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Lots of stuff. Syncing to home.

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j-hartling
2026-03-20 16:45:54 +01:00
parent 1516fe6090
commit a276883454
28 changed files with 1106 additions and 562 deletions
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33
python/save_inv_data_log-hp.py
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@@ -3,7 +3,6 @@ import numpy as np
from thunderhopper.modeltools import load_data, save_data
from thunderhopper.filetools import crop_paths
from thunderhopper.filters import decibel, sosfilter
from thunderhopper.model import extract_env
from IPython import embed
# GENERAL SETTINGS:
@@ -12,21 +11,18 @@ data_paths = glob.glob(f'../data/processed/{target}*.npz')
save_path = '../data/inv/log_hp/'
# ANALYSIS SETTINGS:
add_noise = True
single_db_ref = True
example_scales = np.array([0, 0.1, 1, 10, 100, 200])
scales = np.geomspace(0.1, 1000, 100)
if not add_noise:
example_scales = example_scales[example_scales > 0]
add_noise = False
example_scales = np.array([0.1, 1, 10, 30, 100, 300])
scales = np.geomspace(0.1, 10000, 1000)
scales = np.unique(np.concatenate((scales, example_scales)))
# EXECUTION:
for data_path, name in zip(data_paths, crop_paths(data_paths)):
print(f'Processing {name}')
# Get song envelope:
data, config = load_data(data_path, files='env')
song, rate = data['env'], config['env_rate']
# Get filtered song (prior to envelope extraction):
data, config = load_data(data_path, files='filt')
song, rate = data['filt'], config['rate']
# Get song segment to be analyzed:
time = np.arange(song.shape[0]) / rate
@@ -40,19 +36,20 @@ for data_path, name in zip(data_paths, crop_paths(data_paths)):
mix = song[:, None] * scales[None, :]
if add_noise:
# Add normalized noise envelope:
# Add normalized envelopenoise:
rng = np.random.default_rng()
noise = rng.normal(size=song.shape)
noise = extract_env(noise, rate, config=config)
noise = rng.normal(scale=1, size=song.shape)
noise /= noise[segment].std()
mix += noise[:, None]
# Process mixture:
mix_log = decibel(mix, axis=None if single_db_ref else 0)
mix = sosfilter(np.abs(mix), rate, config['env_fcut'], 'lp',
padtype='even', padlen=config['padlen'])
mix_log = decibel(mix, ref=1)
mix_inv = sosfilter(mix_log, rate, config['inv_fcut'], 'hp',
padtype='constant', padlen=config['padlen'])
# Get "intensity measure" per stage:
# Get intensity measure per stage:
measure_env = mix[segment, :].std(axis=0)
measure_log = mix_log[segment, :].std(axis=0)
measure_inv = mix_inv[segment, :].std(axis=0)
@@ -63,9 +60,9 @@ for data_path, name in zip(data_paths, crop_paths(data_paths)):
data = dict(
scales=scales,
example_scales=example_scales,
env=mix[:, save_inds],
log=mix_log[:, save_inds],
inv=mix_inv[:, save_inds],
snip_env=mix[:, save_inds],
snip_log=mix_log[:, save_inds],
snip_inv=mix_inv[:, save_inds],
measure_env=measure_env,
measure_log=measure_log,
measure_inv=measure_inv,