remove use of python (5d172dea) · Commits · IVAS Codec Public Collaboration / IVAS Codec

scripts/binauralRenderer_interface/CMakeLists.txt

+38 −4

Original line number	Diff line number	Diff line
		@@ -11,6 +11,28 @@ set(IVAS_TRUNK_ENC_PATH ${IVAS_TRUNK_PATH}/lib_enc)
		set(IVAS_TRUNK_COM_PATH ${IVAS_TRUNK_PATH}/lib_com)
		set(IVAS_TRUNK_DEBUG_PATH ${IVAS_TRUNK_PATH}/lib_debug)

		option(USE_PYTHON "Use SOFA python reader" OFF)
		option(USE_MATLAB "Use SOFA matlab reader" ON)

		if (USE_MATLAB)
		find_package(Matlab REQUIRED)
		message("Matlab_VERSION = ${Matlab_VERSION}")
		message("Matlab_ROOT_DIR = ${Matlab_ROOT_DIR}")
		message("Matlab_INCLUDE_DIRS = ${Matlab_INCLUDE_DIRS}")
		if (NOT Matlab_MAT_LIBRARY)
		string(REPLACE "mex" "mat" Matlab_MAT_LIBRARY ${Matlab_MEX_LIBRARY})
		endif()
		message("Matlab_MAT_LIBRARY = ${Matlab_MAT_LIBRARY}")
		message("Matlab_LIBRARIES = ${Matlab_LIBRARIES}")
		message("Matlab_MX_LIBRARY = ${Matlab_MX_LIBRARY}")
		message("Matlab_MEX_LIBRARY = ${Matlab_MEX_LIBRARY}")
		message("Matlab_ENGINE_LIBRARY = ${Matlab_ENGINE_LIBRARY}")
		message("Matlab_DATAARRAY_LIBRARY = ${Matlab_DATAARRAY_LIBRARY}")
		add_definitions(-DUSE_MATLAB)
		include_directories(${Matlab_INCLUDE_DIRS} ${IVAS_TRUNK_UTIL_PATH} ${IVAS_TRUNK_ENC_PATH} ${IVAS_TRUNK_DEC_PATH} ${IVAS_TRUNK_REND_PATH} ${IVAS_TRUNK_COM_PATH} ${IVAS_TRUNK_DEBUG_PATH})
		endif()

		if (USE_PYTHON)
		find_package(Python REQUIRED COMPONENTS Development Interpreter NumPy)

		message("Python_EXECUTABLE = ${Python_EXECUTABLE}")
		@@ -37,6 +59,7 @@ endif()
		add_definitions(-DNPY_NO_DEPRECATED_API)

		include_directories(${Python_INCLUDE_DIRS} ${Python_NumPy_INCLUDE_DIRS} ${IVAS_TRUNK_UTIL_PATH} ${IVAS_TRUNK_ENC_PATH} ${IVAS_TRUNK_DEC_PATH} ${IVAS_TRUNK_REND_PATH} ${IVAS_TRUNK_COM_PATH} ${IVAS_TRUNK_DEBUG_PATH})
		endif()

		set(SOURCE_FILES_C
		${PROJECT_SOURCE_DIR}/ivas_crend_binaural_filter_design.c
		@@ -77,11 +100,22 @@ add_library(${PROJECT_NAME}_lib STATIC ${SOURCE_FILES_C} ${SOURCE_FILES_H})

		add_executable(${PROJECT_NAME} generate_crend_ivas_tables_from_sofa.c)

		if (USE_MATLAB)
		if(UNIX AND NOT APPLE)
		target_link_libraries(${PROJECT_NAME} ${PROJECT_NAME}_lib ${Matlab_MAT_LIBRARY} -lm -ldl)
		else()
		message("Matlab_MX_LIBRARY = ${Matlab_MX_LIBRARY}")
		target_link_libraries(${PROJECT_NAME} ${PROJECT_NAME}_lib ${Matlab_MAT_LIBRARY} ${Matlab_LIBRARIES} )
		endif()
		endif()

		if (USE_PYTHON)
		if(UNIX AND NOT APPLE)
		target_link_libraries(${PROJECT_NAME} ${PROJECT_NAME}_lib ${Python_LIBRARIES} -lm -ldl)
		else()
		target_link_libraries(${PROJECT_NAME} ${PROJECT_NAME}_lib ${Python_LIBRARIES})
		endif()
		endif()

