TypePy

SCPI Command :

CALCulate:MATH<*>:FFT:WINDow:TYPE
Commands in total: 1
Subgroups: 0
Direct child commands: 1
get(math=Math.Default) → FftWindowType[source]
# CALCulate:MATH<*>:FFT:WINDow:TYPE
value: enums.FftWindowType = driver.calculate.math.fft.window.typePy.get(math = repcap.Math.Default)

Windowing helps minimize the discontinuities at the end of the measured signal interval and thus reduces the effect of spectral leakage, increasing the frequency resolution. Various different window functions are provided in the R&S RTP to suit different input signals. Each of the window functions has specific characteristics, including some advantages and some trade-offs. These characteristics need to be considered carefully to find the optimum solution for the measurement task.

Parameters:

math – optional repeated capability selector. Default value: Nr1 (settable in the interface ‘Math’)

Returns:

window_type: RECTangular | HAMMing | HANN | BLACkharris | GAUSsian | FLATTOP2 | FLATtop2 | KAISerbessel

  • RECTangular: The rectangular window has the best frequency resolution, but a poor amplitude accuracy and is recommended for separating two tones with almost equal amplitudes and a small frequency distance.

  • HAMMing: The Hamming window is bell shaped and has a good frequency resolution and fair amplitude accuracy. It is recommended for frequency response measurements as well as sine waves, periodic signals and narrow-band noise

  • HANN: The Hann window is bell shaped and has a slightly worse frequency resolution but smaller sidelobe level than the Hamming window. The applications are the same.

  • BLACkharris: The Blackman window is bell shaped and has a poor frequency resolution, but very good amplitude accuracy. It is recommended mainly for signals with single frequencies to detect harmonics.

  • GAUSsian: Good frequiency resolution and best magnitude resolution, recommended for weak signals and short duration

  • FLATTOP2 = FLATtop2: The flattop window has a poor frequency resolution, but the best amplitude accuracy and the sharpest side lobe. It is recommended for accurate single-tone amplitude measurements.

  • KAISerbessel: The Kaiser-Bessel window has a fair frequency resolution and good amplitude accuracy, and a very high sidelobe level. It is recommended for separating two tones with differing amplitudes and a small frequency distance.

set(window_type: FftWindowType, math=Math.Default) → None[source]
# CALCulate:MATH<*>:FFT:WINDow:TYPE
driver.calculate.math.fft.window.typePy.set(window_type = enums.FftWindowType.BLACkharris, math = repcap.Math.Default)

Windowing helps minimize the discontinuities at the end of the measured signal interval and thus reduces the effect of spectral leakage, increasing the frequency resolution. Various different window functions are provided in the R&S RTP to suit different input signals. Each of the window functions has specific characteristics, including some advantages and some trade-offs. These characteristics need to be considered carefully to find the optimum solution for the measurement task.

Parameters:

  • window_type –

    RECTangular | HAMMing | HANN | BLACkharris | GAUSsian | FLATTOP2 | FLATtop2 | KAISerbessel

    • RECTangular: The rectangular window has the best frequency resolution, but a poor amplitude accuracy and is recommended for separating two tones with almost equal amplitudes and a small frequency distance.

    • HAMMing: The Hamming window is bell shaped and has a good frequency resolution and fair amplitude accuracy. It is recommended for frequency response measurements as well as sine waves, periodic signals and narrow-band noise

    • HANN: The Hann window is bell shaped and has a slightly worse frequency resolution but smaller sidelobe level than the Hamming window. The applications are the same.

    • BLACkharris: The Blackman window is bell shaped and has a poor frequency resolution, but very good amplitude accuracy. It is recommended mainly for signals with single frequencies to detect harmonics.

    • GAUSsian: Good frequiency resolution and best magnitude resolution, recommended for weak signals and short duration

    • FLATTOP2 = FLATtop2: The flattop window has a poor frequency resolution, but the best amplitude accuracy and the sharpest side lobe. It is recommended for accurate single-tone amplitude measurements.

    • KAISerbessel: The Kaiser-Bessel window has a fair frequency resolution and good amplitude accuracy, and a very high sidelobe level. It is recommended for separating two tones with differing amplitudes and a small frequency distance.

  • math – optional repeated capability selector. Default value: Nr1 (settable in the interface ‘Math’)