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valid
beat
r'''Beat tracking evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.beat.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='beat')[0] >>> est_ann = est_jam.search(namespace='beat')[0] >>> scores = jams.eval.beat(ref_ann, est_ann)
jams/eval.py
def beat(ref, est, **kwargs): r'''Beat tracking evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.beat.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='beat')[0] >>> est_ann = est_jam.search(namespace='beat')[0] >>> scores = jams.eval.beat(ref_ann, est_ann) ''' namespace = 'beat' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_times, _ = ref.to_event_values() est_times, _ = est.to_event_values() return mir_eval.beat.evaluate(ref_times, est_times, **kwargs)
def beat(ref, est, **kwargs): r'''Beat tracking evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.beat.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='beat')[0] >>> est_ann = est_jam.search(namespace='beat')[0] >>> scores = jams.eval.beat(ref_ann, est_ann) ''' namespace = 'beat' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_times, _ = ref.to_event_values() est_times, _ = est.to_event_values() return mir_eval.beat.evaluate(ref_times, est_times, **kwargs)
[ "r", "Beat", "tracking", "evaluation" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L73-L113
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b16778399b9528efbd71434842a079f7691a7a66
valid
chord
r'''Chord evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.chord.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='chord')[0] >>> est_ann = est_jam.search(namespace='chord')[0] >>> scores = jams.eval.chord(ref_ann, est_ann)
jams/eval.py
def chord(ref, est, **kwargs): r'''Chord evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.chord.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='chord')[0] >>> est_ann = est_jam.search(namespace='chord')[0] >>> scores = jams.eval.chord(ref_ann, est_ann) ''' namespace = 'chord' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_interval, ref_value = ref.to_interval_values() est_interval, est_value = est.to_interval_values() return mir_eval.chord.evaluate(ref_interval, ref_value, est_interval, est_value, **kwargs)
def chord(ref, est, **kwargs): r'''Chord evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.chord.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='chord')[0] >>> est_ann = est_jam.search(namespace='chord')[0] >>> scores = jams.eval.chord(ref_ann, est_ann) ''' namespace = 'chord' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_interval, ref_value = ref.to_interval_values() est_interval, est_value = est.to_interval_values() return mir_eval.chord.evaluate(ref_interval, ref_value, est_interval, est_value, **kwargs)
[ "r", "Chord", "evaluation" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L158-L198
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b16778399b9528efbd71434842a079f7691a7a66
valid
hierarchy_flatten
Flatten a multi_segment annotation into mir_eval style. Parameters ---------- annotation : jams.Annotation An annotation in the `multi_segment` namespace Returns ------- hier_intervalss : list A list of lists of intervals, ordered by increasing specificity. hier_labels : list A list of lists of labels, ordered by increasing specificity.
jams/eval.py
def hierarchy_flatten(annotation): '''Flatten a multi_segment annotation into mir_eval style. Parameters ---------- annotation : jams.Annotation An annotation in the `multi_segment` namespace Returns ------- hier_intervalss : list A list of lists of intervals, ordered by increasing specificity. hier_labels : list A list of lists of labels, ordered by increasing specificity. ''' intervals, values = annotation.to_interval_values() ordering = dict() for interval, value in zip(intervals, values): level = value['level'] if level not in ordering: ordering[level] = dict(intervals=list(), labels=list()) ordering[level]['intervals'].append(interval) ordering[level]['labels'].append(value['label']) levels = sorted(list(ordering.keys())) hier_intervals = [ordering[level]['intervals'] for level in levels] hier_labels = [ordering[level]['labels'] for level in levels] return hier_intervals, hier_labels
def hierarchy_flatten(annotation): '''Flatten a multi_segment annotation into mir_eval style. Parameters ---------- annotation : jams.Annotation An annotation in the `multi_segment` namespace Returns ------- hier_intervalss : list A list of lists of intervals, ordered by increasing specificity. hier_labels : list A list of lists of labels, ordered by increasing specificity. ''' intervals, values = annotation.to_interval_values() ordering = dict() for interval, value in zip(intervals, values): level = value['level'] if level not in ordering: ordering[level] = dict(intervals=list(), labels=list()) ordering[level]['intervals'].append(interval) ordering[level]['labels'].append(value['label']) levels = sorted(list(ordering.keys())) hier_intervals = [ordering[level]['intervals'] for level in levels] hier_labels = [ordering[level]['labels'] for level in levels] return hier_intervals, hier_labels
