Visualize cross-sections in attribute form

[leendertvanwolfswinkel]

Please take into account that we may want to extend the functionality of this in the future, so probably use pyqtgraph. If choosing another python package, please discuss this first. We are also using pyqtgraph in ThreeDiToolbox quite a bit, so it would be nice to use the same here.

Example This is an example / sketch of a tabulated trapezium cross-section for a Cross-section location. The DEM does not have to be plotted.

Private Zenhub Image

Requirements

• Labelled X and Y axis
• Elevation (Y axis) should be relative to datum, i.e. lowest point of cross-section is at reference level / crest level / invert level

Layers it applies to The following layers have cross-sections:

• Weir: bottom = crest level
• Orifice: bottom = crest level
• Cross-section location: bottom = reference level
• Culvert: bottom = max(invert_level_start_point, invert_level_end_point)
• Pipe: bottom = max(invert_level_start_point, invert_level_end_point)

Cross-section shapes See https://docs.3di.live/h_onedee_flow.html#cross-section-shapes for illustrations

• Closed rectangle: Width of rectangle = cross_section_width, height of rectangle = cross_section_height
• Open rectangle: Width of rectangle = cross_section_width, height of rectangle = cross_section_width. No line at the top of the rectangle
• Circle: Diameter = cross_section_width
• Egg: We have python code for this somewhere
• Inverted egg: We have python code for this somewhere
• Tabulated rectangle: X axis ranges from -1max(width) to 1max(width). Data source: cross_section_table. Interpret the values in this table as height, width pairs. No interpolation between the data points.
• Tabulated rectangle: X axis ranges from -1max(width) to 1max(width). Data source: cross_section_table. Interpret the values in this table as height, width pairs. Linear interpolation between the data points
• YZ: X axis starts a 0. Data source: cross_section_table. Interpret the values in this table as X, Y pairs in the plot. Linear interpolation between the data points