code: def test_correct_parameters_multi_channels(
      self, frequency, quality_factor, sampling_freq
  ):
      self.assertIsInstance(
          SignalRemoveFrequency(
              frequency, quality_factor, sampling_freq
          ),
          SignalRemoveFrequency,
      )
      sig = np.load(TEST_SIGNAL)
      t = sig.shape[1] / sampling_freq
      composite_sig = sig + np.sin(2 * np.pi * frequency * t)
      freqremove = SignalRemoveFrequency(
          frequency, quality_factor, sampling_freq
      )
      freqremovesignal = freqremove(composite_sig)
      y = np.fft.fft(composite_sig) / composite_sig.shape[1]
      y = y[: composite_sig.shape[1] // 2]
      y2 = np.fft.fft(freqremovesignal) / freqremovesignal.shape[1]
      y2 = y2[: freqremovesignal.shape[1] // 2]
      self.assertEqual(composite_sig.shape[1], sig.shape[1])
      self.assertAlmostEqual(y.all(), y2.all())
  
file_path: MONAI/tests/test_signal_remove_frequency.py
imports: from __future__ import annotations
  import os
  import unittest
  from unittest import skipUnless
  import numpy
  import torch
  from parameterized import parameterized
  from monai.transforms import SignalRemoveFrequency
  from monai.utils import optional_import
  from monai.utils.type_conversion import convert_to_tensor
label_desc: Use image node_id 1 for calling the TestSignalRemoveFrequencyNumpy obj's underlying member method code with example usage: obj.test_correct_parameters_multi_channels(frequency, quality_factor, sampling_freq) without return types