cars.applications.triangulation.triangulation_wrappers

Preprocessing module: contains functions used for triangulation

Functions

add_layer(dataset, layer_name, layer_coords, point_cloud)	Add layer point cloud to point cloud dataset
interpolate_geoid_height(geoid_filename, positions[, ...])	terrain to index conversion
geoid_offset(points, geoid_path)	Compute the point cloud height offset from geoid.
generate_point_cloud_file_names(csv_dir, laz_dir, row, col)	generate the point cloud CSV and LAZ filenames of a given tile from its
compute_performance_map(alti_ref, z_inf, z_sup[, ...])	Compute performance map

Module Contents

cars.applications.triangulation.triangulation_wrappers.add_layer(dataset, layer_name, layer_coords, point_cloud)

Add layer point cloud to point cloud dataset

Parameters:

• dataset – input disparity map dataset

• layer_name – layer key in disparity dataset

• layer_coords – layer axis name in disparity dataset

• point_cloud – output point cloud dataset

cars.applications.triangulation.triangulation_wrappers.interpolate_geoid_height(geoid_filename, positions, interpolation_method='linear')

terrain to index conversion retrieve geoid height above ellispoid This is a modified version of the Shareloc interpolate_geoid_height function that supports Nan positions (return Nan)

Parameters:

• geoid_filename (str) – geoid_filename

• positions (2D numpy array: (number of points,[long coord, lat coord])) – geodetic coordinates

• interpolation_method (str) – default is ‘linear’ (interpn parameter)

Returns:

geoid height

Return type:

1 numpy array (number of points)

cars.applications.triangulation.triangulation_wrappers.geoid_offset(points, geoid_path)

Compute the point cloud height offset from geoid.

Parameters:

• points (xarray.Dataset or pandas.DataFrame) – point cloud data in lat/lon/alt WGS84 (EPSG 4326) coordinates.

• geoid_path (string) – path to input geoid file on disk

Returns:

the same point cloud but using geoid as altimetric reference.

Return type:

xarray.Dataset or pandas.DataFrame

cars.applications.triangulation.triangulation_wrappers.generate_point_cloud_file_names(csv_dir: str, laz_dir: str, row: int, col: int, index: dict = None, pair_key: str = 'PAIR_0')

generate the point cloud CSV and LAZ filenames of a given tile from its corresponding row and col. Optionally update the index, if provided.

Parameters:

• csv_dir (str) – target directory for csv files, If None no csv filenames will be generated

• laz_dir (str) – target directory for laz files, If None no laz filenames will be generated

• row (int) – row index of the tile

• col (int) – col index of the tile

• index (dict) – product index to update with the filename

• pair_key (str) – current product key (used in index), if a list is given a filename will be added to the index for each element of the list

cars.applications.triangulation.triangulation_wrappers.compute_performance_map(alti_ref, z_inf, z_sup, ambiguity_map=None, perf_ambiguity_threshold=None)

Compute performance map

Parameters:

• alti_ref (xarray Dataarray) – z

• z_inf (xarray Dataarray) – z inf map

• z_sup (xarray Dataarray) – z sup map

• ambiguity_map (xarray Dataarray) – None or ambiguity map

• perf_ambiguity_threshold (None or float) – ambiguity threshold to use