Hi,

Negative intensities are actually extremely common, especially for
those experiencing fast relaxation.  In the time course, exponential
can often go below the noise level.  At that point you have a white
noise distribution about zero, so you have equal change of positive
and negative values.  This is no problem at all and such data should
not be deselected.  These noise points at the end also significantly
help with the fitting by indicating to the optimisation algorithm that
the curve should not be significant at these points.

Regards,

Edward

On 29 August 2014 15:22, Troels Emtekær Linnet <[email protected]> wrote:
> Hi Edward.
>
> Is all intensities always positive?
>
> Some of our students tried, with a peak list which contained negative
> intensities.
>
> Could spins with negative intensities be automatically de-selected?
>
> Or is intensities sometimes negative?
>
> best
>
>
>
> ---------- Forwarded message ----------
> From:  <[email protected]>
> Date: 2014-08-29 14:57 GMT+02:00
> Subject: r25432 - /trunk/specific_analyses/relax_disp/data.py
> To: [email protected]
>
>
> Author: bugman
> Date: Fri Aug 29 14:57:38 2014
> New Revision: 25432
>
> URL: http://svn.gna.org/viewcvs/relax?rev=25432&view=rev
> Log:
> Better error checking for the
> specific_analyses.relax_disp.average_intensity() function.
>
> This function would fail with a traceback if a peak intensity error
> analysis had not yet been
> performed.  Now it fails instead with a clean RelaxError so that the
> user knows what is wrong.
>
>
> Modified:
>     trunk/specific_analyses/relax_disp/data.py
>
> Modified: trunk/specific_analyses/relax_disp/data.py
> URL: 
> http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/data.py?rev=25432&r1=25431&r2=25432&view=diff
> ==============================================================================
> --- trunk/specific_analyses/relax_disp/data.py  (original)
> +++ trunk/specific_analyses/relax_disp/data.py  Fri Aug 29 14:57:38 2014
> @@ -149,7 +149,7 @@
>          # Error intensity data.
>          if error:
>              # Error checking.
> -            if not int_keys[i] in spin.peak_intensity_err:
> +            if not hasattr(spin, 'peak_intensity_err') or not
> int_keys[i] in spin.peak_intensity_err:
>                  raise RelaxError("The peak intensity errors are
> missing the key '%s'." % int_keys[i])
>
>              # Sum.
>
>
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