/**
 * @file hdf5BindDatasets.hpp
 * @brief Utilities for combining HDF5 datasets
 * @note 2026-03-07 Output datasets now inherit compression level from input datasets
 *         via setCompressionLevel() called before every createDataset() invocation.
 * 
 * This file provides functionality for binding multiple HDF5 datasets together,
 * either by rows or columns. It supports operations similar to R's rbind and cbind
 * functions, but optimized for HDF5 datasets. The implementation handles large
 * datasets efficiently and provides proper error handling.
 * 
 * Key features:
 * - Column-wise binding (cbind equivalent)
 * - Row-wise binding (rbind equivalent)
 * - Index-based row binding
 * - Automatic dimension adjustment
 * - Support for unlimited datasets
 * 
 * @note This module is part of the BigDataStatMeth library
 * @note Data in R is transposed when stored in HDF5 data files
 */

#ifndef BIGDATASTATMETH_UTIL_BIND_DATASETS_HPP
#define BIGDATASTATMETH_UTIL_BIND_DATASETS_HPP

#include <RcppEigen.h>
#include "H5Cpp.h"

namespace BigDataStatMeth {

    /**
     * @brief Binds multiple HDF5 datasets together
     * 
     * @param filename HDF5 file path
     * @param group Group containing the datasets
     * @param datasets Vector of dataset names to bind
     * @param dsOut Pointer to output HDF5 dataset
     * @param func Operation type:
     *        - 0: Bind by Columns (cbind)
     *        - 1: Bind by Rows (rbind)
     *        - 2: Bind by Rows with index
     * @param binternal Internal processing flag
     * 
     * @note When binding by columns, if dimensions don't match, the function will attempt to
     *       resize matrices by adding needed columns/rows
     * @note For row binding, the number of columns must match
     * @note For column binding, the number of rows must match
     * 
     * @throws H5::FileIException on file access errors
     * @throws H5::DataSetIException on dataset operation errors
     * @throws H5::DataSpaceIException on dataspace operation errors
     * @throws std::exception on general errors
     * 
     * Performance considerations:
     * - Uses Eigen for efficient matrix operations
     * - Implements block-wise reading and writing
     * - Supports unlimited datasets for flexible growth
     */
    inline void RcppBind_datasets_hdf5( std::string filename, std::string group, 
                                 Rcpp::StringVector datasets, 
                                 BigDataStatMeth::hdf5Dataset* dsOut,  
                                 int func, bool binternal )
    {
        
        try {

            H5::Exception::dontPrint();

            // BigDataStatMeth::hdf5Dataset* dsIn = nullptr;
            std::unique_ptr<BigDataStatMeth::hdf5Dataset> dsIn(nullptr);
            
            hsize_t* dims_out;
            std::vector<hsize_t> stride = {1, 1},
                                 block = {1, 1},
                                 offset = {0, 0},
                                 count = {0, 0};
            
            // Seek all datasets to perform calculus
            for( int i=0; i < datasets.size(); i++ ) 
            {
                
                std::string strdataset = group +"/" + datasets(i);
                
                // dsIn = new BigDataStatMeth::hdf5Dataset(filename, strdataset, false);
                dsIn.reset( new BigDataStatMeth::hdf5Dataset(filename, strdataset, false) );
                dsIn->openDataset();
                
                // Real data set dimension
                dims_out =   dsIn->dim();
                
                // Get block from complete matrix
                std::vector<double> vdIn( dims_out[0] * dims_out[1] ); 
                dsIn->readDatasetBlock( {0, 0}, {dims_out[0], dims_out[1]}, stride, block, vdIn.data() );
                Eigen::Map<Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>> original (vdIn.data(), dims_out[0], dims_out[1] );    
                
                // delete dsIn; dsIn = nullptr;
                if( func == 0 || func == 1) {
                    
                    if( func == 0 ) { // byCols
                        
                        // Test if dimmensions are correct
                        if( original.cols() != static_cast<Eigen::Index>(count[0]) && i!=0) {
                            
                            if( static_cast<Eigen::Index>(count[0]) > original.cols()) {
                                // Append needed cols to merge by cols
                                int iappend = count[0] - original.cols();
                                //..// original.conservativeResize(original.rows(), original.cols() + iappend);
                                original.resize(original.rows(), original.cols() + iappend);
                                
                            } else {
                                std::string strmessage = "Can't bind current dataset, number of rows differ on size";
                                Rcpp::message(Rcpp::wrap(strmessage));
                                return void();
                            }
                        }
                        
                        offset[0] = offset[0] + count[1];
                        
                    } else { // byRows
                        
                        // Check if dimmensions are correct
                        if( original.rows() != static_cast<Eigen::Index>(count[0])  && i!=0) {
                            
                            if( static_cast<Eigen::Index>(count[0]) > original.rows()) {
                                // Append needed rows to merge by rows
                                int iappend = count[0] - original.rows();
                                original.resize(original.rows() + iappend, original.cols());
                                
                            } else {
                                std::string strmessage = "Can't bind current dataset, number of columns differ on size";
                                Rcpp::message(Rcpp::wrap(strmessage));
                                return void();
                            }
                            
