diff --git a/python/tffpy/create_subregions.py b/python/tffpy/create_subregions.py
index 9fac82c00086c50ca5daf1552034238bd62ec37e..5b22f0ecf1581fdce0bda2c4aee5ea379f0d9d0b 100644
--- a/python/tffpy/create_subregions.py
+++ b/python/tffpy/create_subregions.py
@@ -32,7 +32,8 @@ def create_subregions(mask_bool, dgt_params, signal_params, tol,
Tolerance on sub-region distance (spectral norm of the composition
of the Gabor multipliers related to two candidate sub-regions.
fig_dir : Path
- If not None, folder where figures are stored.
+ If not None, folder where figures are stored. If None, figures are
+ not plotted.
return_norms : bool
If True, the final distance matrix is returned as a second output.
diff --git a/python/tffpy/datasets.py b/python/tffpy/datasets.py
index 9a74fd8691dd5128eb5b4a400a4bad381280dc08..13cac9fb553841826ec3ddcf858be7dee7bcb3cd 100644
--- a/python/tffpy/datasets.py
+++ b/python/tffpy/datasets.py
@@ -21,23 +21,100 @@ default_data_root_dir = get_data_path()
default_data_dir = default_data_root_dir / 'data_8000Hz_16384samples'
-def get_dataset(wav_dir=default_data_dir):
+def get_dataset():
+ """
+ Get dataset for isolated wideband and localized sources before mixing.
+
+ Returns
+ -------
+ dataset : dict
+ dataset['wideband'] (resp. dataset['localized']) is a dictionary
+ containing the :py:class:`Path` object for all the wideband
+ (resp. localized) sounds.
+ """
dataset = dict()
dataset['wideband'] = {
- x.stem: x for x in (wav_dir / 'wide_band_sources').glob('*.wav')
+ x.stem: x
+ for x in (default_data_dir / 'wide_band_sources').glob('*.wav')
}
dataset['localized'] = {
- x.stem: x for x in (wav_dir / 'localized_sources').glob('*.wav')
+ x.stem: x
+ for x in (default_data_dir / 'localized_sources').glob('*.wav')
}
return dataset
-def get_mix(loc_source, wideband_src, crop=False,
+def get_mix(loc_source, wideband_src, crop=None,
wb_to_loc_ratio_db=0, win_dur=128 / 8000, win_type='gauss',
hop_ratio=1/4, n_bins_ratio=4, n_iter_closing=2,
n_iter_opening=2, delta_mix_db=0, delta_loc_db=30,
closing_first=True, or_mask=False,
fig_dir=None, prefix=''):
+ """
+ Build the mix two sounds and the related time-frequency boolean mask.
+
+ Parameters
+ ----------
+ loc_source : Path
+ Localized sound file.
+ wideband_src : Path
+ Wideband sound file.
+ crop : int or None
+ If not None, a cropped, centered portion of the sound will be
+ extracted with the specified length, in samples.
+ wb_to_loc_ratio_db : float
+ Wideband source to localized source energy ratio to be adjusted in
+ the mix.
+ win_dur : float
+ Window duration, in seconds.
+ win_type : str
+ Window name
+ hop_ratio : float
+ Ratio of the window length that will be set as hop size for the DGT.
+ n_bins_ratio : float
+ Factor that will be applied to the window length to compute the
+ number of bins in the DGT.
+ delta_mix_db : float
+ Coefficient energy ratio, in dB, between the wideband source and the
+ localized source in the mixture in order to select coefficients in
+ the mask.
+ delta_loc_db : float
+ Dynamic range, in dB, for the localized source in order to select
+ coefficients in the mask.
+ or_mask : bool
+ If True, the mask is build by taking the union of the two masks
+ obtained using thresholds `delta_mix_db` and `delta_loc_db`. If
+ False, the intersection is taken.
+ n_iter_closing : int
+ Number of successive morphological closings with radius 1 (a.k.a.
+ radius of one single closing)
+ n_iter_opening : int
+ Number of successive morphological openings with radius 1 (a.k.a.
+ radius of one single opening)
+ closing_first : bool
+ If True, morphological closings are applied first, followed by
+ openings. If False, the reverse way is used.
+ fig_dir : Path
+ If not None, folder where figures are stored. If None, figures are
+ not plotted.
+ prefix : str
+ If not None, this prefix is used when saving the figures.
