Python numpy.kaiser() Examples

The following are 13 code examples for showing how to use numpy.kaiser(). These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.

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Example 1
Project: deep-learning-note   Author: wdxtub   File: util.py    License: MIT License 5 votes vote down vote up
def smooth_curve(x):
    """用于使损失函数的图形变圆滑
    参考:http://glowingpython.blogspot.jp/2012/02/convolution-with-numpy.html
    """
    window_len = 11
    s = np.r_[x[window_len-1:0:-1], x, x[-1:-window_len:-1]]
    w = np.kaiser(window_len, 2)
    y = np.convolve(w/w.sum(), s, mode='valid')
    return y[5:len(y)-5] 
Example 2
Project: deep-learning-from-scratch   Author: oreilly-japan   File: util.py    License: MIT License 5 votes vote down vote up
def smooth_curve(x):
    """損失関数のグラフを滑らかにするために用いる

    参考:http://glowingpython.blogspot.jp/2012/02/convolution-with-numpy.html
    """
    window_len = 11
    s = np.r_[x[window_len-1:0:-1], x, x[-1:-window_len:-1]]
    w = np.kaiser(window_len, 2)
    y = np.convolve(w/w.sum(), s, mode='valid')
    return y[5:len(y)-5] 
Example 3
Project: cupy   Author: cupy   File: window.py    License: MIT License 5 votes vote down vote up
def kaiser(M, beta):
    """Return the Kaiser window.
    The Kaiser window is a taper formed by using a Bessel function.

    .. math::  w(n) = I_0\\left( \\beta \\sqrt{1-\\frac{4n^2}{(M-1)^2}}
               \\right)/I_0(\\beta)

    with

    .. math:: \\quad -\\frac{M-1}{2} \\leq n \\leq \\frac{M-1}{2}

    where :math:`I_0` is the modified zeroth-order Bessel function.

     Args:
        M (int):
            Number of points in the output window. If zero or less, an empty
            array is returned.
        beta (float):
            Shape parameter for window

    Returns:
        ~cupy.ndarray:  The window, with the maximum value normalized to one
        (the value one appears only if the number of samples is odd).

    .. seealso:: :func:`numpy.kaiser`
    """
    if M == 1:
        return cupy.array([1.])
    if M <= 0:
        return cupy.array([])
    alpha = (M - 1) / 2.0
    out = cupy.empty(M, dtype=cupy.float64)
    return _kaiser_kernel(beta, alpha, out) 
Example 4
Project: spectrum   Author: cokelaer   File: window.py    License: BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def _kaiser(n, beta):
    """Independant Kaiser window

    For the definition of the Kaiser window, see A. V. Oppenheim & R. W. Schafer, "Discrete-Time Signal Processing".

    The continuous version of width n centered about x=0 is:

    .. note:: 2 times slower than scipy.kaiser
    """
    from scipy.special import iv as besselI
    m = n - 1
    k = arange(0, m)
    k = 2. * beta / m * sqrt (k * (m - k))
    w = besselI (0, k) / besselI (0, beta)
    return w 
Example 5
Project: spectrum   Author: cokelaer   File: window.py    License: BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def window_visu(N=51, name='hamming', **kargs):
    """A Window visualisation tool

    :param N: length of the window
    :param name: name of the window
    :param NFFT: padding used by the FFT
    :param mindB: the minimum frequency power in dB
    :param maxdB: the maximum frequency power in dB
    :param kargs: optional arguments passed to :func:`create_window`

    This function plot the window shape and its equivalent in the Fourier domain.

    .. plot::
        :width: 80%
        :include-source:

        from spectrum import window_visu
        window_visu(64, 'kaiser', beta=8.)

    """
    # get the default parameters
    mindB = kargs.pop('mindB', -100)
    maxdB = kargs.pop('maxdB', None)
    norm = kargs.pop('norm', True)

    # create a window object
    w = Window(N, name, **kargs)

    # plot the time and frequency windows
    w.plot_time_freq(mindB=mindB, maxdB=maxdB, norm=norm) 
Example 6
Project: sound_field_analysis-py   Author: AppliedAcousticsChalmers   File: process.py    License: MIT License 5 votes vote down vote up
def iFFT(Y, output_length=None, window=False):
    """ Inverse real-valued Fourier Transform

    Parameters
    ----------
    Y : array_like
       Frequency domain data [Nsignals x Nbins]
    output_length : int, optional
       Length of returned time-domain signal (Default: 2 x len(Y) + 1)
    window : boolean, optional
       Window applied to the resulting time-domain signal

