Functions
void	find_ab (const raft::handle_t &handle, UMAPParams *params)

std::unique_ptr< raft::sparse::COO< float, int > >	get_graph (const raft::handle_t &handle, float X, float y, int n, int d, int64_t knn_indices, float knn_dists, UMAPParams *params)

void	refine (const raft::handle_t &handle, float X, int n, int d, raft::sparse::COO< float, int > graph, UMAPParams params, float embeddings)

void	init_and_refine (const raft::handle_t &handle, float X, int n, int d, raft::sparse::COO< float, int > graph, UMAPParams params, float embeddings)

void	fit (const raft::handle_t &handle, float X, float y, int n, int d, int64_t knn_indices, float knn_dists, UMAPParams params, float embeddings, raft::sparse::COO< float, int > *graph)

void	fit_sparse (const raft::handle_t &handle, int indptr, int indices, float data, size_t nnz, float y, int n, int d, int knn_indices, float knn_dists, UMAPParams params, float embeddings, raft::sparse::COO< float, int > *graph)

void	transform (const raft::handle_t &handle, float X, int n, int d, float orig_X, int orig_n, float embedding, int embedding_n, UMAPParams params, float *transformed)

void	transform_sparse (const raft::handle_t &handle, int indptr, int indices, float data, size_t nnz, int n, int d, int orig_x_indptr, int orig_x_indices, float orig_x_data, size_t orig_nnz, int orig_n, float embedding, int embedding_n, UMAPParams params, float *transformed)

Function Documentation

◆ find_ab()

void ML::UMAP::find_ab	(	const raft::handle_t &	handle,
		UMAPParams *	params
	)

Returns the simplical set to be consumed by the ML::UMAP::refine function.

Parameters

[in]	handle	raft::handle_t
[out]	params	pointer to ML::UMAPParams object of which the a and b parameters will be updated

◆ fit()

void ML::UMAP::fit	(	const raft::handle_t &	handle,
		float *	X,
		float *	y,
		int	n,
		int	d,
		int64_t *	knn_indices,
		float *	knn_dists,
		UMAPParams *	params,
		float *	embeddings,
		raft::sparse::COO< float, int > *	graph
	)

Dense fit

Parameters

[in]	handle	raft::handle_t
[in]	X	pointer to input array
[in]	y	pointer to labels array
[in]	n	n_samples of input array
[in]	d	n_features of input array
[in]	knn_indices	pointer to knn_indices of input (optional)
[in]	knn_dists	pointer to knn_dists of input (optional)
[in]	params	pointer to ML::UMAPParams object
[out]	embeddings	pointer to embedding produced through projection
[out]	graph	pointer to fuzzy simplicial set graph

◆ fit_sparse()

void ML::UMAP::fit_sparse	(	const raft::handle_t &	handle,
		int *	indptr,
		int *	indices,
		float *	data,
		size_t	nnz,
		float *	y,
		int	n,
		int	d,
		int *	knn_indices,
		float *	knn_dists,
		UMAPParams *	params,
		float *	embeddings,
		raft::sparse::COO< float, int > *	graph
	)

Sparse fit

Parameters

[in]	handle	raft::handle_t
[in]	indptr	pointer to index pointer array of input array
[in]	indices	pointer to index array of input array
[in]	data	pointer to data array of input array
[in]	nnz	pointer to data array of input array
[in]	y	pointer to labels array
[in]	n	n_samples of input array
[in]	d	n_features of input array
[in]	knn_indices	pointer to knn_indices of input (optional)
[in]	knn_dists	pointer to knn_dists of input (optional)
[in]	params	pointer to ML::UMAPParams object
[out]	embeddings	pointer to embedding produced through projection
[out]	graph	pointer to fuzzy simplicial set graph

◆ get_graph()

std::unique_ptr<raft::sparse::COO<float, int> > ML::UMAP::get_graph	(	const raft::handle_t &	handle,
		float *	X,
		float *	y,
		int	n,
		int	d,
		int64_t *	knn_indices,
		float *	knn_dists,
		UMAPParams *	params
	)

Returns the simplical set to be consumed by the ML::UMAP::refine function.

