Modules

Subpackages

• curve_apps.contours package
  • Submodules
  • curve_apps.contours.driver module
    • ContoursDriver
      • ContoursDriver.get_contours()
      • ContoursDriver.make_curve()
  • curve_apps.contours.params module
• curve_apps.edges package
  • Submodules
  • curve_apps.edges.driver module
    • EdgesDriver
      • EdgesDriver.get_canny_edges()
      • EdgesDriver.get_edges()
      • EdgesDriver.get_line_indices()
      • EdgesDriver.make_curve()
  • curve_apps.edges.params module
• curve_apps.trend_lines package
  • Submodules
  • curve_apps.trend_lines.driver module
    • TrendLinesDriver
      • TrendLinesDriver.get_connections()
      • TrendLinesDriver.labels
      • TrendLinesDriver.make_curve()
      • TrendLinesDriver.parts
      • TrendLinesDriver.vertices
  • curve_apps.trend_lines.params module

Submodules

curve_apps.driver module

class curve_apps.driver.BaseCurveDriver(*args: Any, **kwargs: Any)

Bases: Driver

Driver for the edge detection application.

Parameters:

parameters – Application parameters.

abstract make_curve()

run()

Run method of the driver.

curve_apps.utils module

curve_apps.utils.filter_segments_orientation(vertices: numpy.ndarray, edges: numpy.ndarray, azimuth: float, azimuth_tol: float)

Filter segments orientation.

Parameters:

• vertices – Vertices for points.

• edges – Edges for points.

• azimuth – Filter angle (degree) on segments orientation, clockwise from North.

• azimuth_tol – Tolerance (degree) on the azimuth.

Returns:

Array of boolean.

curve_apps.utils.find_curves(vertices: numpy.ndarray, parts: numpy.ndarray, params: TrendLineDetectionParameters | None = None) → list[list[list[float]]]

Find curves in a set of points.

Parameters:

• vertices – Vertices for points.

• parts – Identifier for points belong to common parts.

• params – Trend line detection parameters.

Returns:

List of curves.

curve_apps.utils.get_contour_list(params: ContourDetectionParameters) → list[float]

Compute contours requested by input parameters.

Returns:

Corresponding list of values in float format.

curve_apps.utils.image_to_grid_coordinate_transfer(image: numpy.ndarray, grid: list[numpy.ndarray]) → Callable

Returns a function to interpolate from image to grid coordinates.

Parameters:

grid – list of x and y grids.

curve_apps.utils.interp_to_grid(entity: geoh5py.objects.ObjectBase, values: numpy.ndarray, resolution: float, max_distance: float) → tuple[list[numpy.ndarray], numpy.ndarray]

Interpolate values into a regular grid based on entity locations.

Parameters:

• entity – Geoh5py object with locations data.

• values – Data to be interpolated to grid.

• resolution – Grid resolution

• max_distance – Maximum distance used in weighted average.

curve_apps.utils.set_vertices_height(vertices: numpy.ndarray, entity: geoh5py.objects.ObjectBase)

Uses entity z values to add height column to an Nx2 vertices array.

Parameters:

• vertices – Nx2 array of vertices.

• entity – geoh5py entity with vertices property.

returns: Nx3 array of vertices.

curve_apps.utils.walk_edges(path: list, incoming: list, edges: np.ndarray, vertices: np.ndarray, damping: float = 0.0, *, mask: np.ndarray | None = None) → tuple[list, np.ndarray]

Find all edges connected to a point.

Parameters:

• path – Current list of edges forming a path.

• incoming – Incoming edge.

• edges – All edges.

• vertices – Direction of the edges.

• damping – Damping factor between [0, 1] for the path roughness.

• mask – Mask for nodes that have already been visited.

Returns:

Edges connected to point.