Difference between revisions of "Walkthrough model worfklow reuse"

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{|style="margin: 0 auto;"
 
{|style="margin: 0 auto;"
| [[File:ReuseWorkflowSketchPlotOrder.png|thumb|upright|400px| right click to get the plotting options of a step ]]
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| [[File:ReuseWorkflowPlotTableSketchOrder.png|thumb|upright|400px| right click to get the plotting options of a step. ]]
| [[File:ReuseWorkflowSketchPlot.png|thumb|upright|300px|created backbone traversing the <tt>points</tt> ]]
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| [[File:ReuseWorkflowPlotTableSketch.png|thumb|upright|300px|created points and orientations ]]
 
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... not forgetting to save the ''model'' into the catalogue. The model will contain the generated <tt>crop_points</tt> and also the parameter values used to generate them.
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[[File:ReuseWorkflowSaveModel.png|thumb|center|300px|Saving the ''model'']]

Revision as of 06:20, 17 August 2016

This walkthrough shows how to reuse the geometric computations performed on a single model onto a larger set of models.

We can use a synthetic tomogram containing different tubular structures. In this catalogue, we open the tomogram with dtmslice, and then define a filament model following the usual procedure, so that we end up with a single model containing a set on points.

We will now define a workflow, i.e., a method of converting points into crop_points.

We open the workflow editor of the active model, and start operating the steps, checking graphically the result of each parameter selection. We create first a backbone, selecting the interval between backbone elements.

Creation of the backbone

And check how the results looks like:

right click to get the plotting options of a step
created backbone traversing the points

We then proceed for the next step: selection of the interval (in pixels) between two consecutive crop points.

Selection of interval between crop points

And check again the results:

right click to get the plotting options of a step.
created points and orientations

... not forgetting to save the model into the catalogue. The model will contain the generated crop_points and also the parameter values used to generate them.

Saving the model