parameters: (system, w=None, n=10000)
return_statement: return w, h
docstring: Calculate the frequency response of a continuous-time system.
  
      Parameters
      ----------
      system : an instance of the `lti` class or a tuple describing the system.
          The following gives the number of elements in the tuple and
          the interpretation:
  
              * 1 (instance of `lti`)
              * 2 (num, den)
              * 3 (zeros, poles, gain)
              * 4 (A, B, C, D)
  
      w : array_like, optional
          Array of frequencies (in rad/s). Magnitude and phase data is
          calculated for every value in this array. If not given, a reasonable
          set will be calculated.
      n : int, optional
          Number of frequency points to compute if `w` is not given. The `n`
          frequencies are logarithmically spaced in an interval chosen to
          include the influence of the poles and zeros of the system.
  
      Returns
      -------
      w : 1D ndarray
          Frequency array [rad/s]
      H : 1D ndarray
          Array of complex magnitude values
  
      Notes
      -----
      If (num, den) is passed in for ``system``, coefficients for both the
      numerator and denominator should be specified in descending exponent
      order (e.g. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).
  
      Examples
      --------
      Generating the Nyquist plot of a transfer function
  
      >>> from scipy import signal
      >>> import matplotlib.pyplot as plt
  
      Transfer function: H(s) = 5 / (s-1)^3
  
      >>> s1 = signal.ZerosPolesGain([], [1, 1, 1], [5])
  
      >>> w, H = signal.freqresp(s1)
  
      >>> plt.figure()
      >>> plt.plot(H.real, H.imag, "b")
      >>> plt.plot(H.real, -H.imag, "r")
      >>> plt.show()
docstring_summary: Calculate the frequency response of a continuous-time system.
docstring_tokens: Calculate the frequency response of a continuous - time system .
function: def freqresp(system, w=None, n=10000):
      """Calculate the frequency response of a continuous-time system.
  
      Parameters
      ----------
      system : an instance of the `lti` class or a tuple describing the system.
          The following gives the number of elements in the tuple and
          the interpretation:
  
              * 1 (instance of `lti`)
              * 2 (num, den)
              * 3 (zeros, poles, gain)
              * 4 (A, B, C, D)
  
      w : array_like, optional
          Array of frequencies (in rad/s). Magnitude and phase data is
          calculated for every value in this array. If not given, a reasonable
          set will be calculated.
      n : int, optional
          Number of frequency points to compute if `w` is not given. The `n`
          frequencies are logarithmically spaced in an interval chosen to
          include the influence of the poles and zeros of the system.
  
      Returns
      -------
      w : 1D ndarray
          Frequency array [rad/s]
      H : 1D ndarray
          Array of complex magnitude values
  
      Notes
      -----
      If (num, den) is passed in for ``system``, coefficients for both the
      numerator and denominator should be specified in descending exponent
      order (e.g. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).
  
      Examples
      --------
      Generating the Nyquist plot of a transfer function
  
      >>> from scipy import signal
      >>> import matplotlib.pyplot as plt
  
      Transfer function: H(s) = 5 / (s-1)^3
  
      >>> s1 = signal.ZerosPolesGain([], [1, 1, 1], [5])
  
      >>> w, H = signal.freqresp(s1)
  
      >>> plt.figure()
      >>> plt.plot(H.real, H.imag, "b")
      >>> plt.plot(H.real, -H.imag, "r")
      >>> plt.show()
      """
      if isinstance(system, lti):
          sys = system._as_tf()
      elif isinstance(system, dlti):
          raise AttributeError('freqresp can only be used with continuous-time '
                               'systems.')
      else:
          sys = lti(*system)._as_tf()
  
      if sys.inputs != 1 or sys.outputs != 1:
          raise ValueError("freqresp() requires a SISO (single input, single "
                           "output) system.")
  
      if w is not None:
          worN = w
      else:
          worN = n
  
      # In the call to freqs(), sys.num.ravel() is used because there are
      # cases where sys.num is a 2-D array with a single row.
      w, h = freqs(sys.num.ravel(), sys.den, worN=worN)
  
      return w, h
function_tokens: def freqresp ( system , w = None , n = 10000 ) : if isinstance ( system , lti ) : sys = system . _as_tf ( ) elif isinstance ( system , dlti ) : raise AttributeError ( 'freqresp can only be used with continuous-time ' 'systems.' ) else : sys = lti ( * system ) . _as_tf ( ) if sys . inputs != 1 or sys . outputs != 1 : raise ValueError ( "freqresp() requires a SISO (single input, single " "output) system." ) if w is not None : worN = w else : worN = n # In the call to freqs(), sys.num.ravel() is used because there are # cases where sys.num is a 2-D array with a single row. w , h = freqs ( sys . num . ravel ( ) , sys . den , worN = worN ) return w , h