package owl
sectionYPositions = computeSectionYPositions($el), 10)"
x-init="setTimeout(() => sectionYPositions = computeSectionYPositions($el), 10)"
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On This Page
- Create dense matrices
- Dense row vectors and meshgrids
- Obtain the basic properties of a matrix
- Manipulate a matrix
- Iterate elements, columns, and rows.
- Examin elements and compare two matrices
- Randomisation functions
- Input/Output and helper functions
- Unary mathematical operations
- Binary mathematical operations
- Fucntions of in-place modification
OCaml Scientific and Engineering Computing
Install
dune-project
Dependency
Authors
Maintainers
Sources
owl-0.7.1.tbz
sha256=4efa33bb2f04fa14f493a3dd9bf4210895ff558d490cf8c3bd1484ba20ff26f3
sha512=1c03d0822a642975ab0b08e621012e17b7b41563196e7c2e93dd2e3338a9b0b37a63c1c6a786b8a40f32f9bd21b4c57f898b12e1b1cdd892b78fe4927e4c35b6
doc/owl/Owl_dense_matrix_c/index.html
Module Owl_dense_matrix_c
Complex dense matrix module: this module supports operations on dense matrices of complex numbers. The complex number has a record type of {re = float; im = float}.
This page only contains detailed explanations for the operations specific to Dense.Complex module. Most of the other operations are the same to those in Dense.Real module, therefore please refer to the documentation of Dense.Real for more information.
type elt = Complex.ttype mat = (Complex.t, Bigarray.complex32_elt) Owl_dense_matrix_generic.ttype cast_mat = (float, Bigarray.float32_elt) Owl_dense_matrix_generic.tCreate dense matrices
val empty : int -> int -> matval zeros : int -> int -> matval ones : int -> int -> matval eye : int -> matval bernoulli : ?p:float -> int -> int -> matval unit_basis : int -> int -> matval hadamard : int -> matval magic : int -> matDense row vectors and meshgrids
val vector : int -> matval vector_zeros : int -> matval vector_ones : int -> matval vector_uniform : int -> matObtain the basic properties of a matrix
val shape : mat -> int * intval row_num : mat -> intval col_num : mat -> intval numel : mat -> intval nnz : mat -> intval density : mat -> floatval size_in_bytes : mat -> intManipulate a matrix
val get_fancy : Owl_types.index list -> mat -> matval set_fancy : Owl_types.index list -> mat -> mat -> unitval reset : mat -> unitval swap_rows : mat -> int -> int -> unitval swap_cols : mat -> int -> int -> unitval top : mat -> int -> int array arrayval bottom : mat -> int -> int array arrayval argsort :
mat ->
(int64, Bigarray.int64_elt, Bigarray.c_layout) Bigarray.Genarray.tIterate elements, columns, and rows.
Examin elements and compare two matrices
val is_zero : mat -> boolval is_positive : mat -> boolval is_negative : mat -> boolval is_nonpositive : mat -> boolval is_nonnegative : mat -> boolval is_normal : mat -> boolval not_nan : mat -> boolval not_inf : mat -> boolRandomisation functions
Input/Output and helper functions
val save : mat -> string -> unitval load : string -> matval save_txt : ?sep:string -> ?append:bool -> mat -> string -> unitval load_txt : ?sep:string -> string -> matUnary mathematical operations
Binary mathematical operations
Fucntions of in-place modification
val bernoulli_ : ?p:float -> out:mat -> unitval zeros_ : out:mat -> unitval ones_ : out:mat -> unitval sort_ : mat -> unit sectionYPositions = computeSectionYPositions($el), 10)"
x-init="setTimeout(() => sectionYPositions = computeSectionYPositions($el), 10)"
>
On This Page
- Create dense matrices
- Dense row vectors and meshgrids
- Obtain the basic properties of a matrix
- Manipulate a matrix
- Iterate elements, columns, and rows.
- Examin elements and compare two matrices
- Randomisation functions
- Input/Output and helper functions
- Unary mathematical operations
- Binary mathematical operations
- Fucntions of in-place modification