    Returns
    -------
    y : array_like
       Reconstructed time-domain signal
    """
    Y = _np.atleast_2d(Y)
    y = _np.fft.irfft(Y, n=output_length)

    if window:
        no_of_samples = y.shape[-1]

        if window == 'hann':
            window_array = _np.hanning(no_of_samples)
        elif window == 'hamming':
            window_array = _np.hamming(no_of_samples)
        elif window == 'blackman':
            window_array = _np.blackman(no_of_samples)
        elif window == 'kaiser':
            window_array = _np.kaiser(no_of_samples, 3)
        else:
            raise ValueError('Selected window must be one of hann, hamming, blackman or kaiser')

        y *= window_array

    return y


# noinspection PyUnusedLocal 
Example 7
Project: deep-learning-from-scratch   Author: hguomin   File: util.py    License: MIT License 5 votes vote down vote up
def smooth_curve(x):
    """用于使损失函数的图形变圆滑

    参考:http://glowingpython.blogspot.jp/2012/02/convolution-with-numpy.html
    """
    window_len = 11
    s = np.r_[x[window_len-1:0:-1], x, x[-1:-window_len:-1]]
    w = np.kaiser(window_len, 2)
    y = np.convolve(w/w.sum(), s, mode='valid')
    return y[5:len(y)-5] 
Example 8
Project: pystoi   Author: mpariente   File: utils.py    License: MIT License 5 votes vote down vote up
def _resample_window_oct(p, q):
    """Port of Octave code to Python"""

    gcd = np.gcd(p, q)
    if gcd > 1:
        p /= gcd
        q /= gcd

    # Properties of the antialiasing filter
    log10_rejection = -3.0
    stopband_cutoff_f = 1. / (2 * max(p, q))
    roll_off_width = stopband_cutoff_f / 10

    # Determine filter length
    rejection_dB = -20 * log10_rejection
    L = np.ceil((rejection_dB - 8) / (28.714 * roll_off_width))

    # Ideal sinc filter
    t = np.arange(-L, L + 1)
    ideal_filter = 2 * p * stopband_cutoff_f \
        * np.sinc(2 * stopband_cutoff_f * t)

    # Determine parameter of Kaiser window
    if (rejection_dB >= 21) and (rejection_dB <= 50):
        beta = 0.5842 * (rejection_dB - 21)**0.4 \
            + 0.07886 * (rejection_dB - 21)
    elif rejection_dB > 50:
        beta = 0.1102 * (rejection_dB - 8.7)
    else:
        beta = 0.0

    # Apodize ideal filter response
    h = np.kaiser(2 * L + 1, beta) * ideal_filter

    return h 
Example 9
Project: R-CNN_LIGHT   Author: YeongHyeon   File: util.py    License: MIT License 5 votes vote down vote up
def smooth_curve(x):
    """ Used to smooth the graph of the loss function

    reference:http://glowingpython.blogspot.jp/2012/02/convolution-with-numpy.html
    """
    window_len = 11
    s = np.r_[x[window_len-1:0:-1], x, x[-1:-window_len:-1]]
    w = np.kaiser(window_len, 2)
    y = np.convolve(w/w.sum(), s, mode='valid')
    return y[5:len(y)-5] 
Example 10
Project: sfs-python   Author: sfstoolbox   File: tapering.py    License: MIT License 5 votes vote down vote up
def kaiser(active, *, beta):
    """Kaiser tapering window.

    This uses :func:`numpy.kaiser`.

    Parameters
    ----------
    active : array_like, dtype=bool
        A boolean array containing ``True`` for active loudspeakers.
    alpha : float
        Shape parameter of the Kaiser window, see :func:`numpy.kaiser`.

    Returns
    -------
    (len(active),) `numpy.ndarray`
        Tapering weights.

