code: def morlet2(M, s, w=5):
      """
      Complex Morlet wavelet, designed to work with `cwt`.
      Returns the complete version of morlet wavelet, normalised
      according to `s`::
          exp(1j*w*x/s) * exp(-0.5*(x/s)**2) * pi**(-0.25) * sqrt(1/s)
      Parameters
      ----------
      M : int
          Length of the wavelet.
      s : float
          Width parameter of the wavelet.
      w : float, optional
          Omega0. Default is 5
      Returns
      -------
      morlet : (M,) ndarray
      See Also
      --------
      morlet : Implementation of Morlet wavelet, incompatible with `cwt`
      Notes
      -----
      .. versionadded:: 1.4.0
      This function was designed to work with `cwt`. Because `morlet2`
      returns an array of complex numbers, the `dtype` argument of `cwt`
      should be set to `complex128` for best results.
      Note the difference in implementation with `morlet`.
      The fundamental frequency of this wavelet in Hz is given by::
          f = w*fs / (2*s*np.pi)
      where ``fs`` is the sampling rate and `s` is the wavelet width parameter.
      Similarly we can get the wavelet width parameter at ``f``::
          s = w*fs / (2*f*np.pi)
      Examples
      --------
      >>> from scipy import signal
      >>> import matplotlib.pyplot as plt
      >>> M = 100
      >>> s = 4.0
      >>> w = 2.0
      >>> wavelet = signal.morlet2(M, s, w)
      >>> plt.plot(abs(wavelet))
      >>> plt.show()
      This example shows basic use of `morlet2` with `cwt` in time-frequency
      analysis:
      >>> from scipy import signal
      >>> import matplotlib.pyplot as plt
      >>> t, dt = np.linspace(0, 1, 200, retstep=True)
      >>> fs = 1/dt
      >>> w = 6.
      >>> sig = np.cos(2*np.pi*(50 + 10*t)*t) + np.sin(40*np.pi*t)
      >>> freq = np.linspace(1, fs/2, 100)
      >>> widths = w*fs / (2*freq*np.pi)
      >>> cwtm = signal.cwt(sig, signal.morlet2, widths, w=w)
      >>> plt.pcolormesh(t, freq, np.abs(cwtm),
          cmap='viridis', shading='gouraud')
      >>> plt.show()
      """
  
      return _morlet2_kernel(w, s, size=M)
  
imports: import cupy
  import numpy
  from ..convolution.convolve import convolve
label_desc: Use image node_id 4 for calling a global function with example usage: morlet2(M, s, w) and returns: _morlet2_kernel