class_docstr: Tests specific to IntervalIndex.from_arrays
docstr: mixed int/float left/right results in float for both sides
docstr_tok: ["mixed","int\/float","left\/right","results","in","float","for","both","sides"]
code: def test_mixed_float_int(self, left_subtype, right_subtype):
      """mixed int/float left/right results in float for both sides"""
      left = np.arange(9, dtype=left_subtype)
      right = np.arange(1, 10, dtype=right_subtype)
      result = IntervalIndex.from_arrays(left, right)
  
      expected_left = Index(left, dtype=np.float64)
      expected_right = Index(right, dtype=np.float64)
      expected_subtype = np.float64
  
      tm.assert_index_equal(result.left, expected_left)
      tm.assert_index_equal(result.right, expected_right)
      assert result.dtype.subtype == expected_subtype
  
imports: from functools import partial
  import numpy
  import pytest
  import pandas.util._test_decorators
  from pandas.core.dtypes.common import is_unsigned_integer_dtype
  from pandas.core.dtypes.dtypes import IntervalDtype
  from pandas import Categorical, CategoricalDtype, CategoricalIndex, Index, Interval, IntervalIndex, date_range, notna, period_range, timedelta_range
  import pandas._testing
  from pandas.core.arrays import IntervalArray
  import pandas.core.common
label_desc: Use image node_id 4 for calling the TestFromArrays obj's underlying member method code with example usage: obj.test_mixed_float_int(left_subtype, right_subtype) without return types