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_spline_filter(self):
      np.random.seed(12457)
      # Test the type-error branch
      raises(TypeError, bsp.spline_filter, array([0]), 0)
      # Test the complex branch
      data_array_complex = (
          np.random.rand(7, 7) + np.random.rand(7, 7) * 1j
      )
      # make the magnitude exceed 1, and make some negative
      data_array_complex = 10 * (1 + 1j - 2 * data_array_complex)
      result_array_complex = array(
          [
              [
                  -4.61489230e-01 - 1.92994022j,
                  8.33332443 + 6.25519943j,
                  6.96300745e-01 - 9.05576038j,
                  5.28294849 + 3.97541356j,
                  5.92165565 + 7.68240595j,
                  6.59493160 - 1.04542804j,
                  9.84503460 - 5.85946894j,
              ],
              [
                  -8.78262329 - 8.4295969j,
                  7.20675516 + 5.47528982j,
                  -8.17223072 + 2.06330729j,
                  -4.38633347 - 8.65968037j,
                  9.89916801 - 8.91720295j,
                  2.67755103 + 8.8706522j,
                  6.24192142 + 3.76879835j,
              ],
              [
                  -3.15627527 + 2.56303072j,
                  9.87658501 - 0.82838702j,
                  -9.96930313 + 8.72288895j,
                  3.17193985 + 6.42474651j,
                  -4.50919819 - 6.84576082j,
                  5.75423431 + 9.94723988j,
                  9.65979767 + 6.90665293j,
              ],
              [
                  -8.28993416 - 6.61064005j,
                  9.71416473e-01 - 9.44907284j,
                  -2.38331890 + 9.25196648j,
                  -7.08868170 - 0.77403212j,
                  4.89887714 + 7.05371094j,
                  -1.37062311 - 2.73505688j,
                  7.70705748 + 2.5395329j,
              ],
              [
                  2.51528406 - 1.82964492j,
                  3.65885472 + 2.95454836j,
                  5.16786575 - 1.66362023j,
                  -8.77737999e-03 + 5.72478867j,
                  4.10533333 - 3.10287571j,
                  9.04761887 + 1.54017115j,
                  -5.77960968e-01 - 7.87758923j,
              ],
              [
                  9.86398506 - 3.98528528j,
                  -4.71444130 - 2.44316983j,
                  -1.68038976 - 1.12708664j,
                  2.84695053 + 1.01725709j,
                  1.14315915 - 8.89294529j,
                  -3.17127085 - 5.42145538j,
                  1.91830420 - 6.16370344j,
              ],
              [
                  7.13875294 + 2.91851187j,
                  -5.35737514 + 9.64132309j,
                  -9.66586399 + 0.70250005j,
                  -9.87717438 - 2.0262239j,
                  9.93160629 + 1.5630846j,
                  4.71948051 - 2.22050714j,
                  9.49550819 + 7.8995142j,
              ],
          ]
      )
      # FIXME: for complex types, the computations are done in
      # single precision (reason unclear). When this is changed,
      # this test needs updating.
      assert_allclose(
          bsp.spline_filter(data_array_complex, 0),
          result_array_complex,
          rtol=1e-6,
      )
      # Test the real branch
      np.random.seed(12457)
      data_array_real = np.random.rand(12, 12)
      # make the magnitude exceed 1, and make some negative
      data_array_real = 10 * (1 - 2 * data_array_real)
      result_array_real = array(
          [
              [
                  -0.463312621,
                  8.33391222,
                  0.697290949,
                  5.28390836,
                  5.92066474,
                  6.59452137,
                  9.84406950,
                  -8.78324188,
                  7.20675750,
                  -8.17222994,
                  -4.38633345,
                  9.89917069,
              ],
              [
                  2.67755154,
                  6.24192170,
                  -3.15730578,
                  9.87658581,
                  -9.96930425,
                  3.17194115,
                  -4.50919947,
                  5.75423446,
                  9.65979824,
                  -8.29066885,
                  0.971416087,
                  -2.38331897,
              ],
              [
                  -7.08868346,
                  4.89887705,
                  -1.37062289,
                  7.70705838,
                  2.51526461,
                  3.65885497,
                  5.16786604,
                  -8.77715342e-03,
                  4.10533325,
                  9.04761993,
                  -0.577960351,
                  9.86382519,
              ],
              [
                  -4.71444301,
                  -1.68038985,
                  2.84695116,
                  1.14315938,
                  -3.17127091,
                  1.91830461,
                  7.13779687,
                  -5.35737482,
                  -9.66586425,
                  -9.87717456,
                  9.93160672,
                  4.71948144,
              ],
              [
                  9.49551194,
                  -1.92958436,
                  6.25427993,
                  -9.05582911,
                  3.97562282,
                  7.68232426,
                  -1.04514824,
                  -5.86021443,
                  -8.43007451,
                  5.47528997,
                  2.06330736,
                  -8.65968112,
              ],
              [
                  -8.91720100,
                  8.87065356,
                  3.76879937,
                  2.56222894,
                  -0.828387146,
                  8.72288903,
                  6.42474741,
                  -6.84576083,
                  9.94724115,
                  6.90665380,
                  -6.61084494,
                  -9.44907391,
              ],
              [
                  9.25196790,
                  -0.774032030,
                  7.05371046,
                  -2.73505725,
                  2.53953305,
                  -1.82889155,
                  2.95454824,
                  -1.66362046,
                  5.72478916,
                  -3.10287679,
                  1.54017123,
                  -7.87759020,
              ],
              [
                  -3.98464539,
                  -2.44316992,
                  -1.12708657,
                  1.01725672,
                  -8.89294671,
                  -5.42145629,
                  -6.16370321,
                  2.91775492,
                  9.64132208,
                  0.702499998,
                  -2.02622392,
                  1.56308431,
              ],
              [
                  -2.22050773,
                  7.89951554,
                  5.98970713,
                  -7.35861835,
                  5.45459283,
                  -7.76427957,
                  3.67280490,
                  -4.05521315,
                  4.51967507,
                  -3.22738749,
                  -3.65080177,
                  3.05630155,
              ],
              [
                  -6.21240584,
                  -0.296796126,
                  -8.34800163,
                  9.21564563,
                  -3.61958784,
                  -4.77120006,
                  -3.99454057,
                  1.05021988e-03,
                  -6.95982829,
                  6.04380797,
                  8.43181250,
                  -2.71653339,
              ],
              [
                  1.19638037,
                  6.99718842e-02,
                  6.72020394,
                  -2.13963198,
                  3.75309875,
                  -5.70076744,
                  5.92143551,
                  -7.22150575,
                  -3.77114594,
                  -1.11903194,
                  -5.39151466,
                  3.06620093,
              ],
              [
                  9.86326886,
                  1.05134482,
                  -7.75950607,
                  -3.64429655,
                  7.81848957,
                  -9.02270373,
                  3.73399754,
                  -4.71962549,
                  -7.71144306,
                  3.78263161,
                  6.46034818,
                  -4.43444731,
              ],
          ]
      )
      assert_allclose(
          bsp.spline_filter(data_array_real, 0), result_array_real
      )
  
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 1 for calling the TestBSplines obj's underlying member method code with example usage: obj.test_spline_filter() without return types