package owl

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Create sparse ndarray
Obtain basic properties
Manipulate a N-dimensional array
Iterate array elements
Examine array elements or compare two arrays
Input/Output and helper functions
Unary mathematical operations
Binary mathematical operations

package owl

owl
- Owl
- Owl_algodiff
  - D
    
    Arr
    
    Mat
    
    Maths
  - S
    
    Arr
    
    Mat
    
    Maths
- Owl_algodiff_generic
  - Make
    
    A
    
    Arr
    
    M
    
    Mat
    
    Maths
  - MatrixSig
  - NdarraySig
- Owl_algodiff_numerical
- Owl_backend_gsl_linalg
- Owl_backend_gsl_maths
- Owl_backend_gsl_stats
- Owl_cluster
- Owl_const
  - CGS
  - CGSM
  - MKS
  - Prefix
  - SI
- Owl_conv
- Owl_dataset
- Owl_dense
- Owl_dense_common
- Owl_dense_matrix
  - C
  - D
  - Generic
  - Operator
  - S
  - Z
- Owl_dense_matrix_c
- Owl_dense_matrix_d
- Owl_dense_matrix_generic
- Owl_dense_matrix_s
- Owl_dense_matrix_z
- Owl_dense_ndarray
  - C
  - D
  - Generic
  - Operator
  - S
  - Z
- Owl_dense_ndarray_c
- Owl_dense_ndarray_d
- Owl_dense_ndarray_generic
- Owl_dense_ndarray_s
- Owl_dense_ndarray_z
- Owl_dense_vector
- Owl_dense_vector_c
- Owl_dense_vector_d
- Owl_dense_vector_generic
- Owl_dense_vector_s
- Owl_dense_vector_z
- Owl_ext
  - Dense
- Owl_ext_binop
  - C_C
  - C_DAC
  - C_DAD
  - C_DAS
  - C_DAZ
  - C_DMC
  - C_DMD
  - C_DMS
  - C_DMZ
  - C_F
  - DAC_C
  - DAC_DAC
  - DAC_DAD
  - DAC_DAS
  - DAC_DAZ
  - DAC_F
  - DAD_C
  - DAD_DAC
  - DAD_DAD
  - DAD_DAS
  - DAD_DAZ
  - DAD_F
  - DAS_C
  - DAS_DAC
  - DAS_DAD
  - DAS_DAS
  - DAS_DAZ
  - DAS_F
  - DAZ_C
  - DAZ_DAC
  - DAZ_DAD
  - DAZ_DAS
  - DAZ_DAZ
  - DAZ_F
  - DMC_C
  - DMC_DMC
  - DMC_DMD
  - DMC_DMS
  - DMC_DMZ
  - DMC_F
  - DMD_C
  - DMD_DMC
  - DMD_DMD
  - DMD_DMS
  - DMD_DMZ
  - DMD_F
  - DMS_C
  - DMS_DMC
  - DMS_DMD
  - DMS_DMS
  - DMS_DMZ
  - DMS_F
  - DMZ_C
  - DMZ_DMC
  - DMZ_DMD
  - DMZ_DMS
  - DMZ_DMZ
  - DMZ_F
  - F_C
  - F_DAC
  - F_DAD
  - F_DAS
  - F_DAZ
  - F_DMC
  - F_DMD
  - F_DMS
  - F_DMZ
  - F_F
- Owl_ext_dense_matrix
  - BasicSig
  - C
  - CZ_Sig
  - D
  - Make_Basic
    
    M
    
    P
  - Make_CZ
    
    M
    
    P
  - Make_SD
    
    M
    
    P
  - PackSig
  - Pack_DMC
  - Pack_DMD
  - Pack_DMS
  - Pack_DMZ
  - S
  - SD_Sig
  - Z
- Owl_ext_dense_ndarray
  - BasicSig
  - C
  - CZ_Sig
  - D
  - Make_Basic
    
    M
    
    P
  - Make_CZ
    
    M
    
    P
  - Make_SD
    
    M
    
    P
  - PackSig
  - Pack_DAC
  - Pack_DAD
  - Pack_DAS
  - Pack_DAZ
  - S
  - SD_Sig
  - Z
- Owl_ext_lifts
  - DAC_DAD
  - DAC_DAZ
  - DAD_DAZ
  - DAS_DAC
  - DAS_DAD
  - DAS_DAZ
  - DMC_DMD
  - DMC_DMZ
  - DMD_DMZ
  - DMS_DMC
  - DMS_DMD
  - DMS_DMZ
  - F_C
- Owl_ext_types
- Owl_ext_uniop
  - C
  - DAC
  - DAD
  - DAS
  - DAZ
  - DMC
  - DMD
  - DMS
  - DMZ
  - F
- Owl_fft
- Owl_linalg
- Owl_maths
- Owl_nlp
- Owl_nlp_corpus
- Owl_nlp_lda
  - FTreeLDA
  - LightLDA
  - SimpleLDA
  - SparseLDA
- Owl_nlp_lda0
  - FTreeLDA
  - LightLDA
  - SimpleLDA
  - SparseLDA
- Owl_nlp_similarity
- Owl_nlp_tfidf
- Owl_nlp_utils
- Owl_nlp_vocabulary
- Owl_operator
  - BasicSig
  - ExtendSig
  - Make_Basic
    