		if(WIN32)
		add_compile_definitions(_CRT_SECURE_NO_WARNINGS)

scripts/binauralRenderer_interface/generate_crend_ivas_tables_from_sofa.c

+214 −24

Original line number	Diff line number	Diff line
		@@ -39,6 +39,9 @@
		#include <unistd.h>
		#define MAX_PATH PATH_MAX
		#endif
		#ifdef _WIN32
		#define _USE_MATH_DEFINES
		#endif
		#include <math.h>
		#include "options.h"
		#include "ivas_cnst.h"
		@@ -56,10 +59,14 @@
		#undef M
		#endif

		#ifdef USE_MATLAB
		#include "mat.h"
		#else
		#include <Python.h>
		#include "numpy/utils.h" // Include any other Numpy headers, UFuncs for example.
		#include "numpy/numpyconfig.h" // Include any other Numpy headers, UFuncs for example.
		#include "numpy/arrayobject.h" // Include any other Numpy headers, UFuncs for example.
		#endif

		/------------------------------------------------------------------------------------------
		* Constants
		@@ -222,6 +229,7 @@ char *h_file_path = NULL;
		char *rom_file_name = NULL;
		uint16_t frame_len_ms = 5;

		#ifndef USE_MATLAB
		PyObject *sofa_load_func = NULL;
		PyObject *sofa_find_dir_func = NULL;

		@@ -252,6 +260,7 @@ int numpy_import_array( int ret )
		return 0;
		}

		#endif
		/------------------------------------------------------------------------------------------
		* Standalone Renderer program
		*
		@@ -638,6 +647,9 @@ int main( int argc, char *argv[] )
		char *tmpstr = strstr( ivas_path, "/binauralRenderer_interface" );
		#endif
		tmpstr[0] = '\0';

		#ifndef USE_MATLAB

		Py_Initialize();

		PyObject sysPath = PySys_GetObject( (char ) "path" );
		@@ -749,7 +761,7 @@ int main( int argc, char *argv[] )
		free( binary_common_file_name );
		return -1;
		}

		#endif
		int err = 0;
		for ( ; i < argc; i++ )
		{
		@@ -849,16 +861,39 @@ int main( int argc, char *argv[] )
		if ( binary_file_path )
		free( binary_file_path );



		#ifndef USE_MATLAB
		Py_DECREF( sofa_find_dir_func );
		Py_DECREF( sofa_load_func );

		Py_Finalize();
		#endif

		return err;
		}

		int32_t find_pos_spheric( const double *Source_Position_Cartesian, int32_t numPos, const double dir_spheric[3] )
		{
		double valmax = 0;
		int32_t indmax = -1;
		int32_t ind;
		double dir_cart[3];
		double tmp;
		dir_cart[0] = ( dir_spheric[2] * cos( dir_spheric[0] * M_PI / 180. ) * cos( dir_spheric[1] * M_PI / 180. ) );
		dir_cart[1] = ( dir_spheric[2] * sin( dir_spheric[0] * M_PI / 180. ) * cos( dir_spheric[1] * M_PI / 180. ) );
		dir_cart[2] = dir_spheric[2] * sin( dir_spheric[1] * M_PI / 180. );

		for ( ind = 0; ind < numPos; ind++ )
		{
		tmp = Source_Position_Cartesian[ind * 3] * dir_cart[0] + Source_Position_Cartesian[ind * 3 + 1] * dir_cart[1] + Source_Position_Cartesian[ind * 3 + 2] * dir_cart[2];
		if ( tmp > valmax )
		{
		valmax = tmp;
		indmax = ind;
		}
		}
		return indmax;
		}

		int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader cfgReader )
		{
		char *sofa_file_path = NULL;
		@@ -867,7 +902,6 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		const char *sofaDataBaseName = "";
		const char *sofaListenerName = "";
		double *data_IR_current = NULL;
		double *sofa_data_IR_val = NULL;
		double *sofa_data_IR_val_48k = NULL;
		double *sofa_data_IR_val_32k = NULL;
		double *sofa_data_IR_val_16k = NULL;
		@@ -875,6 +909,12 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		double *sofa_delay_val = NULL;
		double *sofa_src_pos_val = NULL;
		double *sofa_src_pos_cart_val = NULL;

		long sofa_sample_rate = 0;
		double a[3] = { 0 };
		double t[3] = { 0 };
		long nearest;
		#ifndef USE_MATLAB
		PyObject *args = NULL;
		PyObject *kwargs = NULL;

