comaniac commented on a change in pull request #15815: Numpy add numpy op hanning, hamming,
blackman
URL: https://github.com/apache/incubatormxnet/pull/15815#discussion_r323404633
##########
File path: python/mxnet/symbol/numpy/_symbol.py
##########
@@ 2508,4 +2508,277 @@ def argmax(a, axis=None, out=None):
return _npi.argmax(a, axis=axis, keepdims=False, out=out)
+@set_module('mxnet.symbol.numpy')
+def hanning(M, dtype=_np.float64, ctx=None):
+ r"""Return the Hanning window.
+
+ The Hanning window is a taper formed by using a weighted cosine.
+
+ Parameters
+ 
+ M : int
+ Number of points in the output window. If zero or less, an
+ empty array is returned.
+ dtype : str or numpy.dtype, optional
+ An optional value type. Default is `numpy.float64`. Note that you need
+ select numpy.float32 or float64 in this operator.
+ ctx : Context, optional
+ An optional device context (default is the current default context).
+
+ Returns
+ 
+ out : _Symbol, shape(M,)
+ The window, with the maximum value normalized to one (the value
+ one appears only if `M` is odd).
+
+ See Also
+ 
+ blackman, hamming
+
+ Notes
+ 
+ The Hanning window is defined as
+
+ .. math:: w(n) = 0.5  0.5cos\left(\frac{2\pi{n}}{M1}\right)
+ \qquad 0 \leq n \leq M1
+
+ The Hanning was named for Julius von Hann, an Austrian meteorologist.
+ It is also known as the Cosine Bell. Some authors prefer that it be
+ called a Hann window, to help avoid confusion with the very similar
+ Hamming window.
+
+ Most references to the Hanning window come from the signal processing
+ literature, where it is used as one of many windowing functions for
+ smoothing values. It is also known as an apodization (which means
+ "removing the foot", i.e. smoothing discontinuities at the beginning
+ and end of the sampled signal) or tapering function.
+
+ References
+ 
+ .. [1] Blackman, R.B. and Tukey, J.W., (1958) The measurement of power
+ spectra, Dover Publications, New York.
+ .. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics",
+ The University of Alberta Press, 1975, pp. 106108.
+ .. [3] Wikipedia, "Window function",
+ http://en.wikipedia.org/wiki/Window_function
+ .. [4] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
+ "Numerical Recipes", Cambridge University Press, 1986, page 425.
+
+ Examples
+ 
+ >>> np.hanning(12)
+ array([0.00000000e+00, 7.93732437e02, 2.92292528e01, 5.71157416e01,
+ 8.27430424e01, 9.79746513e01, 9.79746489e01, 8.27430268e01,
+ 5.71157270e01, 2.92292448e01, 7.93731320e02, 1.06192832e13], dtype=float64)
+
+ Plot the window and its frequency response:
+
+ >>> import matplotlib.pyplot as plt
+ >>> window = np.hanning(51)
+ >>> plt.plot(window.asnumpy())
+ [<matplotlib.lines.Line2D object at 0x...>]
+ >>> plt.title("Hann window")
+ Text(0.5, 1.0, 'Hann window')
+ >>> plt.ylabel("Amplitude")
+ Text(0, 0.5, 'Amplitude')
+ >>> plt.xlabel("Sample")
+ Text(0.5, 0, 'Sample')
+ >>> plt.show()
+ """
+ if dtype is None:
+ dtype = _np.float64
+ if ctx is None:
+ ctx = current_context()
+ return _npi.hanning(M, dtype=dtype, ctx=ctx)
+
+
+@set_module('mxnet.symbol.numpy')
+def hamming(M, dtype=_np.float64, ctx=None):
+ r"""Return the hamming window.
+
+
+ The hamming window is a taper formed by using a weighted cosine.
+
+ Parameters
+ 
+ M : int
+ Number of points in the output window. If zero or less, an
+ empty array is returned.
+ dtype : str or numpy.dtype, optional
+ An optional value type. Default is `numpy.float64`. Note that you need
+ select numpy.float32 or float64 in this operator.
+ ctx : Context, optional
+ An optional device context (default is the current default context).
+
+ Returns
+ 
+ out : _Symbol, shape(M,)
+ The window, with the maximum value normalized to one (the value
+ one appears only if `M` is odd).
+
+ See Also
+ 
+ blackman, hanning
+
+ Notes
+ 
+ The Hamming window is defined as
+
+ .. math:: w(n) = 0.54  0.46cos\left(\frac{2\pi{n}}{M1}\right)
+ \qquad 0 \leq n \leq M1
+
+ The Hamming was named for R. W. Hamming, an associate of J. W. Tukey
+ and is described in Blackman and Tukey. It was recommended for
+ smoothing the truncated autocovariance function in the time domain.
+ Most references to the Hamming window come from the signal processing
+ literature, where it is used as one of many windowing functions for
+ smoothing values. It is also known as an apodization (which means
+ "removing the foot", i.e. smoothing discontinuities at the beginning
+ and end of the sampled signal) or tapering function.
+
+ References
+ 
+ .. [1] Blackman, R.B. and Tukey, J.W., (1958) The measurement of power
+ spectra, Dover Publications, New York.
