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Processing GEF files

Classes have been created to simplify usage of GEF files such as a data access class (GEFData) that includes visualization of GEF measurement data, or classification of soil layout. All classes and functions can be imported from the viktor.geo module. For more detailed examples, please check the docstring of the functions.

GEFFile class

The GEFFile object is used to parse the file content of GEF files and convert the data to dictionary or GEFData object. The data is split into 'measurement_data' and 'headers' category. For 'measurement_data' the compulsory fields are 'Rf', 'qc' and 'elevation'. These are automatically always returned and stored when parsing a GEF file. Additional columns can be requested from the controller by specifying them in the parse call using the keyword "additional_columns". The height reference- and coordinate system are parsed from the gef file and return in the properties "height_system" and "coordinate_system". Any property relating with a reference relates to the height_system value. In general the following definitions (taken from the norm) are used:

  • depth is always a positive number, denoting vertical distance from start of measurement to end
  • length is always a positive number, denoting distance measured along path of measurement
  • elevation is the vertical position of a measurement wrt to a reference datum. (so reference_datum_height - depth), can be partially positive and negative

GEFFile.parse needs to be mocked within the context of (automated) testing.

GEFData class

GEFData is a data class to simplify the usage of GEF data. A GEFData object can directly be initiated with the dictionary that is created by the GEFFile class. All keys from 'measurement_data' and 'headers' are set as attributes of the GEFData object, and are therefore directly accessible.

The measurement data can be used to determine the soil types with classify(method: Type[ClassificationMethod], return_soil_layout_obj: bool = True). Currently, the RobertsonMethod and TableMethod are supported for soil classification. The properties of all possible soil types need to be provided when calling the classify method in order to create a SoilLayout.


GEFData.classify needs to be mocked within the context of (automated) testing.

GEF visualization

For easy visualization of GEF data, a helper function is created. A code example is provide below:


class Controller(ViktorController):

@ImageView("GEF plot", duration_guess=5)
def visualize(self, params, **kwargs):
gef_data = ...
soil_layout_original = ...
soil_layout_user = ...
svg_image = gef_visualization(self.gef_data, self.soil_layout_original, self.soil_layout_user, as_file=True)
return ImageResult(svg_image)

If the standard helper function does not satisfy the requirements, it is possible to create your own matplotlib. GEFData has get_resistance_visualization(axes: matplotlib.pyplot.Axes) and get_cone_visualization(axes: matplotlib.pyplot.Axes) functions, while SoilLayout has get_visualization(axes: matplotlib.pyplot.Axes). All functions require a matplotlib Axes object that are stateful, and therefore the visualization functions do not return. Example to use one of the visualization functions is shown below:

import matplotlib.pyplot as plt

class Controller(ViktorController):

@ImageView("GEF plot", duration_guess=5)
def visualize(self, params, **kwargs):
gef_data = ...

# Create main figure
fig = plt.figure(figsize=(8.27, 11.69))

# Define contour (rectangle) for cone visualization, and create Axes object that can be modified by functions
rect_cone = [0.1, 0.1, 0.4, 0.9] # [left, bottom, width, height]
cone_axes = plt.axes(rect_cone)
# Modify created Axes objects

# Convert to SVG for visualization
svg_data = StringIO()
fig.savefig(svg_data, format='svg', bbox_inches='tight', pad_inches=0.8)
return ImageResult(svg_data)

Soil structure

A general purpose soil structure has been introduced that is being used by the GEF parser, namely Soil, SoilLayer and SoilLayout. A SoilLayout is a collection of SoilLayer objects, which contain a Soil, top and bottom of layer as attributes. Extra properties can be added to the Soil class to provide more (geotechnical) information. Properties can be stored on Soil and SoilLayer object by calling update_properties and providing a dict with the relevant parameters.

A SoilLayout can be manually created using the __init__(self, soil_layers: List[SoilLayer]) function, but in order to simplify storage of the object in the database class methods have been created. To store the object in the database the function serialize() can be used. For re-initialization of SoilLayout the function from_dict(cls, soil_layout_dict: Dict[str, List]) can be used.