qiskit/visualization/pulse_visualization.py
def pulse_drawer(samples, duration, dt=None, interp_method='None',
                 filename=None, interactive=False,
                 dpi=150, nop=1000, size=(6, 5)):
    """Plot the interpolated envelope of pulse

    Args:
        samples (ndarray): Data points of complex pulse envelope.
        duration (int): Pulse length (number of points).
        dt (float): Time interval of samples.
        interp_method (str): Method of interpolation
            (set `None` for turn off the interpolation).
        filename (str): Name required to save pulse image.
        interactive (bool): When set true show the circuit in a new window
            (this depends on the matplotlib backend being used supporting this).
        dpi (int): Resolution of saved image.
        nop (int): Data points for interpolation.
        size (tuple): Size of figure.
    Returns:
        matplotlib.figure: A matplotlib figure object for the pulse envelope.
    Raises:
        ImportError: when the output methods requieres non-installed libraries.
        QiskitError: when invalid interpolation method is specified.
    """

    try:
        from matplotlib import pyplot as plt
    except ImportError:
        raise ImportError('pulse_drawer need matplotlib. '
                          'Run "pip install matplotlib" before.')

    if dt:
        _dt = dt
    else:
        _dt = 1

    re_y = np.real(samples)
    im_y = np.imag(samples)

    image = plt.figure(figsize=size)
    ax0 = image.add_subplot(111)

    if interp_method == 'CubicSpline':
        # spline interpolation, use mid-point of dt
        time = np.arange(0, duration + 1) * _dt + 0.5 * _dt
        cs_ry = CubicSpline(time[:-1], re_y)
        cs_iy = CubicSpline(time[:-1], im_y)

        _time = np.linspace(0, duration * _dt, nop)
        _re_y = cs_ry(_time)
        _im_y = cs_iy(_time)
    elif interp_method == 'None':
        # pseudo-DAC output
        time = np.arange(0, duration + 1) * _dt

        _time = np.r_[time[0], np.repeat(time[1:-1], 2), time[-1]]
        _re_y = np.repeat(re_y, 2)
        _im_y = np.repeat(im_y, 2)
    else:
        raise QiskitError('Invalid interpolation method "%s"' % interp_method)

    # plot
    ax0.fill_between(x=_time, y1=_re_y, y2=np.zeros_like(_time),
                     facecolor='red', alpha=0.3,
                     edgecolor='red', linewidth=1.5,
                     label='real part')
    ax0.fill_between(x=_time, y1=_im_y, y2=np.zeros_like(_time),
                     facecolor='blue', alpha=0.3,
                     edgecolor='blue', linewidth=1.5,
                     label='imaginary part')

    ax0.set_xlim(0, duration * _dt)
    ax0.grid(b=True, linestyle='-')
    ax0.legend(bbox_to_anchor=(0.5, 1.00), loc='lower center',
               ncol=2, frameon=False, fontsize=14)

    if filename:
        image.savefig(filename, dpi=dpi, bbox_inches='tight')

    plt.close(image)

    if image and interactive:
        plt.show(image)

    return image
def pulse_drawer(samples, duration, dt=None, interp_method='None',
                 filename=None, interactive=False,
                 dpi=150, nop=1000, size=(6, 5)):
    try:
        from matplotlib import pyplot as plt
    except ImportError:
        raise ImportError('pulse_drawer need matplotlib. '
                          'Run "pip install matplotlib" before.')

    if dt:
        _dt = dt
    else:
        _dt = 1

    re_y = np.real(samples)
    im_y = np.imag(samples)

    image = plt.figure(figsize=size)
    ax0 = image.add_subplot(111)

    if interp_method == 'CubicSpline':
        # spline interpolation, use mid-point of dt
        time = np.arange(0, duration + 1) * _dt + 0.5 * _dt
        cs_ry = CubicSpline(time[:-1], re_y)
        cs_iy = CubicSpline(time[:-1], im_y)

        _time = np.linspace(0, duration * _dt, nop)
        _re_y = cs_ry(_time)
        _im_y = cs_iy(_time)
    elif interp_method == 'None':
        # pseudo-DAC output
        time = np.arange(0, duration + 1) * _dt

