Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Downbeats: allow weighting of beats per bar #408

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Downbeats: allow weighting of beats per bar #408

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
31 changes: 23 additions & 8 deletions madmom/features/downbeats.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -153,6 +153,11 @@ class DBNDownBeatTrackingProcessor(Processor):
(down-)beat activation function).
fps : float, optional
Frames per second.
beats_per_bar_weights : list, optional
Weight the beats_per_bar list when choosing.
Higher numbers favour the beat number at the same index, e.g.
for beats_per_bar of [3, 4], a value here for [1, 2] will bias the
the choice towards 4 beats per bar.

References
----------
Expand Down Expand Up @@ -200,11 +205,15 @@ class DBNDownBeatTrackingProcessor(Processor):
def __init__(self, beats_per_bar, min_bpm=MIN_BPM, max_bpm=MAX_BPM,
num_tempi=NUM_TEMPI, transition_lambda=TRANSITION_LAMBDA,
observation_lambda=OBSERVATION_LAMBDA, threshold=THRESHOLD,
correct=CORRECT, fps=None, **kwargs):
correct=CORRECT, fps=None, beats_per_bar_weights=None,
**kwargs):
# pylint: disable=unused-argument
# pylint: disable=no-name-in-module
# expand arguments to arrays
beats_per_bar = np.array(beats_per_bar, ndmin=1)
beats_per_bar_weights = (np.array(beats_per_bar_weights, ndmin=1)
if beats_per_bar_weights
else np.ones(beats_per_bar.shape))
min_bpm = np.array(min_bpm, ndmin=1)
max_bpm = np.array(max_bpm, ndmin=1)
num_tempi = np.array(num_tempi, ndmin=1)
Expand All @@ -220,11 +229,14 @@ def __init__(self, beats_per_bar, min_bpm=MIN_BPM, max_bpm=MAX_BPM,
if len(transition_lambda) != len(beats_per_bar):
transition_lambda = np.repeat(transition_lambda,
len(beats_per_bar))
if not (len(min_bpm) == len(max_bpm) == len(num_tempi) ==
len(beats_per_bar) == len(transition_lambda)):
raise ValueError('`min_bpm`, `max_bpm`, `num_tempi`, `num_beats` '
'and `transition_lambda` must all have the same '
'length.')
lengths = [len(a) for a in (min_bpm, max_bpm, num_tempi, beats_per_bar,
transition_lambda, beats_per_bar_weights)]
if not sum(beats_per_bar_weights):
raise ValueError("`beats_per_bar_weights` cannot total zero")
if np.var(lengths):
raise ValueError('`min_bpm`, `max_bpm`, `num_tempi`, `num_beats`, '
'`beats_per_bar_weights` and `transition_lambda` '
'must all have the same length.')
# get num_threads from kwargs
num_threads = min(len(beats_per_bar), kwargs.get('num_threads', 1))
# init a pool of workers (if needed)
Expand All @@ -245,6 +257,7 @@ def __init__(self, beats_per_bar, min_bpm=MIN_BPM, max_bpm=MAX_BPM,
self.hmms.append(HiddenMarkovModel(tm, om))
# save variables
self.beats_per_bar = beats_per_bar
self.beats_per_bar_weights = beats_per_bar_weights
self.threshold = threshold
self.correct = correct
self.fps = fps
Expand Down Expand Up @@ -283,8 +296,10 @@ def process(self, activations, **kwargs):
# (parallel) decoding of the activations with HMM
results = list(self.map(_process_dbn, zip(self.hmms,
it.repeat(activations))))
# choose the best HMM (highest log probability)
best = np.argmax(np.asarray(results)[:, 1])
# choose the best HMM (highest log probability) after weighting
weights = self.beats_per_bar_weights
scores = np.asarray(results)[:, 1] + np.log(weights / np.sum(weights))
best = np.argmax(scores)
# the best path through the state space
path, _ = results[best]
# the state space and observation model of the best HMM
Expand Down
10 changes: 10 additions & 0 deletions tests/test_features_downbeats.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -101,6 +101,16 @@ def test_process(self):
downbeats = self.processor(sample_downbeat_act)
self.assertTrue(np.allclose(downbeats, np.empty((0, 2))))

def test_weighting_measure(self):
self.processor = DBNDownBeatTrackingProcessor(
[3, 4], fps=sample_downbeat_act.fps,
beats_per_bar_weights=[100, 1], correct=False)
downbeats = self.processor(sample_downbeat_act)
correct = np.array([[0.08, 1], [0.43, 2], [0.77, 3],
[1.11, 1], [1.45, 2], [1.79, 3],
[2.13, 1], [2.47, 2]])
self.assertTrue(np.allclose(downbeats, correct))


class TestPatternTrackingProcessorClass(unittest.TestCase):

Expand Down