confirmed that (buf)spectralshape is now in Hz

release-packaging/HelpSource/Classes/FluidBufSpectralShape.schelp

@@ -11,12 +11,12 @@ The descriptors are:
 LIST::
 ##the four first statistical moments (https://en.wikipedia.org/wiki/Moment_(mathematics) ), more commonly known as:
 	LIST::
-	## the spectral centroid (1) in spectral bins as units. This is the point that splits the spectrum in 2 halves of equal energy. It is the weighted average of the magnitude spectrum.
-	## the spectral spread (2) in spectral bins. This is the standard deviation of the spectrum envelop, or the average of the distance to the centroid.
-	## the normalised skewness (3) as ratio. This indicates how tilted is the spectral curve in relation to the middle of the spectral frame, i.e. half of the Nyquist frequency. If it is below the bin representing that frequency, i.e. the central bin of the magnitude spectrum, it is positive.
+	## the spectral centroid (1) in Hz. This is the point that splits the spectrum in 2 halves of equal energy. It is the weighted average of the magnitude spectrum.
+	## the spectral spread (2) in Hz. This is the standard deviation of the spectrum envelop, or the average of the distance to the centroid.
+	## the normalised skewness (3) as ratio. This indicates how tilted is the spectral curve in relation to the middle of the spectral frame, i.e. half of the Nyquist frequency. If it is below that frequency, i.e. the central bin of the magnitude spectrum, it is positive.
 	## the normalised kurtosis (4) as ratio. This indicates how focused is the spectral curve. If it is peaky, it is high.
 	::
-	## the rolloff (5) in bin number. This indicates the bin under which 95% of the energy is included.
+	## the rolloff (5) in Hz. This indicates the frequency under which 95% of the energy is included.
 	## the flatness (6) in dB. This is the ratio of geometric mean of the magnitude, over the arithmetic mean of the magnitudes. It yields a very approximate measure on how noisy a signal is.
 	## the crest (7) in dB. This is the ratio of the loudest magnitude over the RMS of the whole frame. A high number is an indication of a loud peak poking out from the overal spectral curve.
 
@@ -86,7 +86,7 @@ Routine{
 
 // listen to the source and look at the buffer
 b.play;
-c.plot(minval:-5, maxval:250)
+c.plot(separately:true)
 ::
 
 STRONG::A stereo buffer example.::
@@ -115,5 +115,5 @@ Routine{
 )
 
 // look at the buffer: 7shapes for left, then 7 shapes for right
-c.plot(minval:-25, maxval:150)
+c.plot(separately:true)
 ::

release-packaging/HelpSource/Classes/FluidSpectralShape.schelp

@@ -10,12 +10,12 @@ The descriptors are:
 LIST::
 ##the four first statistical moments (https://en.wikipedia.org/wiki/Moment_(mathematics) ), more commonly known as:
 	LIST::
-	## the spectral centroid (1) in spectral bins as units. This is the point that splits the spectrum in 2 halves of equal energy. It is the weighted average of the magnitude spectrum.
-	## the spectral spread (2) in spectral bins. This is the standard deviation of the spectrum envelop, or the average of the distance to the centroid.
-	## the normalised skewness (3) as ratio. This indicates how tilted is the spectral curve in relation to the middle of the spectral frame, i.e. half of the Nyquist frequency. If it is below the bin representing that frequency, i.e. the central bin of the magnitude spectrum, it is positive.
+	## the spectral centroid (1) in Hz. This is the point that splits the spectrum in 2 halves of equal energy. It is the weighted average of the magnitude spectrum.
+	## the spectral spread (2) in Hz. This is the standard deviation of the spectrum envelop, or the average of the distance to the centroid.
+	## the normalised skewness (3) as ratio. This indicates how tilted is the spectral curve in relation to the middle of the spectral frame, i.e. half of the Nyquist frequency. If it is below that frequency, i.e. the central bin of the magnitude spectrum, it is positive.
 	## the normalised kurtosis (4) as ratio. This indicates how focused is the spectral curve. If it is peaky, it is high.
 	::
-	## the rolloff (5) in bin number. This indicates the bin under which 95% of the energy is included.
+	## the rolloff (5) in Hz. This indicates the frequency under which 95% of the energy is included.
 	## the flatness (6) in dB. This is the ratio of geometric mean of the magnitude, over the arithmetic mean of the magnitudes. It yields a very approximate measure on how noisy a signal is.
 	## the crest (7) in dB. This is the ratio of the loudest magnitude over the RMS of the whole frame. A high number is an indication of a loud peak poking out from the overal spectral curve.
 
@@ -129,7 +129,7 @@ a = Array.fill(7, {arg i;
 });
 )
 
-// this time, update a little more slowly, and convert in Hz the 3 descriptors published in bins by the algorythm.
+// this time, update a little more slowly.
 (
 r = Routine {
 	{
@@ -138,13 +138,7 @@ r = Routine {
 			{
 				if(w.isClosed.not) {
 					val.do({arg item,index;
-						if ((index < 2) || (index == 4))
-						{
-							a[index].string = (item * s.sampleRate / 1024).round(0.01);
-						} {
-							a[index].string = item.round(0.01);
-						};
-					})
+						a[index].string = item.round(0.01)})
 				}
 			}.defer
 		});