class_docstr: Test behaviors of B-splines. The values tested against were returned as of
  SciPy 1.1.0 and are included for regression testing purposes
class_docstr_tok: ["Test","behaviors","of","B-splines",".","The","values","tested","against","were","returned","as","of","SciPy","1.1.0","and","are","included","for","regression","testing","purposes"]
code: def test_cubic(self):
      np.random.seed(12460)
      assert_array_equal(bsp.cubic([0]), array([0]))
      data_array_complex = (
          np.random.rand(4, 4) + np.random.rand(4, 4) * 1j
      )
      data_array_complex = 1 + 1j - 2 * data_array_complex
      # scaling the magnitude by 10 makes the results close enough to zero,
      # that the assertion fails, so just make the elements have a mix of
      # positive and negative imaginary components...
      result_array_complex = array(
          [
              [0.23056563, 0.38414406, 0.08342987, 0.06904847],
              [0.17240848, 0.47055447, 0.63896278, 0.39756424],
              [0.12672571, 0.65862632, 0.1116695, 0.09700386],
              [0.3544116, 0.17856518, 0.1528841, 0.17285762],
          ]
      )
      assert_allclose(
          bsp.cubic(data_array_complex), result_array_complex
      )
  
file_path: catboost/contrib/python/scipy/py3/scipy/signal/tests/test_bsplines.py
imports: import numpy
  from numpy import array
  from numpy.testing import assert_equal, assert_allclose, assert_array_equal, assert_almost_equal
  import pytest
  from pytest import raises
  import scipy.signal.bsplines
  from scipy import signal
label_desc: Use image node_id 5 for calling the TestBSplines obj's underlying member method code with example usage: obj.test_cubic() without return types