		@@ -882,12 +922,9 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		PyArrayObject *sofa_data_IR = NULL;
		PyArrayObject *sofa_data_IR_48k = NULL;
		PyArrayObject *sofa_delay = NULL;
		long sofa_sample_rate = 0;
		PyArrayObject *sofa_src_pos_cart = NULL;
		PyArrayObject *dir_t = NULL;
		double a[3] = { 0 };
		double t[3] = { 0 };
		long nearest;
		#endif
		/------------------------------------------------------------------------------------------
		* Parse command line and initialize renderer
		------------------------------------------------------------------------------------------/
		@@ -900,6 +937,148 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		}
		strcpy( sofa_file_path, file_path );

		#ifdef USE_MATLAB
		MATFile *mat_fp = matOpen( sofa_file_path, "r" );
		if ( mat_fp == NULL )
		{
		printf( "Error reading existing matrix LocalDouble\n" );
		usage_gen_crend_tables();
		free( sofa_file_path );
		return -1;
		}

		mxArray *sofa = matGetVariable( mat_fp, "Sofa" );
		if ( sofa == NULL )
		{
		printf( "Error reading existing matrix LocalDouble\n" );
		usage_gen_crend_tables();
		free( sofa_file_path );
		matClose( mat_fp );
		return -1;
		}

		mwSize total_num_of_elements;
		mwIndex index = 0;
		int number_of_fields, field_index;
		const char *field_name;
		const mxArray *data;
		const double *sampleRate;

		// total_num_of_elements = mxGetNumberOfElements( sofa );
		number_of_fields = mxGetNumberOfFields( sofa );

		/* For the given index, walk through each field. */
		for ( field_index = 0; field_index < number_of_fields; field_index++ )
		{
		// display_subscript( structure_array_ptr, index );
		field_name = mxGetFieldNameByNumber( sofa,
		field_index );
		if ( strcmp( field_name, "DatabaseName" ) == 0 )
		{
		sofaDataBaseName = mxArrayToUTF8String( mxGetFieldByNumber( sofa,
		index,
		field_index ) );
		if ( sofaDataBaseName == NULL )
		{
		printf( "\tEmpty Field for %s\n", field_name );
		}
		}
		if ( strcmp( field_name, "ListenerShortName" ) == 0 )
		{
		sofaListenerName = mxArrayToUTF8String( mxGetFieldByNumber( sofa,
		index,
		field_index ) );
		if ( sofaListenerName == NULL )
		{
		printf( "\tEmpty Field for %s\n", field_name );
		}
		}
		if ( strcmp( field_name, "latencys" ) == 0 )
		{
		sofa_latencys = mxGetPr( mxGetFieldByNumber( sofa,
		index,
		field_index ) );
		if ( sofa_latencys == NULL )
		{
		printf( "\tEmpty Field for %s\n", field_name );
		}
		}
		if ( strcmp( field_name, "DataResampled" ) == 0 )
		{
		data = mxGetFieldByNumber( sofa,
		index,
		field_index );
		if ( data == NULL )
		{
		printf( "\tEmpty Field for %s\n", field_name );
		free( sofa_file_path );
		matClose( mat_fp );
		return -1;
		}

		total_num_of_elements = mxGetNumberOfElements( data );