+ .. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics", The
+ University of Alberta Press, 1975, pp. 109110.
+ .. [3] Wikipedia, "Window function",
+ https://en.wikipedia.org/wiki/Window_function
+ .. [4] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
+ "Numerical Recipes", Cambridge University Press, 1986, page 425.
+
+ Examples
+ 
+ >>> np.hamming(12)
+ array([0.08 , 0.15302338, 0.34890913, 0.60546482, 0.84123599,
+ 0.98136679, 0.98136677, 0.84123585, 0.60546469, 0.34890905,
+ 0.15302328, 0.08 ], dtype=float64)
+
+ Plot the window and its frequency response:
+
+ >>> import matplotlib.pyplot as plt
+ >>> window = np.hamming(51)
+ >>> plt.plot(window.asnumpy())
+ [<matplotlib.lines.Line2D object at 0x...>]
+ >>> plt.title("hamming window")
+ Text(0.5, 1.0, 'hamming window')
+ >>> plt.ylabel("Amplitude")
+ Text(0, 0.5, 'Amplitude')
+ >>> plt.xlabel("Sample")
+ Text(0.5, 0, 'Sample')
+ >>> plt.show()
+ """
+ if dtype is None:
+ dtype = _np.float64
+ if ctx is None:
+ ctx = current_context()
+ return _npi.hamming(M, dtype=dtype, ctx=ctx)
+
+
+@set_module('mxnet.symbol.numpy')
+def blackman(M, dtype=_np.float64, ctx=None):
+ r"""Return the Blackman window.
+
+ The Blackman window is a taper formed by using the first three
+ terms of a summation of cosines. It was designed to have close to the
+ minimal leakage possible. It is close to optimal, only slightly worse
+ than a Kaiser window.
+
+ Parameters
+ 
+ M : int
+ Number of points in the output window. If zero or less, an
+ empty array is returned.
+ dtype : str or numpy.dtype, optional
+ An optional value type. Default is `numpy.float64`. Note that you need
+ select numpy.float32 or float64 in this operator.
+ ctx : Context, optional
+ An optional device context (default is the current default context).
+
+ Returns
+ 
+ out : _Symbol
+ The window, with the maximum value normalized to one (the value one
+ appears only if the number of samples is odd).
+
+ See Also
+ 
+ hamming, hanning
+
+ Notes
+ 
+ The Blackman window is defined as
+
+ .. math:: w(n) = 0.42  0.5 \cos(2\pi n/{M1}) + 0.08 \cos(4\pi n/{M1})
+
+ Most references to the Blackman window come from the signal processing
+ literature, where it is used as one of many windowing functions for
+ smoothing values. It is also known as an apodization (which means
+ "removing the foot", i.e. smoothing discontinuities at the beginning
+ and end of the sampled signal) or tapering function. It is known as a
+ "near optimal" tapering function, almost as good (by some measures)
+ as the kaiser window.
+
+ References
+ 
+ Blackman, R.B. and Tukey, J.W., (1958) The measurement of power spectra,
+ Dover Publications, New York.
+
+ Oppenheim, A.V., and R.W. Schafer. DiscreteTime Signal Processing.
+ Upper Saddle River, NJ: PrenticeHall, 1999, pp. 468471.
+
+ See Also
+ 
+ hamming, hanning
+
+ Notes
+ 
+ The Blackman window is defined as
+
+ .. math:: w(n) = 0.42  0.5 \cos(2\pi n/{M1}) + 0.08 \cos(4\pi n/{M1})
+
+ Most references to the Blackman window come from the signal processing
+ literature, where it is used as one of many windowing functions for
+ smoothing values. It is also known as an apodization (which means
+ "removing the foot", i.e. smoothing discontinuities at the beginning
+ and end of the sampled signal) or tapering function. It is known as a
+ "near optimal" tapering function, almost as good (by some measures)
+ as the kaiser window.
+
+ References
+ 
+ Blackman, R.B. and Tukey, J.W., (1958) The measurement of power spectra,
+ Dover Publications, New York.
+
+ Oppenheim, A.V., and R.W. Schafer. DiscreteTime Signal Processing.
+ Upper Saddle River, NJ: PrenticeHall, 1999, pp. 468471.
+
+ Examples
+ 
+ >>> np.blackman(12)
+ array([1.38777878e17, 3.26064393e02, 1.59903660e01, 4.14397978e01,
+ 7.36045260e01, 9.67046812e01, 9.67046772e01, 7.36045039e01,
+ 4.14397819e01, 1.59903601e01, 3.26063877e02, 3.82194276e14], dtype=float64)
+
+ Plot the window and its frequency response:
+
+ >>> import matplotlib.pyplot as plt
+ >>> window = np.blackman(51)
+ >>> plt.plot(window.asnumpy())
+ [<matplotlib.lines.Line2D object at 0x...>]
+ >>> plt.title("blackman window")
+ Text(0.5, 1.0, 'blackman window')
+ >>> plt.ylabel("Amplitude")
+ Text(0, 0.5, 'Amplitude')
+ >>> plt.xlabel("Sample")
+ Text(0.5, 0, 'Sample')
+ >>> plt.show()
+ """
+ if dtype is None:
Review comment:
Remove this logic since dtype must not be None because you have assigned the default value.

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