comaniac commented on a change in pull request #15815: Numpy add numpy op
hanning, hamming, blackman
URL: https://github.com/apache/incubator-mxnet/pull/15815#discussion_r323401201
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File path: python/mxnet/numpy/multiarray.py
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@@ -3588,3 +3589,275 @@ def argmax(a, axis=None, out=None):
array([2., 2.])
"""
return _mx_nd_np.argmax(a, axis, out)
+
+
+@set_module('mxnet.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 : ndarray, 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}}{M-1}\right)
+ \qquad 0 \leq n \leq M-1
+
+ 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. 106-108.
+ .. [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, 7.93732437e-02, 2.92292528e-01, 5.71157416e-01,
+ 8.27430424e-01, 9.79746513e-01, 9.79746489e-01, 8.27430268e-01,
+ 5.71157270e-01, 2.92292448e-01, 7.93731320e-02, 1.06192832e-13],
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 _mx_nd_np.hanning(M, dtype=dtype, ctx=ctx)
+
+
+@set_module('mxnet.numpy')
+def hamming(M, dtype=_np.float64, ctx=None):
Review comment:
The default dtype is float32.
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