code: def test_nanmin(
      *,
      dtype_x_axis_castable,
      initial,
      keep_dims,
      test_flags,
      backend_fw,
      fn_name,
      on_device,
  ):
      (
          input_dtype,
          x,
          axis,
          castable_dtype,
          dtype3,
          where,
      ) = dtype_x_axis_castable
      x = x[0]
      helpers.test_function(
          input_dtypes=[input_dtype, dtype3[0]],
          test_flags=test_flags,
          rtol_=1e-1,
          atol_=1e-1,
          backend_to_test=backend_fw,
          fn_name=fn_name,
          on_device=on_device,
          a=x,
          axis=axis,
          keepdims=keep_dims,
          initial=initial,
          where=where[0],
      )
  
imports: from hypothesis import strategies
  import numpy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test
  from ivy_tests.test_ivy.test_functional.test_core.test_statistical import _statistical_dtype_values, _get_castable_dtype
label_desc: Use image node_id 16 for calling a global function with example usage: test_nanmin() without return types