		for ( indSR = 0; indSR < total_num_of_elements; indSR++ )
		{
		sampleRate = mxGetPr( mxGetFieldByNumber( data,
		indSR,
		1 ) );
		if ( *sampleRate == 48000 )
		{
		const mwSize *dims = mxGetDimensions( mxGetFieldByNumber( data,
		indSR,
		0 ) );
		sofa_N = sofa_N_48k = (int32_t) dims[0];
		sofa_R = (int32_t) dims[1];
		sofa_M = (int32_t) dims[2];
		sofa_data_IR_val_48k = mxGetPr( mxGetFieldByNumber( data,
		indSR,
		0 ) );
		}
		if ( *sampleRate == 32000 )
		{
		sofa_data_IR_val_32k = mxGetPr( mxGetFieldByNumber( data,
		indSR,
		0 ) );
		}
		if ( *sampleRate == 16000 )
		{
		sofa_data_IR_val_16k = mxGetPr( mxGetFieldByNumber( data,
		indSR,
		0 ) );
		}
		}
		}
		if ( strcmp( field_name, "PosCartesian" ) == 0 )
		{
		sofa_src_pos_cart_val = mxGetPr( mxGetFieldByNumber( sofa,
		index,
		field_index ) );
		if ( sofa_src_pos_cart_val == NULL )
		{
		printf( "\tEmpty Field for %s\n", field_name );
		free( sofa_file_path );
		matClose( mat_fp );
		return -1;
		}
		}
		if ( strcmp( field_name, "PosSpherical" ) == 0 )
		{
		sofa_src_pos_val = mxGetPr( mxGetFieldByNumber( sofa,
		index,
		field_index ) );
		if ( sofa_src_pos_val == NULL )
		{
		printf( "\tEmpty Field for %s\n", field_name );
		free( sofa_file_path );
		matClose( mat_fp );
		return -1;
		}
		}
		}
		// }

		#else
		int ret = PyCallable_Check( sofa_load_func );
		if ( ret )
		{
		@@ -963,6 +1142,7 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		}
		}
		}
		#endif

		struct ivas_layout_config lscfg;

		@@ -996,6 +1176,7 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		long nearest = 0;
		// int nd = 1;
		// int64_t n = 3;
		#ifndef USE_MATLAB
		npy_intp dim[1] = { 3 };

		dir_t = (PyArrayObject *) PyArray_SimpleNewFromData( 1, dim, NPY_DOUBLE, t );
		@@ -1007,13 +1188,16 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c

		return -1;
		}
		#endif
		}
		/* get index to a position given in t (in spherical) */
		int index_pos = (int ) malloc( sizeof( int ) * lscfg.nb_channel );
		uint32_t maxDel48kHz = 0;
		if ( index_pos == NULL )
		{
		#ifndef USE_MATLAB
		Py_DECREF( py_results );
		#endif
		free( sofa_file_path );
		fprintf( stderr, "Cannot alloc sofa_file_path !\n\n" );
		return -1;
		@@ -1035,16 +1219,20 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		// tmp[2] = t[2];
		// fprintf( stderr, "Wanted Position: %lf, %lf, %lf\n", t[0], t[1], t[2] );
		// fprintf( stderr, "Wanted Position: %lf, %lf, %lf\n", tmp[0], tmp[1], tmp[2] );
		#ifdef USE_MATLAB
		nearest = find_pos_spheric( sofa_src_pos_cart_val, sofa_M, t );
		#else
		py_results = PyObject_CallFunction( sofa_find_dir_func, "OO", (PyObject ) sofa_src_pos_cart, (PyObject ) dir_t );
		nearest = PyLong_AsLong( py_results );
		#endif
		if ( ( nearest >= 0 ) && ( nearest < sofa_M ) )
		{
		a[0] = sofa_src_pos_val[nearest * 3];
		a[0] = sofa_src_pos_val[nearest * 3] * 180. / M_PI;
		if ( a[0] < 0 )
		{
		a[0] += 360.;
		}
		a[1] = sofa_src_pos_val[nearest * 3 + 1];
		a[1] = sofa_src_pos_val[nearest * 3 + 1] * 180. / M_PI;
		a[2] = sofa_src_pos_val[nearest * 3 + 2];
		}

		@@ -1061,10 +1249,10 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		free( sofa_file_path );
		return -1;
		}
		if ( a[0] > 180 )
		a[0] -= 360;
		if ( a[0] < -180 )
		a[0] += 360;
		if ( a[0] > 180. )
		a[0] -= 360.;
		if ( a[0] < -180. )
		a[0] += 360.;
		fprintf( stderr, "Nearest Position: %f, %f, %f\n", a[0], a[1], a[2] );
		fprintf( stderr, "Nearest position found at: %ld\n", nearest );
		index_pos[i] = nearest;
		@@ -1077,7 +1265,6 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		uint32_t size = (uint32_t) sofa_R;
		uint32_t delL = 0, delR = 0;
		}

		size_t len_ls_cfg_name = strlen( lscfg.name );

		double latency_48k = 0;
		@@ -1261,8 +1448,7 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		}
		else
		{
		ivas_set_hrtf_fr( &hrtf_data, ivas_hrtf, frame_len
		);
		ivas_set_hrtf_fr( &hrtf_data, ivas_hrtf, frame_len );
		}
		hrtf_data.latency_s += 0.000000001f;