    Examples
    --------
    .. plot::
        :context: close-figs

        plt.plot(sfs.tapering.kaiser(active1, beta=0), label='beta = 0')
        plt.plot(sfs.tapering.kaiser(active1, beta=2), label='beta = 2')
        plt.plot(sfs.tapering.kaiser(active1, beta=6), label='beta = 6')
        plt.plot(sfs.tapering.kaiser(active1, beta=8.6), label='beta = 8.6')
        plt.plot(sfs.tapering.kaiser(active1, beta=14), label='beta = 14')
        plt.axis([-3, 103, -0.1, 1.1])
        plt.legend(loc='lower center')

    .. plot::
        :context: close-figs

        plt.plot(sfs.tapering.kaiser(active2, beta=7))
        plt.axis([-3, 103, -0.1, 1.1])

    """
    idx = _windowidx(active)
    window = _np.zeros(len(active))
    window[idx] = _np.kaiser(len(idx), beta)
    return window 
Example 11
Project: MLPrimitives   Author: HDI-Project   File: dsp.py    License: MIT License 5 votes vote down vote up
def window_design(self, window_length, beta):
        """Kaiser window design

        Args:
            window_length: Length of the window in number of samples
            beta: Beta value for Kaiser window design

        Returns:
            window: Window designed using the beta and length provided as inputs

        """

        self.window = np.kaiser(window_length, beta)

        return self.window 
Example 12
Project: spectrum   Author: cokelaer   File: window.py    License: BSD 3-Clause "New" or "Revised" License 4 votes vote down vote up
def enbw(data):
    r"""Computes the equivalent noise bandwidth

    .. math:: ENBW = N \frac{\sum_{n=1}^{N} w_n^2}{\left(\sum_{n=1}^{N} w_n \right)^2}

    .. doctest::

        >>> from spectrum import create_window, enbw
        >>> w = create_window(64, 'rectangular')
        >>> enbw(w)
        1.0

    The following table contains the ENBW values for some of the
    implemented windows in this module (with N=16384). They have been
    double checked against litterature (Source: [Harris]_, [Marple]_).

    If not present, it means that it has not been checked.

    =================== ============ =============
    name                 ENBW        litterature
    =================== ============ =============
    rectangular         1.           1.
    triangle            1.3334       1.33
    Hann                1.5001       1.5
    Hamming             1.3629       1.36
    blackman            1.7268       1.73
    kaiser              1.7
    blackmanharris,4    2.004        2.
    riesz               1.2000       1.2
    riemann             1.32         1.3
    parzen              1.917        1.92
    tukey 0.25          1.102        1.1
    bohman              1.7858       1.79
    poisson 2           1.3130       1.3
    hanningpoisson 0.5  1.609        1.61
    cauchy              1.489        1.48
    lanczos             1.3
    =================== ============ =============


    """
    N = len(data)
    return N * np.sum(data**2) / np.sum(data)**2 
Example 13
Project: sarpy   Author: ngageoint   File: Grid.py    License: MIT License 4 votes vote down vote up
def define_weight_function(self, weight_size=DEFAULT_WEIGHT_SIZE):
        """
        Try to derive WgtFunct from WgtType, if necessary. This should likely be called from the `GridType` parent.

        Parameters
        ----------
        weight_size : int
            the size of the `WgtFunct` to generate.

        Returns
        -------
        None
        """

        if self.WgtType is None or self.WgtType.WindowName is None:
            return  # nothing to be done

        window_name = self.WgtType.WindowName.upper()
        if window_name == 'HAMMING':
            # A Hamming window is defined in many places as a raised cosine of weight .54, so this is the default.
            # Some data use a generalized raised cosine and call it HAMMING, so we allow for both uses.
            try:
                # noinspection PyTypeChecker
                coef = float(self.WgtType.get_parameter_value(None, 0.54))  # just get first parameter - name?
            except ValueError:
                coef = 0.54
            self.WgtFunct = _raised_cos(weight_size, coef)
        elif window_name == 'HANNING':
            self.WgtFunct = _raised_cos(weight_size, 0.5)
        elif window_name == 'KAISER':
            try:
                # noinspection PyTypeChecker
                beta = float(self.WgtType.get_parameter_value(None, 14))  # just get first parameter - name?
            except ValueError:
                beta = 14.0  # default suggested in numpy.kaiser
            self.WgtFunct = numpy.kaiser(weight_size, beta)
        elif window_name == 'TAYLOR':
            # noinspection PyTypeChecker
            sidelobes = int(self.WgtType.get_parameter_value('NBAR', 4))  # apparently the matlab argument name
            # noinspection PyTypeChecker
            max_sidelobe_level = float(self.WgtType.get_parameter_value('SLL', -30))  # same
            if max_sidelobe_level > 0:
                max_sidelobe_level *= -1
            self.WgtFunct = _taylor_win(weight_size,
                                        sidelobes=sidelobes,
                                        max_sidelobe_level=max_sidelobe_level,
                                        normalize=True)