    M
  - Make_Extend
    
    M
  - Make_Matrix
    
    M
  - MatrixSig
- Owl_optimise
- Owl_plot
- Owl_pretty
  - Context
  - Toplevel
- Owl_regression
- Owl_slicing
- Owl_sparse
- Owl_sparse_common
- Owl_sparse_dok_matrix
- Owl_sparse_matrix
  - C
  - D
  - Generic
  - Operator
  - S
  - Z
- Owl_sparse_matrix_c
- Owl_sparse_matrix_d
- Owl_sparse_matrix_generic
- Owl_sparse_matrix_s
- Owl_sparse_matrix_z
- Owl_sparse_ndarray
  - C
  - D
  - Generic
  - Operator
  - S
  - Z
- Owl_sparse_ndarray_c
- Owl_sparse_ndarray_d
- Owl_sparse_ndarray_generic
- Owl_sparse_ndarray_s
- Owl_sparse_ndarray_z
- Owl_stats
  - Cdf
  - Pdf
  - Rnd
- Owl_toplevel
- Owl_types
- Owl_utils
  - Stack
owl_neural
- Owl_neural
- Owl_neural_layer
  - Activation
  - AvgPool2D
  - Conv2D
  - Conv3D
  - Dropout
  - Feedforward
  - Flatten
  - FullyConnected
  - GRU
  - Init
  - Input
  - LSTM
  - Lambda
  - Linear
  - LinearNoBias
  - MaxPool2D
  - Recurrent
  - Reshape
- Owl_neural_optimise
  - Batch
  - Clipping
  - Gradient
  - Learning_Rate
  - Loss
  - Momentum
  - Params
  - Regularisation
  - Stopping
  - Utils

Legend:
Library
Module
Module type
Parameter
Class
Class type

type elt = float

type arr = (float, Bigarray.float32_elt) Owl_sparse_ndarray_generic.t

Create sparse ndarray

val zeros : int array -> arr

val binary : ?density:float -> int array -> arr

val uniform : ?scale:float -> ?density:float -> int array -> arr

Obtain basic properties

val shape : arr -> int array

val num_dims : arr -> int

val nth_dim : arr -> int -> int

val numel : arr -> int

val nnz : arr -> int

val density : arr -> float

val same_shape : arr -> arr -> bool

val kind : arr -> (elt, Bigarray.float32_elt) Bigarray.kind

Manipulate a N-dimensional array

val get : arr -> int array -> elt

val set : arr -> int array -> elt -> unit

val slice : int option array -> arr -> arr

val clone : arr -> arr

val flatten : arr -> arr

val reshape : arr -> int array -> arr

val transpose : ?axis:int array -> arr -> arr

val swap : int -> int -> arr -> arr

Iterate array elements

val iteri : ?axis:int option array -> (int array -> elt -> unit) -> arr -> unit

val iter : ?axis:int option array -> (elt -> unit) -> arr -> unit

val mapi : ?axis:int option array -> (int array -> elt -> elt) -> arr -> arr

val map : ?axis:int option array -> (elt -> elt) -> arr -> arr

val filteri : 
  ?axis:int option array ->
  (int array -> elt -> bool) ->
  arr ->
  int array array

val filter : ?axis:int option array -> (elt -> bool) -> arr -> int array array

val foldi : 
  ?axis:int option array ->
  (int array -> 'c -> elt -> 'c) ->
  'c ->
  arr ->
  'c

val fold : ?axis:int option array -> ('c -> elt -> 'c) -> 'c -> arr -> 'c

val iteri_nz : 
  ?axis:int option array ->
  (int array -> elt -> unit) ->
  arr ->
  unit

val iter_nz : ?axis:int option array -> (elt -> unit) -> arr -> unit

val mapi_nz : ?axis:int option array -> (int array -> elt -> elt) -> arr -> arr

val map_nz : ?axis:int option array -> (elt -> elt) -> arr -> arr

val filteri_nz : 
  ?axis:int option array ->
  (int array -> elt -> bool) ->
  arr ->
  int array array

val filter_nz : 
  ?axis:int option array ->
  (elt -> bool) ->
  arr ->
  int array array

val foldi_nz : 
  ?axis:int option array ->
  (int array -> 'c -> elt -> 'c) ->
  'c ->
  arr ->
  'c

val fold_nz : ?axis:int option array -> ('c -> elt -> 'c) -> 'c -> arr -> 'c

Examine array elements or compare two arrays

val exists : (elt -> bool) -> arr -> bool

val not_exists : (elt -> bool) -> arr -> bool

val for_all : (elt -> bool) -> arr -> bool

val is_zero : arr -> bool

val is_positive : arr -> bool

val is_negative : arr -> bool

val is_nonpositive : arr -> bool

val is_nonnegative : arr -> bool

val equal : arr -> arr -> bool

val not_equal : arr -> arr -> bool

val greater : arr -> arr -> bool

val less : arr -> arr -> bool

val greater_equal : arr -> arr -> bool

val less_equal : arr -> arr -> bool

Input/Output and helper functions

val to_array : arr -> (int array * elt) array

val of_array : int array -> (int array * elt) array -> arr

val print : arr -> unit

val save : arr -> string -> unit

val load : string -> arr

Unary mathematical operations

val min : arr -> elt

val max : arr -> elt

val minmax : arr -> elt * elt

val abs : arr -> arr

val neg : arr -> arr

val sum : arr -> elt

val average : arr -> elt

Binary mathematical operations

val add : arr -> arr -> arr

val sub : arr -> arr -> arr

val mul : arr -> arr -> arr

val div : arr -> arr -> arr

val add_scalar : arr -> elt -> arr

val sub_scalar : arr -> elt -> arr

val mul_scalar : arr -> elt -> arr

val div_scalar : arr -> elt -> arr

val scalar_add : elt -> arr -> arr

val scalar_sub : elt -> arr -> arr

val scalar_mul : elt -> arr -> arr

val scalar_div : elt -> arr -> arr