qiskit.visualization.pulse.interpolation

cubic_spline(time: numpy.ndarray, samples: numpy.ndarray, nop: int, *, kind: str = 'cubic') → Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]

Apply cubic interpolation between sampling points.

Parameters

• time – Time vector with length of samples + 1.
• samples – Complex pulse envelope.
• nop – Number of data points for interpolation.

Returns

Interpolated time vector and real and imaginary part of waveform.

interp1d(time, samples, nop, kind='linear')

Scipy interpolation wrapper.

Parameters

• time (ndarray) – Time vector with length of samples + 1.
• samples (ndarray) – Complex pulse envelope.
• nop (int) – Number of data points for interpolation.
• kind (str) – Scipy interpolation type. See scipy.interpolate.interp1d documentation for more information.

Return type

Tuple[ndarray, ndarray, ndarray]

Returns

Interpolated time vector and real and imaginary part of waveform.

linear(time: numpy.ndarray, samples: numpy.ndarray, nop: int, *, kind: str = 'linear') → Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]

Apply linear interpolation between sampling points.

Parameters

• time – Time vector with length of samples + 1.
• samples – Complex pulse envelope.
• nop – Number of data points for interpolation.

Returns

Interpolated time vector and real and imaginary part of waveform.

step_wise(time, samples, nop)

Keep uniform variation between sample values. No interpolation is applied. :type time: ndarray :param time: Time vector with length of samples + 1. :type samples: ndarray :param samples: Complex pulse envelope. :type nop: int :param nop: This argument is not used.

Return type

Tuple[ndarray, ndarray, ndarray]

Returns

Time vector and real and imaginary part of waveform.