code: def test_1var():
      rands = [
          -0.21698284,
          0.41900591,
          0.02349374,
          -0.218552,
          -0.3513699,
          0.33418304,
          0.04226855,
          0.213303,
          0.45948731,
          0.33587736,
      ]
  
      x = numpy.arange(10) + 1
      y = numpy.arange(10) + 1 + rands
  
      params = lmfit.Parameters()
      params.add(name="m", value=1.0, vary=True)
      params.add(name="c", value=0.0, vary=False)
  
      out = lmfit.minimize(linear_chisq, params, args=(x, y))
  
      assert_allclose(params["m"].value, 1.025, rtol=0.02, atol=0.02)
      assert len(params) == 2
      assert out.nvarys == 1
      assert out.chisqr > 0.01
      assert out.chisqr < 5.00
  
imports: import numpy
  from numpy.testing import assert_allclose
  import lmfit
label_desc: Use image node_id 2 for calling a global function with example usage: test_1var() without return types