Parameters

[in]	handle	raft::handle_t
[in]	X	pointer to input array
[in]	y	pointer to labels array
[in]	n	n_samples of input array
[in]	d	n_features of input array
[in]	knn_indices	pointer to knn_indices (optional)
[in]	knn_dists	pointer to knn_dists (optional)
[in]	params	pointer to ML::UMAPParams object

Returns: : simplical set as a unique pointer to a raft::sparse::COO object

◆ init_and_refine()

void ML::UMAP::init_and_refine	(	const raft::handle_t &	handle,
		float *	X,
		int	n,
		int	d,
		raft::sparse::COO< float, int > *	graph,
		UMAPParams *	params,
		float *	embeddings
	)

Initializes embeddings and performs a UMAP fit on them, which enables iterative fitting without callbacks.

Parameters

[in]	handle	raft::handle_t
[in]	X	pointer to input array
[in]	n	n_samples of input array
[in]	d	n_features of input array
[in]	graph	pointer to raft::sparse::COO object computed using ML::UMAP::get_graph
[in]	params	pointer to ML::UMAPParams object
[out]	embeddings	pointer to current embedding with shape n * n_components, stores updated embeddings on executing refine

◆ refine()

void ML::UMAP::refine	(	const raft::handle_t &	handle,
		float *	X,
		int	n,
		int	d,
		raft::sparse::COO< float, int > *	graph,
		UMAPParams *	params,
		float *	embeddings
	)

Performs a UMAP fit on existing embeddings without reinitializing them, which enables iterative fitting without callbacks.

Parameters

[in]	handle	raft::handle_t
[in]	X	pointer to input array
[in]	n	n_samples of input array
[in]	d	n_features of input array
[in]	graph	pointer to raft::sparse::COO object computed using ML::UMAP::get_graph
[in]	params	pointer to ML::UMAPParams object
[out]	embeddings	pointer to current embedding with shape n * n_components, stores updated embeddings on executing refine

◆ transform()

void ML::UMAP::transform	(	const raft::handle_t &	handle,
		float *	X,
		int	n,
		int	d,
		float *	orig_X,
		int	orig_n,
		float *	embedding,
		int	embedding_n,
		UMAPParams *	params,
		float *	transformed
	)

Dense transform

Parameters

[in]	handle	raft::handle_t
[in]	X	pointer to input array to be inferred
[in]	n	n_samples of input array to be inferred
[in]	d	n_features of input array to be inferred
[in]	orig_X	pointer to original training array
[in]	orig_n	number of rows in original training array
[in]	embedding	pointer to embedding created during training
[in]	embedding_n	number of rows in embedding created during training
[in]	params	pointer to ML::UMAPParams object
[out]	transformed	pointer to embedding produced through projection

◆ transform_sparse()

void ML::UMAP::transform_sparse	(	const raft::handle_t &	handle,
		int *	indptr,
		int *	indices,
		float *	data,
		size_t	nnz,
		int	n,
		int	d,
		int *	orig_x_indptr,
		int *	orig_x_indices,
		float *	orig_x_data,
		size_t	orig_nnz,
		int	orig_n,
		float *	embedding,
		int	embedding_n,
		UMAPParams *	params,
		float *	transformed
	)

Sparse transform

Parameters

[in]	handle	raft::handle_t
[in]	indptr	pointer to index pointer array of input array to be inferred
[in]	indices	pointer to index array of input array to be inferred
[in]	data	pointer to data array of input array to be inferred
[in]	nnz	number of stored values of input array to be inferred
[in]	n	n_samples of input array
[in]	d	n_features of input array
[in]	orig_x_indptr	pointer to index pointer array of original training array
[in]	orig_x_indices	pointer to index array of original training array
[in]	orig_x_data	pointer to data array of original training array
[in]	orig_nnz	number of stored values of original training array
[in]	orig_n	number of rows in original training array
[in]	embedding	pointer to embedding created during training
[in]	embedding_n	number of rows in embedding created during training
[in]	params	pointer to ML::UMAPParams object
[out]	transformed	pointer to embedding produced through projection

Functions

Function Documentation

◆ find_ab()

◆ fit()

◆ fit_sparse()

◆ get_graph()

◆ init_and_refine()

◆ refine()

◆ transform()

◆ transform_sparse()