add numpy op hanning

python/mxnet/ndarray/numpy/_op.py

@@ -25,7 +25,7 @@
 from ...context import current_context
 from . import _internal as _npi
 
-__all__ = ['zeros', 'ones', 'add', 'subtract', 'multiply', 'divide', 'mod', 'power']
+__all__ = ['zeros', 'ones', 'add', 'subtract', 'multiply', 'divide', 'mod', 'power', 'hanning']
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -293,3 +293,87 @@ def power(x1, x2, out=None):
         This is a scalar if both x1 and x2 are scalars.
     """
     return _ufunc_helper(x1, x2, _npi.power, _np.power, _npi.power_scalar, _npi.rpower_scalar, out)
+
+
+@set_module('mxnet.ndarray.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 _npi.hanning(M, dtype=dtype, ctx=ctx)

python/mxnet/numpy/multiarray.py

@@ -44,7 +44,7 @@
 from ..ndarray.numpy import _internal as _npi
 
 __all__ = ['ndarray', 'empty', 'array', 'zeros', 'ones', 'add', 'subtract', 'multiply', 'divide',
-           'mod', 'power']
+           'mod', 'power', 'hanning']
 
 
 # This function is copied from ndarray.py since pylint
@@ -1549,3 +1549,87 @@ def power(x1, x2, out=None):
         This is a scalar if both x1 and x2 are scalars.
     """
     return _mx_nd_np.power(x1, x2, out=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)

python/mxnet/symbol/numpy/_symbol.py

@@ -28,7 +28,7 @@
 from .._internal import _set_np_symbol_class
 from . import _internal as _npi
 
-__all__ = ['zeros', 'ones', 'add', 'subtract', 'multiply', 'divide', 'mod', 'power']
+__all__ = ['zeros', 'ones', 'add', 'subtract', 'multiply', 'divide', 'mod', 'power', 'hanning']
 
 
 def _num_outputs(sym):
@@ -1010,4 +1010,88 @@ def power(x1, x2, out=None):
     return _ufunc_helper(x1, x2, _npi.power, _np.power, _npi.power_scalar, _npi.rpower_scalar, 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}}{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 _npi.hanning(M, dtype=dtype, ctx=ctx)
+
+
 _set_np_symbol_class(_Symbol)

src/operator/numpy/np_window_op.cc

@@ -0,0 +1,45 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ *  Copyright (c) 2019 by Contributors
+ * \file np_window_op.cc
+ * \brief CPU Implementation of unary op hanning, hamming, blackman window.
+ */
+
+#include "np_window_op.h"
+
+namespace mxnet {
+namespace op {
+
+DMLC_REGISTER_PARAMETER(NumpyWindowsParam);
+
+NNVM_REGISTER_OP(_npi_hanning)
+.describe("Return the Hanning window."
+          "The Hanning window is a taper formed by using a weighted cosine.")
+.set_num_inputs(0)
+.set_num_outputs(1)
+.set_attr_parser(ParamParser<NumpyWindowsParam>)
+.set_attr<mxnet::FInferShape>("FInferShape", NumpyWindowsShape)
+.set_attr<nnvm::FInferType>("FInferType", InitType<NumpyWindowsParam>)
+.set_attr<FCompute>("FCompute<cpu>", NumpyWindowCompute<cpu, 0>)
+.add_arguments(NumpyWindowsParam::__FIELDS__());
+
+}  // namespace op
+}  // namespace mxnet

src/operator/numpy/np_window_op.cu

@@ -0,0 +1,35 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ *  Copyright (c) 2019 by Contributors
+ * \file np_window_op.cu
+ * \brief CPU Implementation of unary op hanning, hamming, blackman window.
+ */
+
+#include "np_window_op.h"
+
+namespace mxnet {
+namespace op {
+
+NNVM_REGISTER_OP(_npi_hanning)
+.set_attr<FCompute>("FCompute<gpu>", NumpyWindowCompute<gpu, 0>);
+
+}  // namespace op
+}  // namespace mxnet