		@@ -1313,8 +1499,12 @@ int generate_crend_ivas_tables_from_sofa( const char file_path, ConfigReader c
		ivas_hrtf_close( &hrtf_data );
		}

		#ifdef USE_MATLAB
		matClose( mat_fp );
		#else
		Py_DECREF( args );
		Py_DECREF( py_results );
		#endif

		if ( sofa_file_path )
		free( sofa_file_path );

scripts/binauralRenderer_interface/generate_ivas_binauralizer_tables_from_sofa.m

+8 −5

Original line number	Diff line number	Diff line
		@@ -83,6 +83,9 @@ dataSpec.romOutDir = rom_path;
		Mod_Hrf_Itd_Main(dataSpec);

		%% generate crend rom or binary values
		SOFA_save_to_mat(hrir_file);
		SOFA_save_to_mat(brir_file);

		convert_SD2SHD_HRIRs(hrir_path,hrir_file_name,128);

		command = ['.' filesep() 'generate_crend_ivas_tables'];
		@@ -99,11 +102,11 @@ end

		command = [command ...
		' 5 ' ...
		hrir_file ' ' ...
		erase(hrir_file,'.sofa') '_FOA.sofa ' ...
		erase(hrir_file,'.sofa') '_HOA2.sofa ' ...
		erase(hrir_file,'.sofa') '_HOA3.sofa ' ...
		brir_file ];
		erase(hrir_file,'.sofa') '.mat ' ...
		erase(hrir_file,'.sofa') '_FOA.mat ' ...
		erase(hrir_file,'.sofa') '_HOA2.mat ' ...
		erase(hrir_file,'.sofa') '_HOA3.mat ' ...
		erase(brir_file,'.sofa') '.mat ' ];

		%display(command);

scripts/binauralRenderer_interface/matlab_hrir_generation_scripts/SOFA_save_to_mat.m

0 → 100644

+113 −0

Original line number	Diff line number	Diff line
		%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
		%
		% (C) 2022-2023 IVAS codec Public Collaboration with portions copyright Dolby International AB, Ericsson AB,
		% Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V., Huawei Technologies Co. LTD.,
		% Koninklijke Philips N.V., Nippon Telegraph and Telephone Corporation, Nokia Technologies Oy, Orange,
		% Panasonic Holdings Corporation, Qualcomm Technologies, Inc., VoiceAge Corporation, and other
		% contributors to this repository. All Rights Reserved.
		%
		% This software is protected by copyright law and by international treaties.
		% The IVAS codec Public Collaboration consisting of Dolby International AB, Ericsson AB,
		% Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V., Huawei Technologies Co. LTD.,
		% Koninklijke Philips N.V., Nippon Telegraph and Telephone Corporation, Nokia Technologies Oy, Orange,
		% Panasonic Holdings Corporation, Qualcomm Technologies, Inc., VoiceAge Corporation, and other
		% contributors to this repository retain full ownership rights in their respective contributions in
		% the software. This notice grants no license of any kind, including but not limited to patent
		% license, nor is any license granted by implication, estoppel or otherwise.
		%
		% Contributors are required to enter into the IVAS codec Public Collaboration agreement before making
		% contributions.
		%
		% This software is provided "AS IS", without any express or implied warranties. The software is in the
		% development stage. It is intended exclusively for experts who have experience with such software and
		% solely for the purpose of inspection. All implied warranties of non-infringement, merchantability
		% and fitness for a particular purpose are hereby disclaimed and excluded.
		%
		% Any dispute, controversy or claim arising under or in relation to providing this software shall be
		% submitted to and settled by the final, binding jurisdiction of the courts of Munich, Germany in
		% accordance with the laws of the Federal Republic of Germany excluding its conflict of law rules and
		% the United Nations Convention on Contracts on the International Sales of Goods.
		%
		%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

		function SOFA_save_to_mat(Lib_Name,outputSofaPath,sampleRates)
		%UNTITLED Summary of this function goes here
		% Detailed explanation goes here

		if nargin == 1
		outputSofaPath = [erase(Lib_Name,'.sofa') '.mat'];
		sampleRates = [48000 32000 16000];
		end
		if nargin == 2
		sampleRates = [48000 32000 16000];
		end

		if isfile(Lib_Name)
		if isfile(outputSofaPath)
		delete(outputSofaPath);
		end

		Sofa = struct('Sofa',struct());

		sofa_data = ncinfo(Lib_Name);
		for indVar = 1:length(sofa_data.Variables)
		if (strcmp(sofa_data.Variables(indVar).Name, 'latencys'))
		Sofa.latencys = ncread(Lib_Name,'latencys');
		end
		end

