Commit 9f9d024f authored by emerit's avatar emerit
Browse files

add support of sofa files at sample rate different from 48kHz and/or source... 

add support of sofa files at sample rate different from 48kHz and/or source position unit in radians
parent 23d9b857

scripts/binauralRenderer_interface/SofaReader.py

+49 −16
Original line number Diff line number Diff line
@@ -9,7 +9,7 @@ def load( 
) -> Tuple[

    str,

    str,

    np.ndarray,

    int,

    np.ndarray,

    np.ndarray,

    np.ndarray,
@@ -25,51 +25,84 @@ def load( 
    if "latencys" in hrtf.variables.keys():

        latencys = np.array(hrtf.variables["latencys"])

    Sampling_Rate = np.array(hrtf.variables["Data.SamplingRate"])

    if Sampling_Rate.size > 1:

        return (

            "",

            "",

            0,

            None,

            None,

            None,

            None,

            None,

            None,

            None,

        )

    Sampling_Rate = int(Sampling_Rate[0])

    ind_dir = 0

    Source_Position = np.array(hrtf.variables["SourcePosition"])

    unitToRad = [1.0, 1.0]

    Units = hrtf.variables["SourcePosition"].Units

    if "degree" in Units:

        unitToRad[0] = np.pi / 180

        Units = Units.replace("degree,", "", 1)

        if "degree" in Units:

            unitToRad[1] = np.pi / 180

            Units = Units.replace("degree,", "", 1)

    Source_Position_Cartesian = np.copy(Source_Position)

    for ind_dir_ptr in Source_Position:

        Source_Position_Cartesian[ind_dir][0] = (

            ind_dir_ptr[2]

            * np.cos(ind_dir_ptr[0] * np.pi / 180)

            * np.cos(ind_dir_ptr[1] * np.pi / 180)

            * np.cos(ind_dir_ptr[0] * unitToRad[0])

            * np.cos(ind_dir_ptr[1] * unitToRad[1])

        )

        Source_Position_Cartesian[ind_dir][1] = (

            ind_dir_ptr[2]

            * np.sin(ind_dir_ptr[0] * np.pi / 180)

            * np.cos(ind_dir_ptr[1] * np.pi / 180)

            * np.sin(ind_dir_ptr[0] * unitToRad[0])

            * np.cos(ind_dir_ptr[1] * unitToRad[1])

        )

        Source_Position_Cartesian[ind_dir][2] = ind_dir_ptr[2] * np.sin(

            ind_dir_ptr[1] * np.pi / 180

            ind_dir_ptr[1] * unitToRad[1]

        )

        ind_dir = ind_dir + 1

    Data_Delay = np.array(hrtf.variables["Data.Delay"])

    Data_IR_48khz = np.array(hrtf.variables["Data.IR"])

    Data_IR = np.array(hrtf.variables["Data.IR"])

    Data_IR_48khz = np.zeros(

        (

            Data_IR.shape[0],

            Data_IR.shape[1],

            int(np.ceil(Data_IR.shape[2] * 48000 / Sampling_Rate)),

        )

    )

    Data_IR_32khz = np.zeros(

        (

            Data_IR_48khz.shape[0],

            Data_IR_48khz.shape[1],

            int(np.ceil(Data_IR_48khz.shape[2] * 32 / 48)),

            Data_IR.shape[0],

            Data_IR.shape[1],

            int(np.ceil(Data_IR.shape[2] * 32000 / Sampling_Rate)),

        )

    )

    Data_IR_16khz = np.zeros(

        (

            Data_IR_48khz.shape[0],

            Data_IR_48khz.shape[1],

            int(np.ceil(Data_IR_48khz.shape[2] * 16 / 48)),

            Data_IR.shape[0],

            Data_IR.shape[1],

            int(np.ceil(Data_IR.shape[2] * 16000 / Sampling_Rate)),

        )

    )

    ind_dir = 0

    for ind_dir_ptr in Data_IR_48khz:

    for ind_dir_ptr in Data_IR:

        ind_ear = 0

        for ind_ear_ptr in ind_dir_ptr:

            tmp = np.copy(ind_ear_ptr)

            Data_IR_48khz[ind_dir][ind_ear][:] = pyaudio3dtools.audioarray.resample(

                tmp, Sampling_Rate, 48000

            )

            tmp = np.copy(ind_ear_ptr)

            Data_IR_32khz[ind_dir][ind_ear][:] = pyaudio3dtools.audioarray.resample(

                tmp, 48000, 32000

                tmp, Sampling_Rate, 32000

            )

            tmp = np.copy(ind_ear_ptr)

            Data_IR_16khz[ind_dir][ind_ear][:] = pyaudio3dtools.audioarray.resample(

                tmp, 48000, 16000

                tmp, Sampling_Rate, 16000

            )

            ind_ear = ind_ear + 1

        ind_dir = ind_dir + 1

scripts/binauralRenderer_interface/generate_crend_ivas_tables_from_sofa.c

+13 −43
Original line number Diff line number Diff line
@@ -766,7 +766,6 @@ int main( int argc, char *argv[] ) 


    getcwd( current_path, MAX_PATH );

    strcpy( ivas_path, current_path );

    strcpy( ivas_path, current_path );

#ifdef _WIN32

    char *tmpstr = strstr( ivas_path, "\\binauralRenderer_interface" );

#else
@@ -961,15 +960,14 @@ int generate_crend_ivas_tables_from_sofa( const char *file_path, bool no_optim ) 
{

    char *sofa_file_path = NULL;

    int i, indSR;

    unsigned ui;

    int32_t sofa_M, sofa_N, sofa_R, sofa_N_48k;

