FourierSpectrumUneven (FPScript)
Computes the windowed Fourier spectrum for unevenly sampled data.
Syntax
FourierSpectrumUneven(Signal, [ SpectrumType = SPECTRUM_DBNORM ], [ Window = WIN_HANNING ], [ Adjustment ], [ FrequencyCount = 1024 ], [ NyquistMultiple = 2.0 ] [ , Peaks ])
The syntax of the FourierSpectrumUneven function consists of the following parts:
Part |
Description |
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Signal |
The unevenly sampled data to be analyzed. The data set may also contain void values which are then removed before the spectrum is computed. Permitted data structures are data series, data matrix, signal und signal series. All real data types are permitted. If the argument is a list, then the function is executed for each element of the list and the result is also a list. |
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SpectrumType |
The spectral format to be computed. The argument SpectrumType can have the following values:
Permitted data structures are scalar value. All integral data types are permitted. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. If this argument is omitted, it will be set to the default value SPECTRUM_DBNORM. |
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Window |
The fixed or adjustable data window to be applied to the data. The argument Window can have the following values:
Permitted data structures are scalar value. All integral data types are permitted. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. If this argument is omitted, it will be set to the default value WIN_HANNING. |
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Adjustment |
The one-sided Fourier width as a multiple of the frequency interval. The valid range is window specific within 1.0 to 6.0. The default is 1.5 for a tapered cosine window and 3.0 for all other adjustable data windows. Permitted data structures are scalar value. All real data types are permitted. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. |
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FrequencyCount |
The length of the spectrum to be computed. Permitted data structures are scalar value. All integral data types are permitted. The value must be greater or equal to 32 and less or equal to 65536. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. If this argument is omitted, it will be set to the default value 1024. |
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NyquistMultiple |
The multiple of the average Nyquist frequency to be represented in the spectrum. Permitted data structures are scalar value. All real data types are permitted. The value must be greater or equal to 0.25 and less or equal to 4.0. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. If this argument is omitted, it will be set to the default value 2.0. |
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Peaks |
If specified, only bin-interpolated peaks in the spectrum are output. The peaks can be specified as a number of peaks or determined using a dB threshold. Specify a number as a positive number from 1 to 100 without a unit. You can specify a dB threshold as a quantity with the unit dB between 0.01 dB and 300 dB, or as a negative number between -0.01 and -300 without a unit. This argument is permitted for one-dimensional data sets only. Permitted data structures are scalar value. All real data types are permitted. If the argument is a list, then the first element in the list is taken. If this is also a list, then the process is repeated. |
Remarks
The data structure of the result is signal or signal series. If the argument Signal is a data series or data matrix, then the X component of the result contains Nyquist-normalized frequencies.
Available in
Option Spectral Analysis
Examples
FourierSpectrumUneven(Signal, SPECTRUM_DBNORM, WIN_RECTANGULAR, 1, 4096, 4)
Calculates the Fourier spectrum for the uneven signal 'Signal'. Normalized dB is used as the spectrum type, and rectangular -13 dB W=1 is selected as the window type. The number of frequencies is 4096, the multiple of the average Nyquist frequency is 4. This is an example from the Fourier Spectral Analysis Tutorial.
See Also
Uneven Data Fourier Spectral Analysis Object