code: def test_sparse_bin():
      s1 = SparseNDArray(s1_data)
      s2 = SparseNDArray(s2_data)
      v = SparseNDArray(v1, shape=(3,))
  
      for method in (
          "fmod",
          "logaddexp",
          "logaddexp2",
          "equal",
          "not_equal",
          "less",
          "less_equal",
          "greater",
          "greater_equal",
          "hypot",
          "arctan2",
      ):
          lm, rm = getattr(mls, method), getattr(np, method)
          assert_array_equal(lm(s1, s2), rm(s1.toarray(), s2.toarray()))
          assert_array_equal(lm(s1, d1), rm(s1.toarray(), d1))
          assert_array_equal(lm(d1, s1), rm(d1, s1.toarray()))
          r1 = sps.csr_matrix(
              (rm(s1.data, 2), s1.indices, s1.indptr), s1.shape
          )
          assert_array_equal(lm(s1, 2), r1)
          r2 = sps.csr_matrix(
              (rm(2, s1.data), s1.indices, s1.indptr), s1.shape
          )
          assert_array_equal(lm(2, s1), r2)
  
          # test sparse
          assert_array_equal(lm(v, v), rm(v1_data, v1_data))
          assert_array_equal(lm(v, d1), rm(v1_data, d1))
          assert_array_equal(lm(d1, v), rm(d1, v1_data))
          assert_array_equal(lm(v, 2), rm(v1_data, 2))
          assert_array_equal(lm(2, v), rm(2, v1_data))
  
imports: import pickle
  import numpy
  import pytest
  import scipy.sparse
  from ...None import sparse
  from ..None import SparseNDArray, SparseVector, SparseMatrix
  from ..core import issparse
label_desc: Use image node_id 10 for calling a global function with example usage: test_sparse_bin() without return types