		Sofa.Pos = ncread(Lib_Name, 'SourcePosition');
		Sofa.Units = strtrim(strsplit(ncreadatt(Lib_Name, 'SourcePosition', 'Units'), ','));

		assert( any(strcmpi(Sofa.Units{1}, {'degree','radian'})), 'Unknown units');
		if strcmpi(Sofa.Units{1},'degree'), Sofa.Pos(1,:)=Sofa.Pos(1,:)*pi/180; end
		assert( any(strcmpi(Sofa.Units{2}, {'degree','radian'})), 'Unknown units');
		if strcmpi(Sofa.Units{2},'degree'), Sofa.Pos(2,:)=Sofa.Pos(2,:)*pi/180; end
		assert( any(strcmpi(Sofa.Units{3}, {'metre','meter','inch'})), 'Unknown units');
		if strcmpi(Sofa.Units{3},'inch' ), Sofa.Pos(3,:)=Sofa.Pos(3,:)*0.0254; end
		Sofa.PosSpherical = Sofa.Pos;
		Sofa.Pos = Sofa.Pos(3,:) .* ...
		[cos(Sofa.Pos(2,:)).*[cos(Sofa.Pos(1,:));sin(Sofa.Pos(1,:))];sin(Sofa.Pos(2,:))];

		Sofa.PosCartesian = make_unit_vectors(Sofa.Pos);
		NumLoc = size(Sofa.PosCartesian,2);

		% Now, get the impulse repsonses:
		Sofa.DataType = ncreadatt(Lib_Name, '/', 'DataType');
		Sofa.Data.IR = ncread(Lib_Name, 'Data.IR');
		Sofa.Data.SamplingRate = ncread(Lib_Name, 'Data.SamplingRate');
		Sofa.Data.SamplingRate_Units = ncreadatt(Lib_Name, 'Data.SamplingRate', 'Units');
		Sofa.Data.Delay = permute(ncread(Lib_Name, 'Data.Delay'), [2, 1]);
		switch lower(Sofa.DataType)
		case 'fir'
		assert( size(Sofa.Data.IR,2)>=2, 'Expecting 2 receivers (ears)');
		if size(Sofa.Data.IR,2)>2
		Sofa.Data.IR = Sofa.Data.IR(:,1:2,:);
		Sofa.Data.Delay = Sofa.Data.Delay(:,1:2);
		end
		assert( size(Sofa.Data.IR,3)==NumLoc, 'IR is incorrect size');
		assert( all(diff(Sofa.Data.Delay,1,2)==0), ...
		'Non-zero inter-aural delay offset not (yet) implemented');
		assert(strcmp(Sofa.Data.SamplingRate_Units,'hertz'), 'unknown samplerate units');
		otherwise
		error(['unknown GLOBAL_DataType = ', hrtf.GLOBAL_DataType]);
		end

		for ind = 1:length(sampleRates)
		if sampleRates(ind) == Sofa.Data.SamplingRate
		Sofa.DataResampled(ind).IR = Sofa.Data.IR;
		else
		Sofa.DataResampled(ind).IR = resample(Sofa.Data.IR, sampleRates(ind),Sofa.Data.SamplingRate, Dimension=3);
		end
		Sofa.DataResampled(ind).SamplingRate = sampleRates(ind);
		end

		Sofa.License = ncreadatt(Lib_Name,'/','License');
		Sofa.ListenerShortName = ncreadatt(Lib_Name,'/','ListenerShortName');
		Sofa.DatabaseName = ncreadatt(Lib_Name,'/','DatabaseName');
		Sofa.Title = ncreadatt(Lib_Name,'/','Title');
		Sofa.SOFAConventions = ncreadatt(Lib_Name,'/','SOFAConventions');

		save(outputSofaPath, 'Sofa');

		end
		No newline at end of file