{-# LANGUAGE ForeignFunctionInterface #-}
-----------------------------------------------------------------------------
-- |
-- Module      :  HFANN
-- Copyright   :  (c) Olivier Boudry 2008
-- License     :  BSD-style (see the file LICENSE)
-- 
-- Maintainer  :  olivier.boudry@gmail.com
-- Stability   :  experimental
-- Portability :  portable
--
-- The Fast Artificial Neural Network Library (FANN) is a free open source
-- neural network library written in C with support for both fully connected
-- and sparsely connected networks (<http://leenissen.dk/fann/>).
--
-- HFANN is a Haskell interface to this library.
--
-----------------------------------------------------------------------------

module HFANN.Data (
  -- * Data Types
  FannType,
  CFannType,
  CFannTypePtr,
  ActivationFunction,
  TrainAlgorithm,
  Fann (..),
  FannPtr,
  TrainData (..),
  TrainDataPtr,

  -- * Activation Functions
  fannLinear,
  fannThreshold,
  fannThresholdSymetric,
  fannSigmoid,
  fannSigmoidStepwise,
  fannSigmoidSymetric,
  fannSigmoidSymetricStepwise,
  fannGaussian,
  fannGaussianSymetric,
  fannGaussianStepwise,
  fannElliot,
  fannElliotSymetric,
  fannLinearPiece,
  fannLinearPieceSymetric,

  -- * Training Algorithms
  fannTrainIncremental,
  fannTrainBatch,
  fannTrainRPROP,
  fannTrainQuickProp
  ) where

import Data.Word
import Foreign (Ptr)
import Foreign.C.Types

#include <doublefann.h>

-- | The Haskell input/output type
--
-- This is the data type used in Haskell to represent the input/output data.
--
type FannType = Double

-- |The C input/output type
-- This is the data type used in the C library to represent the input/output
-- data.
--
type CFannType = CDouble

-- | A pointer to the C input/output type
--
type CFannTypePtr = Ptr CDouble

-- | The ANN structure
--
data Fann = Fann

-- | A pointer to an ANN structure
--
type FannPtr = Ptr Fann

-- | Data type of the training data structure
--
data TrainData = TrainData

-- | A pointer to the training data structure type
--
type TrainDataPtr = Ptr TrainData

-- | The type of the @Training Algorithm@ enumeration
--
type TrainAlgorithm = #{type enum fann_train_enum}

#{enum TrainAlgorithm,
  ,fannTrainIncremental = FANN_TRAIN_INCREMENTAL
  ,fannTrainBatch = FANN_TRAIN_BATCH
  ,fannTrainRPROP = FANN_TRAIN_RPROP
  ,fannTrainQuickProp = FANN_TRAIN_QUICKPROP
  }

-- | The type of the @Activation Function@ enumeration
--
type ActivationFunction = #{type enum fann_activationfunc_enum}

#{enum ActivationFunction,
  , fannLinear = FANN_LINEAR
  , fannThreshold =  FANN_THRESHOLD
  , fannThresholdSymetric = FANN_THRESHOLD_SYMMETRIC
  , fannSigmoid = FANN_SIGMOID
  , fannSigmoidStepwise = FANN_SIGMOID_STEPWISE
  , fannSigmoidSymetric = FANN_SIGMOID_SYMMETRIC
  , fannSigmoidSymetricStepwise = FANN_SIGMOID_SYMMETRIC_STEPWISE
  , fannGaussian = FANN_GAUSSIAN
  , fannGaussianSymetric = FANN_GAUSSIAN_SYMMETRIC
  , fannGaussianStepwise = FANN_GAUSSIAN_STEPWISE
  , fannElliot = FANN_ELLIOT
  , fannElliotSymetric = FANN_ELLIOT_SYMMETRIC
  , fannLinearPiece = FANN_LINEAR_PIECE
  , fannLinearPieceSymetric = FANN_LINEAR_PIECE_SYMMETRIC
  }