fastgac.GaussianAccumulatorS2Beta

class fastgac.GaussianAccumulatorS2Beta

This GaussianAccumulator can handle the entire sphere by using a space filling curve designed by Google’s S2 Geometry library. It projects a sphere to the faces of a cube and creates six separate hilbert curves for each face. It then stitches these curves together into one continuous thread. This class does not need S2 Geometry Library. We are using a port callsed s2nano that pulls out the essential SFC routine. It basically works by converting a normal to being integrated into a s2_id (SFC unique integer). It performs a faster interpolated and branchless binary search to find the closest cell in buckets. It then performs a local neighborhood search centered around the cell which actually looks at the surface normal.

__init__(self: fastgac_pybind.GaussianAccumulatorS2Beta, level: int = 1) → None

clear_count(self: fastgac_pybind.GaussianAccumulatorS2Beta) → None

Clears all the histogram counts for each cell. Useful to call after peak detection to ‘reset’ the mesh.

copy_ico_mesh(self: fastgac_pybind.GaussianAccumulatorS2Beta, mesh_order: bool = False) → fastgac_pybind.IcoMesh

Creates a copy of the ico mesh.

find_peaks(self: fastgac_pybind.GaussianAccumulatorS2Beta, threshold_abs: int = 25, exclude_border: bool = False, cluster_distance: float = 0.1, min_cluster_weight: float = 0.15) → fastgac_pybind.MatX3d

Find the peaks on the Gaussian Accumulator

get_average_normals_by_vertex(self: fastgac_pybind.GaussianAccumulatorS2Beta, mesh_order: bool = False) → fastgac_pybind.MatX3d

Average the normalized buckets counts (triangles) into the vertices of the mesh.The order by default is sorted by the space filling curve value attached to each cell.

get_bucket_average_normals(self: fastgac_pybind.GaussianAccumulatorS2Beta, mesh_order: bool = False) → fastgac_pybind.MatX3d

Gets the average surface normals of the buckets in the histogram after integration.The order by default is sorted by the space filling curve value attached to each cell.

get_bucket_normals(self: fastgac_pybind.GaussianAccumulatorS2Beta, mesh_order: bool = False) → fastgac_pybind.MatX3d

Gets the surface normals of the buckets in the histogram.The order by default is sorted by the space filling curve value attached to each cell.

get_bucket_sfc_values(self: fastgac_pybind.GaussianAccumulatorS2Beta) → fastgac_pybind.VectorULongInt

Get the space filling curve values of each bucket. Will be sorted low to high.

get_normalized_bucket_counts(self: fastgac_pybind.GaussianAccumulatorS2Beta, mesh_order: bool = False) → fastgac_pybind.VectorDouble

Get the normalized bucket counts in the histogram.The order by default is sorted by the space filling curve value attached to each cell.

get_normalized_bucket_counts_by_vertex(self: fastgac_pybind.GaussianAccumulatorS2Beta, mesh_order: bool = False) → fastgac_pybind.VectorDouble

Average the normalized buckets counts (triangles) into the vertices of the mesh.The order by default is sorted by the space filling curve value attached to each cell.

integrate(self: fastgac_pybind.GaussianAccumulatorS2Beta, normals: fastgac_pybind.MatX3d, num_nbr: int = 12) → fastgac_pybind.VectorULongInt

Will intergrate the normals into the S2 Historgram

property bucket_neighbors

Fast lookup matrix to find neighbors of a bucket

property buckets

The buckets in the histogram, corresponding to cells/triangles on the mesh

property ico_chart

The underlying unwrapped icosphere

property mesh

The underlying sphere-like mesh of the Gaussian Accumulator

property num_buckets

The number of buckets in histogram, size(buckets)