        _time = np.r_[time[0], np.repeat(time[1:-1], 2), time[-1]]
        _re_y = np.repeat(re_y, 2)
        _im_y = np.repeat(im_y, 2)
    else:
        raise QiskitError('Invalid interpolation method "%s"' % interp_method)

    # plot
    ax0.fill_between(x=_time, y1=_re_y, y2=np.zeros_like(_time),
                     facecolor='red', alpha=0.3,
                     edgecolor='red', linewidth=1.5,
                     label='real part')
    ax0.fill_between(x=_time, y1=_im_y, y2=np.zeros_like(_time),
                     facecolor='blue', alpha=0.3,
                     edgecolor='blue', linewidth=1.5,
                     label='imaginary part')

    ax0.set_xlim(0, duration * _dt)
    ax0.grid(b=True, linestyle='-')
    ax0.legend(bbox_to_anchor=(0.5, 1.00), loc='lower center',
               ncol=2, frameon=False, fontsize=14)

    if filename:
        image.savefig(filename, dpi=dpi, bbox_inches='tight')

    plt.close(image)

    if image and interactive:
        plt.show(image)

    return image
def pulse_drawer ( samples , duration , dt = None , interp_method = 'None' , filename = None , interactive = False , dpi = 150 , nop = 1000 , size = ( 6 , 5 ) ) : try : from matplotlib import pyplot as plt except ImportError : raise ImportError ( 'pulse_drawer need matplotlib. ' 'Run "pip install matplotlib" before.' ) if dt : _dt = dt else : _dt = 1 re_y = np . real ( samples ) im_y = np . imag ( samples ) image = plt . figure ( figsize = size ) ax0 = image . add_subplot ( 111 ) if interp_method == 'CubicSpline' : # spline interpolation, use mid-point of dt time = np . arange ( 0 , duration + 1 ) * _dt + 0.5 * _dt cs_ry = CubicSpline ( time [ : - 1 ] , re_y ) cs_iy = CubicSpline ( time [ : - 1 ] , im_y ) _time = np . linspace ( 0 , duration * _dt , nop ) _re_y = cs_ry ( _time ) _im_y = cs_iy ( _time ) elif interp_method == 'None' : # pseudo-DAC output time = np . arange ( 0 , duration + 1 ) * _dt _time = np . r_ [ time [ 0 ] , np . repeat ( time [ 1 : - 1 ] , 2 ) , time [ - 1 ] ] _re_y = np . repeat ( re_y , 2 ) _im_y = np . repeat ( im_y , 2 ) else : raise QiskitError ( 'Invalid interpolation method "%s"' % interp_method ) # plot ax0 . fill_between ( x = _time , y1 = _re_y , y2 = np . zeros_like ( _time ) , facecolor = 'red' , alpha = 0.3 , edgecolor = 'red' , linewidth = 1.5 , label = 'real part' ) ax0 . fill_between ( x = _time , y1 = _im_y , y2 = np . zeros_like ( _time ) , facecolor = 'blue' , alpha = 0.3 , edgecolor = 'blue' , linewidth = 1.5 , label = 'imaginary part' ) ax0 . set_xlim ( 0 , duration * _dt ) ax0 . grid ( b = True , linestyle = '-' ) ax0 . legend ( bbox_to_anchor = ( 0.5 , 1.00 ) , loc = 'lower center' , ncol = 2 , frameon = False , fontsize = 14 ) if filename : image . savefig ( filename , dpi = dpi , bbox_inches = 'tight' ) plt . close ( image ) if image and interactive : plt . show ( image ) return image
Plot the interpolated envelope of pulse

    Args:
        samples (ndarray): Data points of complex pulse envelope.
        duration (int): Pulse length (number of points).
        dt (float): Time interval of samples.
        interp_method (str): Method of interpolation
            (set `None` for turn off the interpolation).
        filename (str): Name required to save pulse image.
        interactive (bool): When set true show the circuit in a new window
            (this depends on the matplotlib backend being used supporting this).
        dpi (int): Resolution of saved image.
        nop (int): Data points for interpolation.
        size (tuple): Size of figure.
    Returns:
        matplotlib.figure: A matplotlib figure object for the pulse envelope.
    Raises:
        ImportError: when the output methods requieres non-installed libraries.
        QiskitError: when invalid interpolation method is specified.
Plot the interpolated envelope of pulse