[−][src]Crate pointcloud
Point Cloud
Abstracts data access over several files and glues metadata files to vector data files
Modules
data_sources | Some data sources and a trait to dimension and uniformly reference the data contained. The only currently supported are memmaps and ram blobs. |
glued_data_cloud | Simple gluing structs that abstracts away multi cloud access |
label_sources | Some label sets to modularly glue together with the data sources. |
loaders | Loaders for datasets. Just opens them up and returns a point cloud. |
pc_errors | The errors that can occur when a point cloud is loading, working or saving |
summaries | Summaries for some label types |
Structs
AdjMatrix | A sparse adjacency matrix. |
CosineSim | Not a norm! Still, helpful for document clouds and the like |
DenseIter | |
L1 | L1 norm, the sum of absolute values |
L2 | L2 norm, the square root of the sum of squares |
Linfty | L infity norm, the max of the absolute values of the elements |
SimpleLabeledCloud | Simply shoves together a point cloud and a label set, for a modular label system |
Enums
Point | An actual point, self contained with it's own objects on the heap. |
PointRef | Reference to a point inside of a dataset. |
Traits
LabelSet | A trait for a container that just holds labels. Meant to be used in conjunction with |
LabeledCloud | A point cloud that is labeled |
Metric | The trait that enables a metric |
PointCloud | Base trait for a point cloud |
Summary | A summary for labels and metadata. You can make this an empty zero sized type for when you don't need it. |
Type Definitions
DefaultCloud | A sensible default for an unlabeled cloud |
DefaultLabeledCloud | A sensible default for an labeled cloud |
PointIndex | To make things more obvious, we type the point index. This is abstracted over the files that were used to build the point cloud |
PointName | To make things more obvious, we type the point name that we pull from the label CSV |