add missing python files

import numpy as np

import pyaudio3dtools

from scipy import signal

from netCDF4 import Dataset

from typing import Tuple

def load(filename)-> Tuple[str, str, np.ndarray, np.ndarray, np.ndarray,np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray]:

    hrtf = Dataset(filename, "r", format="NETCDF4")

    Database_Name = hrtf.DatabaseName

    Listener_Short_Name = hrtf.ListenerShortName 

    latencys = None

    if "latencys" in hrtf.variables.keys():

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

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

    ind_dir = 0

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

    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)

        )

        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)

        )

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

            ind_dir_ptr[1] * np.pi / 180

        )

        ind_dir = ind_dir + 1

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

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

    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_16khz = np.zeros(

        (

            Data_IR_48khz.shape[0],

            Data_IR_48khz.shape[1],

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

        )

    )

    ind_dir = 0

    for ind_dir_ptr in Data_IR_48khz:

        ind_ear = 0

        for ind_ear_ptr in ind_dir_ptr:

            tmp = np.copy(ind_ear_ptr)

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

                tmp, 48000, 32000

            )

            tmp = np.copy(ind_ear_ptr)

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

                tmp,48000, 16000

            )

            ind_ear = ind_ear + 1

        ind_dir = ind_dir + 1

    return Database_Name, Listener_Short_Name, Sampling_Rate, latencys, Data_Delay, Data_IR_48khz, Data_IR_32khz, Data_IR_16khz, Source_Position, Source_Position_Cartesian

def find_pos_cart( Source_Position_Cartesian, dir_cart):

    valmax = 0

    indmax = -1

    ind_dir = 0

    for ind_dir_ptr in Source_Position_Cartesian:

        tmp = np.dot(ind_dir_ptr, dir_cart)

        if tmp > valmax:

            valmax = tmp

            indmax = ind_dir

        ind_dir = ind_dir + 1

    return indmax

def find_pos_spheric( Source_Position_Cartesian,  dir_spheric):

    valmax = 0

    indmax = -1

    ind_dir = 0

    dir_cart = np.copy(dir_spheric)

    dir_cart[0] = (

        dir_spheric[2]

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

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

    )

    dir_cart[1] = (

        dir_spheric[2]

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

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

    )

    dir_cart[2] = dir_spheric[2] * np.sin(dir_spheric[1] * np.pi / 180)

    for ind_dir_ptr in Source_Position_Cartesian:

        tmp = np.dot(ind_dir_ptr, dir_cart)

        if tmp > valmax:

            valmax = tmp

            indmax = ind_dir

        ind_dir = ind_dir + 1

    return indmax

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_48000_dolby_SBA3.sofa"

[baseName, listName, sampleRate, latency,Data_Delay, Data_IR_48khz,Data_IR_32khz,Data_IR_16khz,  srcPos, srcPosCart ] = sr.load(filename)

ind = sr.find_pos_spheric(srcPosCart, [30., 0., 2.])

y_16k = Data_IR_16khz[ind][0]

y_32k = Data_IR_32khz[ind][0]

y_48k = Data_IR_48khz[ind][0]

t_16k = np.linspace(0, y_48k.shape[0] / 48000, y_16k.shape[0], endpoint=False)

t_32k = np.linspace(0, y_48k.shape[0] / 48000, y_32k.shape[0], endpoint=False)

t_48k = np.linspace(0, y_48k.shape[0] / 48000, y_48k.shape[0], endpoint=False)

plt.plot(t_48k, y_48k, label="Signal échantillonné")

plt.plot(t_32k, y_32k, label="Signal échantillonné")

plt.plot(t_16k, y_16k, label="Signal échantillonné")

plt.grid()

plt.show()

exit

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