+
+ Returns
+ -------
+ x_mix : Waveform
+ Mix signal (sum of outputs `x_loc` and `x_wb`)
+ dgt_params : dict
+ DGT parameters
+ signal_params : dict
+ Signal parameters
+ mask : nd-array
+ Time-frequency binary mask
+ x_loc : Waveform
+ Localized source signal
+ x_wb : Waveform
+ Wideband source signal
+ """
dataset = get_dataset()
x_loc = Waveform.from_wavfile(dataset['localized'][loc_source])
@@ -74,18 +151,13 @@ def get_mix(loc_source, wideband_src, crop=False,
tf_mat_wb_db = db(np.abs(dgt(x_wb, dgt_params=dgt_params)))
# Build mask_raw
-
mask_mix = tf_mat_loc_db > tf_mat_wb_db + delta_mix_db
mask_loc = tf_mat_loc_db > tf_mat_loc_db.max() - delta_loc_db
- # mask_raw = np.logical_or(mask_mix, mask_loc)
- # print('AND')
if or_mask:
mask_raw = np.logical_or(mask_mix, mask_loc)
else:
mask_raw = np.logical_and(mask_mix, mask_loc)
- # x_mix = get_mix(x_source=x_loc, x_noise=x_engine)
- # print(sdr(x_loc, x_mix))
struct = generate_binary_structure(2, 1)
if n_iter_closing > 0:
@@ -103,7 +175,6 @@ def get_mix(loc_source, wideband_src, crop=False,
mask = mask_raw
- # mask_labeled, n_labels = label(mask_)
if fig_dir is not None:
fig_dir = Path(fig_dir)
fig_dir.mkdir(exist_ok=True, parents=True)
@@ -140,11 +211,6 @@ def get_mix(loc_source, wideband_src, crop=False,
plot_spectrogram(x=x_loc, dgt_params=dgt_params, fs=fs)
plt.title('Loc')
plt.subplot(235)
- # gabmul = GaborMultiplier(mask_raw=~mask,
- # dgt_params=dgt_params,
- # signal_params=signal_params)
- # x_est = gabmul @ x_loc
- # plot_spectrogram(x=x_est, dgt_params=dgt_params, fs=fs)
tf_mat = dgt(x_loc, dgt_params=dgt_params) * mask
plotdgtreal(coef=tf_mat, a=dgt_params['hop'], M=dgt_params['n_bins'],
fs=fs, dynrange=100)
@@ -160,71 +226,3 @@ def get_mix(loc_source, wideband_src, crop=False,
plt.savefig(fig_dir / '{}mix_spectro_mask.pdf'.format(prefix))
return x_mix, dgt_params, signal_params, mask, x_loc, x_wb
-
-
-if __name__ == '__main__':
- fig_dir = 'fig_bird_car'
- d = get_dataset()
- for k_dataset in d:
- print('{} files in subset {}'.format(len(d[k_dataset]), k_dataset))
- for k_file in d[k_dataset]:
- print(' - {}'.format(k_file))
-
- delta_mix_db = 0
- delta_loc_db = 30
- win_type = 'gauss'
- win_dur = 128 / 8000
- get_mix(loc_source='bird', wideband_src='car',
- win_type=win_type, win_dur=win_dur,
- n_iter_closing=2, n_iter_opening=2, delta_mix_db=delta_mix_db,
- delta_loc_db=delta_loc_db,
- closing_first=True, fig_dir=fig_dir, prefix='cl2')
- get_mix(loc_source='bird', wideband_src='car',
- win_type=win_type, win_dur=win_dur,
- n_iter_closing=1, n_iter_opening=1, delta_mix_db=delta_mix_db,
- delta_loc_db=delta_loc_db,
- closing_first=True, fig_dir=fig_dir, prefix='cl1')
- get_mix(loc_source='bird', wideband_src='car',
- win_type=win_type, win_dur=win_dur,
- n_iter_closing=2, n_iter_opening=2, delta_mix_db=delta_mix_db,
- delta_loc_db=delta_loc_db,
- closing_first=False, fig_dir=fig_dir, prefix='op2')
- get_mix(loc_source='bird', wideband_src='car',
- win_type=win_type, win_dur=win_dur,
- n_iter_closing=1, n_iter_opening=1, delta_mix_db=delta_mix_db,
- delta_loc_db=delta_loc_db,
- closing_first=False, fig_dir=fig_dir, prefix='op1')
-
- plt.figure()
- aw = plt.gca()
-
- for win_type, win_dur in [('hann', 128/8000),
- ('hann', 256/8000),
- ('gauss', 128/8000)]:
- x_mix, dgt_params, signal_params, mask_smoothed, x_loc, x_wb = \
- get_mix(loc_source='bird', wideband_src='car',
- n_iter_closing=2, n_iter_opening=2,
- delta_mix_db=delta_mix_db,
- delta_loc_db=delta_loc_db,
- closing_first=True, win_type=win_type, win_dur=win_dur,
- fig_dir=fig_dir,
- prefix='{}_{}'.format(win_type, int(win_dur * 8000)))
- gabmul = GaborMultiplier(mask=mask_smoothed,
- dgt_params=dgt_params,
- signal_params=signal_params)
- plt.sca(aw)
- gabmul.plot_win(label='{}_{}'.format(win_type, int(win_dur * 8000)))
- plt.figure()
- gabmul.plot_ambiguity_function(dynrange=6)
- plt.sca(aw)
- plt.legend()
-
- chirp_boxes = (
- ((3000, 0.47), (2100, 0.58)),
- ((3700, 0.68), (2100, 0.78)),
- ((3300, 0.88), (2100, 0.98)),
- ((3500, 1.05), (2100, 1.15)),
- ((4000, 1.25), (2300, 1.35)),
- ((3200, 1.45), (2000, 1.55))
- )
- test_boxes = ((3300, 0.1), (2100, 0.2))