0)
      res = s.fillna(-1)
      exp = SparseArray(
          [1, -1, 0, 3, 0], fill_value=0, dtype=np.float64
      )
      tm.assert_sp_array_equal(res, exp)
  
      s = SparseArray([np.nan, np.nan, np.nan, np.nan])
      res = s.fillna(-1)
      exp = SparseArray(
          [-1, -1, -1, -1], fill_value=-1, dtype=np.float64
      )
      tm.assert_sp_array_equal(res, exp)
  
      s = SparseArray([np.nan, np.nan, np.nan, np.nan], fill_value=0)
      res = s.fillna(-1)
      exp = SparseArray(
          [-1, -1, -1, -1], fill_value=0, dtype=np.float64
      )
      tm.assert_sp_array_equal(res, exp)
  
      # float dtype's fill_value is np.nan, replaced by -1
      s = SparseArray([0.0, 0.0, 0.0, 0.0])
      res = s.fillna(-1)
      exp = SparseArray([0.0, 0.0, 0.0, 0.0], fill_value=-1)
      tm.assert_sp_array_equal(res, exp)
  
      # int dtype shouldn't have missing. No changes.
      s = SparseArray([0, 0, 0, 0])
      assert s.dtype == SparseDtype(np.int64)
      assert s.fill_value == 0
      res = s.fillna(-1)
      tm.assert_sp_array_equal(res, s)
  
      s = SparseArray([0, 0, 0, 0], fill_value=0)
      assert s.dtype == SparseDtype(np.int64)
      assert s.fill_value == 0
      res = s.fillna(-1)
      exp = SparseArray([0, 0, 0, 0], fill_value=0)
      tm.assert_sp_array_equal(res, exp)
  
      # fill_value can be nan if there is no missing hole.
      # only fill_value will be changed
      s = SparseArray([0, 0, 0, 0], fill_value=np.nan)
      assert s.dtype == SparseDtype(np.int64, fill_value=np.nan)
      assert np.isnan(s.fill_value)
      res = s.fillna(-1)
      exp = SparseArray([0, 0, 0, 0], fill_value=-1)
      tm.assert_sp_array_equal(res, exp)
  
imports: import re
  import numpy
  import pytest
  from pandas._libs.sparse import IntIndex
  import pandas
  from pandas import SparseDtype, isna
  import pandas._testing
  from pandas.core.arrays.sparse import SparseArray
label_desc: Use image node_id 11 for calling the TestSparseArray obj's underlying member method code with example usage: obj.test_fillna() without return types