rf_det_act#

Measure RF amplitude and phase from ADC samples.

Functions

ap2iq_wf(A, P)

A/P to I/Q waveforms.

asyn_demod(raw_wf, ref_wf)

Asynchronous demodulation (need reference).

iq2ap_wf(I, Q)

I/Q to A/P waveforms.

noniq_demod(raw_wf, n[, m])

Non-I/Q demodulation.

norm_phase(P[, cmd])

normalize phase to +-180 degree or between 0 to 360 degree.

pulse_info(pulse[, threshold])

get information of a pulse.

self_demod_ap(raw_wf[, n])

Self demodulation with Hilbert transform (later may implement padding to mitigate the edge effects).

twop_demod(raw_wf, f_if, fs)

Demodulation with two points.
ap2iq_wf(A, P)[source]#

A/P to I/Q waveforms.

Parameters:

  • A – numpy array, amplitude/phase waveforms, P in degree

  • P – numpy array, amplitude/phase waveforms, P in degree

Returns:

I, Q – numpy array, I/Q waveforms

asyn_demod(raw_wf, ref_wf)[source]#

Asynchronous demodulation (need reference).

Parameters:

  • raw_wf – numpy array, signal waveform to be demodulated

  • ref_wf – numpy array, samples of the RF reference signal

Returns:

  • status – boolean, success (True) or faile (False)

  • I, Q – numpy array, I/Q waveforms of final demodulation

  • Isig, Qsig – numpy array, I/Q waveforms of raw_wf (with inaccurate phase)

  • Iref, Qsig – numpy array, I/Q waveforms of ref_wf (with inaccurate phase)

iq2ap_wf(I, Q)[source]#

I/Q to A/P waveforms.

Parameters:

  • I – numpy array, I/Q waveforms

  • Q – numpy array, I/Q waveforms

Returns:

A, P – numpy array, amplitude/phase waveforms, P in degree

noniq_demod(raw_wf, n, m=1)[source]#

Non-I/Q demodulation.

Refer to LLRF Book section 5.2.2.

Parameters:

  • raw_wf – numpy array, 1-D array of the raw waveform

  • m – integer, non-I/Q parameters (n samples cover m IF cycles)

  • n – integer, non-I/Q parameters (n samples cover m IF cycles)

Returns:

  • status – boolean, success (True) or faile (False)

  • I, Q – numpy array, I/Q waveforms

norm_phase(P, cmd='+-180')[source]#

normalize phase to +-180 degree or between 0 to 360 degree.

Parameters:

  • P – float, phase in degree

  • cmd – string ‘+-180’ or ‘0to360’

Returns:

Pnorm – float, normalized phase, degree

pulse_info(pulse, threshold=0.1)[source]#

get information of a pulse.

Parameters:

  • pulse – numpy array, the pulse data

  • threshold – float, threshold for edge detection

Returns:

  • offs – int, offset id of the pulse

  • pulw – int, pulse width as number of samples

  • peak – float, peak magnitude of the pulse

To be done:

  1. detect the rise time and falling time

  2. detect the flattop region and average

  3. calculate the energy in the pulse

self_demod_ap(raw_wf, n=1)[source]#

Self demodulation with Hilbert transform (later may implement padding to mitigate the edge effects).

Parameters:

  • raw_wf – numpy array, signal waveform to be demodulated

  • n – int, number of points covering full cycles (for coherent sampling)

Returns:

  • status – boolean, success (True) or faile (False)

  • A, P – numpy array, amplitude and phase waveforms, P in degree

twop_demod(raw_wf, f_if, fs)[source]#

Demodulation with two points.

Refer to LLRF Book section 5.2.2.

Parameters:

  • raw_wf – numpy array, raw waveform to be demodulated

  • f_if – float, IF frequency, Hz

  • fs – float, sampling frequency, Hz

Returns:

  • status – boolean, success (True) or faile (False)

  • I, Q – numpy array, I/Q waveforms