                        }
                        offset[1] = offset[1] + count[0];
                    }
                    
                    count[0] = original.cols();
                    count[1] = original.rows();
                    
                    if(i == 0) { 
                        dsOut->inheritCompressionLevel(dsIn->getCompressionLevel());
                        dsOut->createUnlimitedDataset(count[0], count[1], "real");
                    }
                    dsOut->openDataset();
                    
                    if( func == 1 && i!=0) {
                        dsOut->extendUnlimitedDataset(count[0], 0 );
                    } else if ( func == 0 && i!=0) {
                        dsOut->extendUnlimitedDataset( 0, count[1] );
                    }
                    
                    dsOut->writeDatasetBlock( Rcpp::wrap(original), offset, count, stride, block, true);
                    
                } else {
                    // delete dsIn; dsIn = nullptr;
                    throw std::runtime_error("Group not exists, create the input datasets before proceed");
                }
            }
            
        } catch( H5::FileIException& error ) {
            throw std::runtime_error("c++ exception RcppBind_datasets_hdf5 (File IException)");
        } catch( H5::DataSetIException& error ) { // catch failure caused by the dstosplit operations
            throw std::runtime_error("c++ exception RcppBind_datasets_hdf5 (dstosplit IException)");
        } catch( H5::DataSpaceIException& error ) { // catch failure caused by the DataSpace operations
            throw std::runtime_error("c++ exception RcppBind_datasets_hdf5 (DataSpace IException)");
        } catch(std::exception &ex) {
            throw std::runtime_error(std::string("c++ exception RcppBind_datasets_hdf5: ") + ex.what());
        } catch (...) {
            throw std::runtime_error("C++ exception RcppBind_datasets_hdf5 (unknown reason)");
        } 
        
        return void();
        
    }

    /**
     * @brief High-level interface for binding HDF5 datasets
     * 
     * @param filename HDF5 file path
     * @param group Source group containing input datasets
     * @param datasets Vector of dataset names to bind
     * @param outgroup Output group path
     * @param outdataset Output dataset name
     * @param func Binding function type:
     *        - "bindCols": Combine datasets by columns
     *        - "bindRows": Combine datasets by rows
     *        - "bindRowsbyIndex": Combine datasets by rows using an index
     * @param binternal Internal processing flag
     * @param overwrite Optional flag to overwrite existing output dataset
     * 
     * @throws std::range_error if func is not one of the allowed values
     * @throws H5::FileIException on file access errors
     * @throws H5::GroupIException on group operation errors
     * @throws H5::DataSetIException on dataset operation errors
     * @throws std::exception on general errors
     * 
     * @see RcppBind_datasets_hdf5(std::string, std::string, Rcpp::StringVector, BigDataStatMeth::hdf5Dataset*, int, bool)
     *      for the lower-level implementation
     * 
     * Example:
     * @code
     * RcppBind_datasets_hdf5("data.h5", "/input", {"ds1", "ds2"}, "/output", "combined", "bindRows", false, true);
     * @endcode
     */
    inline void RcppBind_datasets_hdf5( std::string filename, std::string group, Rcpp::StringVector datasets, 
                               std::string outgroup, std::string outdataset, std::string func, 
                               bool binternal, Rcpp::Nullable<bool> overwrite = false )
    {
        
        
        
        try
        {
            H5::Exception::dontPrint();
            // BigDataStatMeth::hdf5Dataset* dsOut = nullptr;
            std::unique_ptr<BigDataStatMeth::hdf5Dataset> dsOut(nullptr);
            
            Rcpp::NumericVector oper = {0, 1, 2};
            oper.names() = Rcpp::CharacterVector({ "bindCols", "bindRows", "bindRowsbyIndex"});
            
            bool boverwrite;
            
            if( overwrite.isNull()) { boverwrite = false; } 
            else {   boverwrite = Rcpp::as<bool>(overwrite); }
            
            if (func.compare("bindCols") != 0 && func.compare("bindRows") != 0  && func.compare("bindRowsbyIndex") != 0 ) {
                throw std::range_error( "Function to apply must be \"bindRows\", \"bindCols\" or \"bindRowsbyIndex\" other values are not allowed" );
                return void();
            }
            
            int bindFunction = oper.findName( func );
            
            // dsOut = new BigDataStatMeth::hdf5Dataset(filename, outgroup, outdataset, boverwrite);
            dsOut.reset( new BigDataStatMeth::hdf5Dataset(filename, outgroup, outdataset, boverwrite) );
            
            RcppBind_datasets_hdf5( filename, group, datasets, dsOut.get(), bindFunction, binternal);
            
            // delete dsOut; dsOut = nullptr;
            
        } catch( H5::FileIException& error ) { 
            throw std::runtime_error("c++ exception RcppBind_datasets_hdf5_ (File IException)");
        } catch( H5::GroupIException & error ) { 
            throw std::runtime_error("c++ exception RcppBind_datasets_hdf5_ (Group IException)");
        } catch( H5::DataSetIException& error ) { 
            throw std::runtime_error("c++ exception RcppBind_datasets_hdf5_ (DataSet IException)");
        } catch(std::exception& ex) {
            throw std::runtime_error(std::string("c++ exception RcppBind_datasets_hdf5_: ") + ex.what());
        } catch (...) {
            throw std::runtime_error("C++ exception RcppBind_datasets_hdf5_ (unknown reason)");
        }
        
        return void();
        
    }

}

#endif // BIGDATASTATMETH_UTIL_BIND_DATASETS_HPP
