Module Owl_sparse_matrix_s

type elt = float
type mat = ( float, Stdlib.Bigarray.float32_elt ) Owl_sparse_matrix_generic.t
Create sparse matrices
val zeros : int -> int -> mat
val ones : int -> int -> mat
val eye : int -> mat
val binary : int -> int -> mat
val uniform : ?scale:float -> int -> int -> mat
val uniform_int : ?a:int -> ?b:int -> int -> int -> mat
val sequential : int -> int -> mat
val linspace : elt -> elt -> int -> mat
Obtain the basic properties of a matrix
val shape : mat -> int * int
val row_num : mat -> int
val col_num : mat -> int
val row_num_nz : mat -> int
val col_num_nz : mat -> int
val numel : mat -> int
val nnz : mat -> int
val nnz_rows : mat -> int array
val nnz_cols : mat -> int array
val density : mat -> float
Manipulate a matrix
val insert : mat -> int -> int -> elt -> unit
val get : mat -> int -> int -> elt
val set : mat -> int -> int -> elt -> unit
val reset : mat -> unit
val fill : mat -> elt -> unit
val copy : mat -> mat
val transpose : mat -> mat
val diag : mat -> mat
val row : mat -> int -> mat
val col : mat -> int -> mat
val rows : mat -> int array -> mat
val cols : mat -> int array -> mat
val prune : mat -> elt -> float -> unit
Iterate elements, columns, and rows
val iteri : ( int -> int -> elt -> unit ) -> mat -> unit
val iter : ( elt -> unit ) -> mat -> unit
val mapi : ( int -> int -> elt -> elt ) -> mat -> mat
val map : ( elt -> elt ) -> mat -> mat
val foldi : ( int -> int -> 'a -> elt -> 'a ) -> 'a -> mat -> 'a
val fold : ( 'a -> elt -> 'a ) -> 'a -> mat -> 'a
val filteri : ( int -> int -> elt -> bool ) -> mat -> (int * int) array
val filter : ( elt -> bool ) -> mat -> (int * int) array
val iteri_rows : ( int -> mat -> unit ) -> mat -> unit
val iter_rows : ( mat -> unit ) -> mat -> unit
val iteri_cols : ( int -> mat -> unit ) -> mat -> unit
val iter_cols : ( mat -> unit ) -> mat -> unit
val mapi_rows : ( int -> mat -> 'a ) -> mat -> 'a array
val map_rows : ( mat -> 'a ) -> mat -> 'a array
val mapi_cols : ( int -> mat -> 'a ) -> mat -> 'a array
val map_cols : ( mat -> 'a ) -> mat -> 'a array
val fold_rows : ( 'a -> mat -> 'a ) -> 'a -> mat -> 'a
val fold_cols : ( 'a -> mat -> 'a ) -> 'a -> mat -> 'a
val iteri_nz : ( int -> int -> elt -> unit ) -> mat -> unit
val iter_nz : ( elt -> unit ) -> mat -> unit
val mapi_nz : ( int -> int -> elt -> elt ) -> mat -> mat
val map_nz : ( elt -> elt ) -> mat -> mat
val foldi_nz : ( int -> int -> 'a -> elt -> 'a ) -> 'a -> mat -> 'a
val fold_nz : ( 'a -> elt -> 'a ) -> 'a -> mat -> 'a
val filteri_nz : ( int -> int -> elt -> bool ) -> mat -> (int * int) array
val filter_nz : ( elt -> bool ) -> mat -> (int * int) array
val iteri_rows_nz : ( int -> mat -> unit ) -> mat -> unit
val iter_rows_nz : ( mat -> unit ) -> mat -> unit
val iteri_cols_nz : ( int -> mat -> unit ) -> mat -> unit
val iter_cols_nz : ( mat -> unit ) -> mat -> unit
val mapi_rows_nz : ( int -> mat -> 'a ) -> mat -> 'a array
val map_rows_nz : ( mat -> 'a ) -> mat -> 'a array
val mapi_cols_nz : ( int -> mat -> 'a ) -> mat -> 'a array
val map_cols_nz : ( mat -> 'a ) -> mat -> 'a array
val fold_rows_nz : ( 'a -> mat -> 'a ) -> 'a -> mat -> 'a
val fold_cols_nz : ( 'a -> mat -> 'a ) -> 'a -> mat -> 'a
Examine elements and compare two matrices
val exists : ( elt -> bool ) -> mat -> bool
val not_exists : ( elt -> bool ) -> mat -> bool
val for_all : ( elt -> bool ) -> mat -> bool
val exists_nz : ( elt -> bool ) -> mat -> bool
val not_exists_nz : ( elt -> bool ) -> mat -> bool
val for_all_nz : ( elt -> bool ) -> mat -> bool
val is_zero : mat -> bool
val is_positive : mat -> bool
val is_negative : mat -> bool
val is_nonnegative : mat -> bool
val equal : mat -> mat -> bool
val not_equal : mat -> mat -> bool
val greater : mat -> mat -> bool
val less : mat -> mat -> bool
val greater_equal : mat -> mat -> bool
val less_equal : mat -> mat -> bool
Randomisation functions
val permutation_matrix : int -> mat
val draw_rows : ?replacement:bool -> mat -> int -> mat * int array
val draw_cols : ?replacement:bool -> mat -> int -> mat * int array
val shuffle_rows : mat -> mat
val shuffle_cols : mat -> mat
val shuffle : mat -> mat
Input/Output and helper functions
val to_array : mat -> (int array * elt) array
val of_array : int -> int -> (int array * elt) array -> mat
val to_dense : mat -> Owl_dense_matrix_s.mat
val of_dense : Owl_dense_matrix_s.mat -> mat
val print : mat -> unit
val save : mat -> string -> unit
val load : string -> mat
Unary mathematical operations
val min : mat -> elt
val max : mat -> elt
val minmax : mat -> elt * elt
val trace : mat -> elt
val sum : mat -> elt
val mean : mat -> elt
val sum_rows : mat -> mat
val sum_cols : mat -> mat
val mean_rows : mat -> mat
val mean_cols : mat -> mat
val abs : mat -> mat
val neg : mat -> mat
val l1norm : mat -> elt
val l2norm : mat -> elt
Binary mathematical operations
val add : mat -> mat -> mat
val sub : mat -> mat -> mat
val mul : mat -> mat -> mat
val div : mat -> mat -> mat
val dot : mat -> mat -> mat
val add_scalar : mat -> elt -> mat
val sub_scalar : mat -> elt -> mat
val mul_scalar : mat -> elt -> mat
val div_scalar : mat -> elt -> mat
val scalar_add : elt -> mat -> mat
val scalar_sub : elt -> mat -> mat
val scalar_mul : elt -> mat -> mat
val scalar_div : elt -> mat -> mat
val power_scalar : mat -> elt -> mat
val mpow : mat -> float -> mat