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Statistics panel enhancement #43

weidemann opened this issue Oct 29, 2013 · 1 comment

Statistics panel enhancement #43

weidemann opened this issue Oct 29, 2013 · 1 comment


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@weidemann weidemann commented Oct 29, 2013

Reviewing PyCorrFit vs 0.8.0. Parameter plotting in the Statistics panel is very nice and helpful. Here I suggest few improvements and little cosmetics:

  1. It would ease the workflow to keep the order of appearance of parameters in the pull-down menu the same as in the statistics export frame ”variables” (for a revised order see below).
  2. The parameters are plotted versus internal page number starting from 0 to max. The data points of the lowest and the highest number fuse with the y-axis and are hardly visible.
  3. The text “Create a table..” should be moved inside the “variables” frame, since it refers to export not to display. The frame “variables” could be renamed into “export parameters”, I think this more straightforward.
  4. When many pages are plotted the default size of the Statistics panel is not large enough. One can drag the corner to improve visibility. However, when selecting a different page in the main fitting panel it snaps back. Maybe it can be educated to behave and keep size.
  5. After “clear session” the statistics panel should revert to default.
  6. During fitting, one may encounter the situation to first explore the values (e.g. triplet time), derive a mean, and fix this parameter to this value in a second round. Therefore it would be useful to display the parameter average in the Statistics panel. One could add below “Plot parameter” an additional row containing “Average ” and the respective output window. Since it is called the “Statistics” panel displaying a "Standard deviation" for the selected parameter might also be a good idea.
  7. The order of appearance of the exported fields could be more systematic. E.g. for the most often used T-3D-3D model: (1) filename/title (2) Model Name, (3) avg. signal [kHz], (4) G(0), (5) tau-trp [µs], (6) T [%], (7) tau-diff1 [ms], (8) F1 [%], (9) tau-diff2 [µs], (10) F2 [%], (11) tau-diff3 [µs], (12) F3 [%]. Then the secondary parameters like (13) n [particles], (14) CPP [kHz/particle] etc. Then the pure annotations like (15) duration [sec] etc.
    The rationale behind is that one quickly has to identify the type of experiment and the used model. Then the primary fit parameters should follow, because this is the most important fields. Primary fit parameters are simply the pairs of correlation times together with their fractional contribution to the overall amplitude (G(0)). Secondary parameters are derived but not unambiguous. For example they may depend on non-correlated background. Another issue is that some papers claim for blinking GFPs that G(0) = 1/n and not G(0) = 1/n/(1-T) as it is for triplet, etc. So the user has eventually to take control and make decisions. When primary fit parameters appear first they also will be first in the exported tab delimited text. This is convenient for referencing the fields and post-processing of the data.
  8. Primary parameters could appear checked by default when opening the statistics panel.
  9. Deleted pages produce gaps on the x-axis.
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@paulmueller paulmueller commented Jan 25, 2014

Closed in 0.8.2

paulmueller pushed a commit that referenced this issue Sep 30, 2015
…n frame

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paulmueller pushed a commit that referenced this issue Sep 30, 2015
… title

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paulmueller pushed a commit that referenced this issue Sep 30, 2015
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paulmueller pushed a commit that referenced this issue Sep 30, 2015
… session

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paulmueller pushed a commit that referenced this issue Sep 30, 2015
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paulmueller pushed a commit that referenced this issue Sep 30, 2015
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paulmueller pushed a commit that referenced this issue Sep 30, 2015
…ls might be possible as documented there:

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