parameters: (w0, Q)
return_statement: return _design_notch_peak_filter(w0, Q, "notch")
docstring: Design second-order IIR notch digital filter.
  
      A notch filter is a band-stop filter with a narrow bandwidth
      (high quality factor). It rejects a narrow frequency band and
      leaves the rest of the spectrum little changed.
  
      Parameters
      ----------
      w0 : float
          Normalized frequency to remove from a signal. It is a
          scalar that must satisfy  ``0 < w0 < 1``, with ``w0 = 1``
          corresponding to half of the sampling frequency.
      Q : float
          Quality factor. Dimensionless parameter that characterizes
          notch filter -3 dB bandwidth ``bw`` relative to its center
          frequency, ``Q = w0/bw``.
  
      Returns
      -------
      b, a : ndarray, ndarray
          Numerator (``b``) and denominator (``a``) polynomials
          of the IIR filter.
  
      See Also
      --------
      iirpeak
  
      Notes
      -----
      .. versionadded: 0.19.0
  
      References
      ----------
      .. [1] Sophocles J. Orfanidis, "Introduction To Signal Processing",
             Prentice-Hall, 1996
  
      Examples
      --------
      Design and plot filter to remove the 60Hz component from a
      signal sampled at 200Hz, using a quality factor Q = 30
  
      >>> from scipy import signal
      >>> import numpy as np
      >>> import matplotlib.pyplot as plt
  
      >>> fs = 200.0  # Sample frequency (Hz)
      >>> f0 = 60.0  # Frequency to be removed from signal (Hz)
      >>> Q = 30.0  # Quality factor
      >>> w0 = f0/(fs/2)  # Normalized Frequency
      >>> # Design notch filter
      >>> b, a = signal.iirnotch(w0, Q)
  
      >>> # Frequency response
      >>> w, h = signal.freqz(b, a)
      >>> # Generate frequency axis
      >>> freq = w*fs/(2*np.pi)
      >>> # Plot
      >>> fig, ax = plt.subplots(2, 1, figsize=(8, 6))
      >>> ax[0].plot(freq, 20*np.log10(abs(h)), color='blue')
      >>> ax[0].set_title("Frequency Response")
      >>> ax[0].set_ylabel("Amplitude (dB)", color='blue')
      >>> ax[0].set_xlim([0, 100])
      >>> ax[0].set_ylim([-25, 10])
      >>> ax[0].grid()
      >>> ax[1].plot(freq, np.unwrap(np.angle(h))*180/np.pi, color='green')
      >>> ax[1].set_ylabel("Angle (degrees)", color='green')
      >>> ax[1].set_xlabel("Frequency (Hz)")
      >>> ax[1].set_xlim([0, 100])
      >>> ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90])
      >>> ax[1].set_ylim([-90, 90])
      >>> ax[1].grid()
      >>> plt.show()
docstring_summary: Design second-order IIR notch digital filter.
docstring_tokens: Design second - order IIR notch digital filter .
function: def iirnotch(w0, Q):
      """
      Design second-order IIR notch digital filter.
  
      A notch filter is a band-stop filter with a narrow bandwidth
      (high quality factor). It rejects a narrow frequency band and
      leaves the rest of the spectrum little changed.
  
      Parameters
      ----------
      w0 : float
          Normalized frequency to remove from a signal. It is a
          scalar that must satisfy  ``0 < w0 < 1``, with ``w0 = 1``
          corresponding to half of the sampling frequency.
      Q : float
          Quality factor. Dimensionless parameter that characterizes
          notch filter -3 dB bandwidth ``bw`` relative to its center
          frequency, ``Q = w0/bw``.
  
      Returns
      -------
      b, a : ndarray, ndarray
          Numerator (``b``) and denominator (``a``) polynomials
          of the IIR filter.
  
      See Also
      --------
      iirpeak
  
      Notes
      -----
      .. versionadded: 0.19.0
  
      References
      ----------
      .. [1] Sophocles J. Orfanidis, "Introduction To Signal Processing",
             Prentice-Hall, 1996
  
      Examples
      --------
      Design and plot filter to remove the 60Hz component from a
      signal sampled at 200Hz, using a quality factor Q = 30
  
      >>> from scipy import signal
      >>> import numpy as np
      >>> import matplotlib.pyplot as plt
  
      >>> fs = 200.0  # Sample frequency (Hz)
      >>> f0 = 60.0  # Frequency to be removed from signal (Hz)
      >>> Q = 30.0  # Quality factor
      >>> w0 = f0/(fs/2)  # Normalized Frequency
      >>> # Design notch filter
      >>> b, a = signal.iirnotch(w0, Q)
  
      >>> # Frequency response
      >>> w, h = signal.freqz(b, a)
      >>> # Generate frequency axis
      >>> freq = w*fs/(2*np.pi)
      >>> # Plot
      >>> fig, ax = plt.subplots(2, 1, figsize=(8, 6))
      >>> ax[0].plot(freq, 20*np.log10(abs(h)), color='blue')
      >>> ax[0].set_title("Frequency Response")
      >>> ax[0].set_ylabel("Amplitude (dB)", color='blue')
      >>> ax[0].set_xlim([0, 100])
      >>> ax[0].set_ylim([-25, 10])
      >>> ax[0].grid()
      >>> ax[1].plot(freq, np.unwrap(np.angle(h))*180/np.pi, color='green')
      >>> ax[1].set_ylabel("Angle (degrees)", color='green')
      >>> ax[1].set_xlabel("Frequency (Hz)")
      >>> ax[1].set_xlim([0, 100])
      >>> ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90])
      >>> ax[1].set_ylim([-90, 90])
      >>> ax[1].grid()
      >>> plt.show()
      """
  
      return _design_notch_peak_filter(w0, Q, "notch")
function_tokens: def iirnotch ( w0 , Q ) : return _design_notch_peak_filter ( w0 , Q , "notch" )