Get_qualification_table_plot not providing clear image

Which tool versions are you using?

SDK: v13.6.0
Platform: v2022.11.0
Python: v3.10
Isolation mode: venv/docker

Current Behavior

The get_qualification_table_plot method from the TableMethod class results in a very unclear picture

The axis ticks are not readable, neither are the numbers in the areas and the legend is presented twice on the right hand side because there are 2 plots with the same soil types. The second iteration of the legend also goes off the screen

Expected Behavior

More focus on one picture, maybe make subsections or something in which the user can select to see either the qc_normed on the qc regular plot in full screen.

Context (optional, but preferred)

Right now I don’t feel like I can visually present the applied soil classification to the user as it is too unclear.

If there is a workaround to do this myself I would be happy to learn more about it.

Hello @Rutger,

The idea behind this plot is to draw a square for each row in your classification table, where the x-coordinates are the Qc min and max values, and the y-coordinates are the Rf min and max values. If the user has filled in the table “correctly”, he/she should see a figure where the entire domain is covered by a square. That way, every measurement (forming a point with coordinates [Qc, Rf]) falls into a soil type.

This also means that, indeed: you are able to create this visualisation for yourself as well, by taking the classification table from your params, and using e.g. Plotly to draw a stacked bar plot for each row.

However, I suspect there is something else going a bit wrong here, and I am very curious about the classification table you are using in this situation. The reason there are two plots is that there are two sets of Qc values, Qc and Qc normalized. As we specify in the docs: “For more information about qc_norm (qc_normalized), see table 2.b in in NEN 9997-1+C1:2012, point g specifically.”. But the main thing I suspect is goinig wrong here: in each row you should fill in either Qc or Qc normalized, not both (which is what I think you did). The normalized Qc is (in the NEN table) only applicable to Grind, and Sand. If you do not fill in any Qc normalized in your table, you will also only get a single plot. But if you do fill it in, on that same row you should leave Qc empty. Only 1 of both is used for classification, so even if you fill in both measurements will always be classificied based on the “first” fit.

Anyway, as I said as a first question I would be very interested in the table you used to create this plot.