interpolation¶
interpolation module for pulse visualization.
Functions
|
Scipy interpolation wrapper. |
|
Keep uniform variation between sample values. |
- 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')[source]¶
Scipy interpolation wrapper.
- Parameters
time (
ndarray
) – Time vector with length ofsamples
+ 1.samples (
ndarray
) – Complex pulse envelope.nop (
int
) – Number of data points for interpolation.kind (
str
) – Scipy interpolation type. Seescipy.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)[source]¶
Keep uniform variation between sample values. No interpolation is applied. :type time:
ndarray
:param time: Time vector with length ofsamples
+ 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.