    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;

    double *sofa_sample_rates_val = NULL;

    double *sofa_latencys = NULL;

    double *sofa_delay_val = NULL;

    double *sofa_src_pos_val = NULL;
@@ -980,8 +978,9 @@ int generate_crend_ivas_tables_from_sofa( const char *file_path, bool no_optim ) 


    PyObject *py_results = NULL;

    PyArrayObject *sofa_data_IR = NULL;

    PyArrayObject *sofa_data_IR_48k = NULL;

    PyArrayObject *sofa_delay = NULL;

    PyArrayObject *sofa_sample_rates = NULL;

    long sofa_sample_rate = 0;

    PyArrayObject *sofa_src_pos_cart = NULL;

    PyArrayObject *dir_t = NULL;

    double a[3] = { 0 };
@@ -1036,48 +1035,19 @@ int generate_crend_ivas_tables_from_sofa( const char *file_path, bool no_optim ) 
                npy_intp *strides = NULL;

                sofaDataBaseName = PyUnicode_AsUTF8( PyTuple_GetItem( py_results, 0 ) );

                sofaListenerName = PyUnicode_AsUTF8( PyTuple_GetItem( py_results, 1 ) );

                sofa_sample_rates = (PyArrayObject *) PyTuple_GetItem( py_results, 2 );

                dims = PyArray_DIMS( sofa_sample_rates );

                sofa_sample_rates_val = (double *) PyArray_DATA( sofa_sample_rates );

                if ( dims[0] > 0 )

                {

                    int hasWantedSampleRate = 0;

                    for ( ui = 0; ui < dims[0]; ui++ )

                    {

                        if ( sofa_sample_rates_val[ui] == DEFAULT_SAMPLERATE )

                        {

                            hasWantedSampleRate = 1;

                            break;

                        }

                    }

                    if ( hasWantedSampleRate == 0 )

                    {

                        Py_DECREF( py_results );



                        fprintf( stderr, "Wrong file with wrong sample rate %s!\n\n", sofa_file_path );

                        usage_gen_crend_tables();

                        free( sofa_file_path );



                        return -1;

                    }

                }

                else

                sofa_sample_rate = PyLong_AsLong( PyTuple_GetItem( py_results, 2 ) );

                if ( sofa_sample_rate != DEFAULT_SAMPLERATE )

                {

                    Py_DECREF( py_results );



                    fprintf( stderr, "Wrong file with wrong sample rate %s!\n\n", sofa_file_path );

                    usage_gen_crend_tables();

                    free( sofa_file_path );



                    return -1;

                    fprintf( stderr, "Warning file %s with sample rate %ld resampled to 48 kHz!\n\n", sofa_file_path, sofa_sample_rate );

                    sofa_sample_rate = 48000;

                }

                sofa_latencys = (double *) PyArray_DATA( PyTuple_GetItem( py_results, 3 ) );

                sofa_delay = (PyArrayObject *) PyTuple_GetItem( py_results, 4 );

                sofa_delay_val = (double *) PyArray_DATA( sofa_delay );

                sofa_data_IR = (PyArrayObject *) PyTuple_GetItem( py_results, 5 );

                sofa_data_IR_val = (double *) PyArray_DATA( sofa_data_IR );

                dims = PyArray_DIMS( sofa_data_IR );

                strides = PyArray_STRIDES( sofa_data_IR );

                sofa_data_IR_48k = (PyArrayObject *) PyTuple_GetItem( py_results, 5 );

                sofa_data_IR_val_48k = (double *) PyArray_DATA( sofa_data_IR_48k );

                dims = PyArray_DIMS( sofa_data_IR_48k );

                strides = PyArray_STRIDES( sofa_data_IR_48k );

                sofa_M = (long) dims[0];

                sofa_R = (long) dims[1];

                sofa_N = (long) dims[2];
@@ -1376,7 +1346,7 @@ int generate_crend_ivas_tables_from_sofa( const char *file_path, bool no_optim ) 
        if ( frame_len_ms == 5 )

            frame_len = frame_len >> 2;



        data_IR_current = sofa_data_IR_val;

        data_IR_current = sofa_data_IR_val_48k;

        sofa_N = sofa_N_48k;
@@ -1443,7 +1413,7 @@ int generate_crend_ivas_tables_from_sofa( const char *file_path, bool no_optim ) 
                        sofa_N = (int32_t) ceil( 16000.f * sofa_N_48k / 48000.f );

                        break;

                    default:

                        data_IR_current = sofa_data_IR_val;

                        data_IR_current = sofa_data_IR_val_48k;

                        sofa_N = sofa_N_48k;

                        break;

                }

scripts/binauralRenderer_interface/run.py

+9 −1
Original line number Diff line number Diff line 
import os

import sys



localPath = os.getcwd()

oseperator = os.sep

localPath = localPath.replace(os.sep + "binauralRenderer_interface", "")



sys.path.append(localPath)

import SofaReader as sr

import numpy as np

import matplotlib.pyplot as plt





filename = "./HRIRs_sofa/HRIR_128_Meth5_IRC_53_Q10_symL_Itrp1_48000.sofa"

filename = "./HRIRs_sofa/HRIR_128_Meth5_IRC_53_Q10_symL_Itrp1_48000_FOA.sofa"

# filename = "./HRIRs_sofa/HRIR_128_48000_dolby_SBA3.sofa"



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