Commit 6afc4d69 authored by thomas.forbriger's avatar thomas.forbriger
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foutra [TASK]: properly indent list

parent 26f97671
......@@ -2,55 +2,55 @@
# ============================================================================
# foutra: definition of command line options and parameters
# ---------------------------------------------------------
outfile output filename
infile input filename
t:T select traces T, where T may be any range
specification like '3-4' or '5,6,7-12,20'
outfile output filename
infile input filename
t:T select traces T, where T may be any range
specification like '3-4' or '5,6,7-12,20'
-help prints this help text
-xhelp print information concerning supported data formats
-help prints this help text
-xhelp print information concerning supported data formats
-v be verbose
-D debug mode
-o overwrite output
-boxcar apply boxcar taper (i.e. no taper; default is Hanning)
-amplitude calculate amplitude spectrum
-power calculate power spectrum
-type type select input file type
-Type type select output file type
-avg[=n] smooth power spectrum by averaging over n samples
-rbw[=n] smooth power spectrum by averaging over n decades
-demean[=n] remove average (determined from n samples)
-detrend[=n] remove trend (determined from n samples)
-v be verbose
-D debug mode
-o overwrite output
-boxcar apply boxcar taper (i.e. no taper; default is Hanning)
-amplitude calculate amplitude spectrum
-power calculate power spectrum
-type type select input file type
-Type type select output file type
-avg[=n] smooth power spectrum by averaging over n samples
-rbw[=n] smooth power spectrum by averaging over n decades
-demean[=n] remove average (determined from n samples)
-detrend[=n] remove trend (determined from n samples)
-derivative[=n] take n-th derivative of time series
-scalerbw[=n] scale to mean value in n decades
-divisor[=n] FFT becomes very inefficient if the factorization
of the number of samples includes large prime numbers.
This option removes the least number of samples to
the total number of samples a multiple of "n"
-ASCII[=base] write result to two-column ASCII files with basename 'base'
-logascii[=n] write ASCII data on logarithmic frequency axis with
one value per 'n' decades
-avgascii only average values for output to ASCII file
this option speeds up calculation together with
-scalerbw which increases computation time
with the square of frequency
-rms report rms values of input data
-harmonic scale output appropriate fro harmonic signals
useful for two-tone-tests of linearity (see below)
-pad n pad time series with zeroes; n gives the integer factor
for the number of samples; the raw amplitude spectrum
has to be understood as the spectrum of the whole
series including the padded zeroes; PSD and harmonic
signals are scaled to represent the taper time window
only, such that padding is a means of smoothing only
-nsegments n subdivide input time series in "n" overlapping
sequences (overlap is 50%); spectral analysis is
done for each sequence individually; the result
is the mean of all sequences; this applies to PSD
and harmonic signal analysis only; it is particularly
useful for two-tone-test where spectral smoothing
of background noise is anticpated, while maintaining
the full resolution for harmonic peaks
-scalerbw[=n] scale to mean value in n decades
-divisor[=n] FFT becomes very inefficient if the factorization
of the number of samples includes large prime numbers.
This option removes the least number of samples to
the total number of samples a multiple of "n"
-ASCII[=base] write result to two-column ASCII files with basename 'base'
-logascii[=n] write ASCII data on logarithmic frequency axis with
one value per 'n' decades
-avgascii only average values for output to ASCII file
this option speeds up calculation together with
-scalerbw which increases computation time
with the square of frequency
-rms report rms values of input data
-harmonic scale output appropriate fro harmonic signals
useful for two-tone-tests of linearity (see below)
-pad n pad time series with zeroes; n gives the integer factor
for the number of samples; the raw amplitude spectrum
has to be understood as the spectrum of the whole
series including the padded zeroes; PSD and harmonic
signals are scaled to represent the taper time window
only, such that padding is a means of smoothing only
-nsegments n subdivide input time series in "n" overlapping
sequences (overlap is 50%); spectral analysis is
done for each sequence individually; the result
is the mean of all sequences; this applies to PSD
and harmonic signal analysis only; it is particularly
useful for two-tone-test where spectral smoothing
of background noise is anticpated, while maintaining
the full resolution for harmonic peaks
#
# ----- END OF foutra_options.txt -----
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