How to use the spaudiopy.grids.gauss function in spaudiopy

"11303/6153.3 ...")
        r = requests.get('https://depositonce.tu-berlin.de/bitstream/11303/'
                         '6153.3/8/FABIAN_HRTFs_NeutralHeadOrientation.zip')
        with zipfile.ZipFile(io.BytesIO(r.content)) as zip_ref:
            zip_ref.extractall(os.path.join(current_file_dir, '../data/'))
        file = loadmat(filename)
    # CTF already compensated in DIR
    # Extracting the data is a bit ugly here...
    SamplingRate = int(file['SamplingRate'])
    SH_l = file['SH'][0][0][0]
    SH_r = file['SH'][0][0][1]
    f = np.squeeze(file['SH'][0][0][5])

    # default grid:
    if (grid_azi is None) and (grid_colat is None):
        grid_azi, grid_colat, _ = grids.gauss(35)  # grid positions

    # %% Inverse SHT
    HRTF_l = sph.inverse_sht(SH_l, grid_azi, grid_colat, 'complex')
    HRTF_r = sph.inverse_sht(SH_r, grid_azi, grid_colat, 'complex')
    assert HRTF_l.shape == HRTF_r.shape
    # %%
    hrir_l = np.fft.irfft(HRTF_l)  # creates 256 samples(t)
    hrir_r = np.fft.irfft(HRTF_r)  # creates 256 samples(t)
    assert hrir_l.shape == hrir_r.shape

    # %% Resample
    fs_target = 48000
    hrir_l_48k, hrir_r_48k, _ = process.resample_hrirs(hrir_l, hrir_r,
                                                       SamplingRate,
                                                       fs_target)
    fs_target = 96000

# %%
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import loadmat, savemat
from scipy import signal as scysignal

import soundfile as sf

from spaudiopy import plots, sph, process, utils, grids, IO


# %% Setup
N = 35  # modal order of grid
N_hrtf = 35  # modal order of HRTFs

azi, colat, weights = grids.gauss(N)  # grid positions
plt.figure()
plt.scatter(azi, colat)

# %% Load HRTF
try:
    file = loadmat(
    '../data/FABIAN_HRTF_DATABASE_V2/1 HRIRs/SphericalHarmonics/FABIAN_HRIR_measured_HATO_0.mat')
except FileNotFoundError:
    import requests, zipfile, io
    print("Downloading from http://dx.doi.org/10.14279/depositonce-5718.2...")
    r = requests.get('https://depositonce.tu-berlin.de/bitstream/11303/6153.2/18/FABIAN_HRTF_DATABASE_V2.zip')
    with zipfile.ZipFile(io.BytesIO(r.content)) as zip_ref:
        zip_ref.extractall('../data/')
    file = loadmat(
    '../data/FABIAN_HRTF_DATABASE_V2/1 HRIRs/SphericalHarmonics/FABIAN_HRIR_measured_HATO_0.mat')

Returns
    -------
    HRIRs : sig.HRIRs instance
        left : (g, h) numpy.ndarray
            h(t) for grid position g.
        right : (g, h) numpy.ndarray
            h(t) for grid position g.
        grid : (g, 2) pandas.dataframe
            [azi: azimuth, colat: colatitude] for hrirs.
        fs : int
            fs(t).

    """
    if filename == 'dummy':
        azi, colat, _ = grids.gauss(15)
        grid = pd.DataFrame({'azi': azi, 'colat': colat})
        # Create diracs as dummy
        hrir_l = np.zeros([grid.shape[0], 256])
        hrir_l[:, 0] = np.ones(hrir_l.shape[0])
        hrir_r = np.zeros_like(hrir_l)
        hrir_r[:, 0] = np.ones(hrir_r.shape[0])
        hrir_fs = fs

    elif filename is None:
        # default
        if fs not in [44100, 48000, 96000]:
            raise NotImplementedError('44100, 48000, 96000'
                                      ' default available.')
        default_file = '../data/' + 'HRTF_default_' + str(fs) + '.mat'
        current_file_dir = os.path.dirname(__file__)
        filename = os.path.join(current_file_dir, default_file)