[ "Flatten", "a", "multi_segment", "annotation", "into", "mir_eval", "style", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L243-L276
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b16778399b9528efbd71434842a079f7691a7a66
valid
hierarchy
r'''Multi-level segmentation evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.hierarchy.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='multi_segment')[0] >>> est_ann = est_jam.search(namespace='multi_segment')[0] >>> scores = jams.eval.hierarchy(ref_ann, est_ann)
jams/eval.py
def hierarchy(ref, est, **kwargs): r'''Multi-level segmentation evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.hierarchy.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='multi_segment')[0] >>> est_ann = est_jam.search(namespace='multi_segment')[0] >>> scores = jams.eval.hierarchy(ref_ann, est_ann) ''' namespace = 'multi_segment' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_hier, ref_hier_lab = hierarchy_flatten(ref) est_hier, est_hier_lab = hierarchy_flatten(est) return mir_eval.hierarchy.evaluate(ref_hier, ref_hier_lab, est_hier, est_hier_lab, **kwargs)
def hierarchy(ref, est, **kwargs): r'''Multi-level segmentation evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.hierarchy.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='multi_segment')[0] >>> est_ann = est_jam.search(namespace='multi_segment')[0] >>> scores = jams.eval.hierarchy(ref_ann, est_ann) ''' namespace = 'multi_segment' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_hier, ref_hier_lab = hierarchy_flatten(ref) est_hier, est_hier_lab = hierarchy_flatten(est) return mir_eval.hierarchy.evaluate(ref_hier, ref_hier_lab, est_hier, est_hier_lab, **kwargs)
[ "r", "Multi", "-", "level", "segmentation", "evaluation" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L279-L319
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b16778399b9528efbd71434842a079f7691a7a66
valid
tempo
r'''Tempo evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.tempo.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='tempo')[0] >>> est_ann = est_jam.search(namespace='tempo')[0] >>> scores = jams.eval.tempo(ref_ann, est_ann)
jams/eval.py
def tempo(ref, est, **kwargs): r'''Tempo evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.tempo.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='tempo')[0] >>> est_ann = est_jam.search(namespace='tempo')[0] >>> scores = jams.eval.tempo(ref_ann, est_ann) ''' ref = coerce_annotation(ref, 'tempo') est = coerce_annotation(est, 'tempo') ref_tempi = np.asarray([o.value for o in ref]) ref_weight = ref.data[0].confidence est_tempi = np.asarray([o.value for o in est]) return mir_eval.tempo.evaluate(ref_tempi, ref_weight, est_tempi, **kwargs)
def tempo(ref, est, **kwargs): r'''Tempo evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.tempo.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='tempo')[0] >>> est_ann = est_jam.search(namespace='tempo')[0] >>> scores = jams.eval.tempo(ref_ann, est_ann) ''' ref = coerce_annotation(ref, 'tempo') est = coerce_annotation(est, 'tempo') ref_tempi = np.asarray([o.value for o in ref]) ref_weight = ref.data[0].confidence est_tempi = np.asarray([o.value for o in est]) return mir_eval.tempo.evaluate(ref_tempi, ref_weight, est_tempi, **kwargs)
[ "r", "Tempo", "evaluation" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L322-L362
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b16778399b9528efbd71434842a079f7691a7a66
valid
melody
r'''Melody extraction evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.melody.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='pitch_contour')[0] >>> est_ann = est_jam.search(namespace='pitch_contour')[0] >>> scores = jams.eval.melody(ref_ann, est_ann)
jams/eval.py
def melody(ref, est, **kwargs): r'''Melody extraction evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.melody.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='pitch_contour')[0] >>> est_ann = est_jam.search(namespace='pitch_contour')[0] >>> scores = jams.eval.melody(ref_ann, est_ann) ''' namespace = 'pitch_contour' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_times, ref_p = ref.to_event_values() est_times, est_p = est.to_event_values() ref_freq = np.asarray([p['frequency'] * (-1)**(~p['voiced']) for p in ref_p]) est_freq = np.asarray([p['frequency'] * (-1)**(~p['voiced']) for p in est_p]) return mir_eval.melody.evaluate(ref_times, ref_freq, est_times, est_freq, **kwargs)
def melody(ref, est, **kwargs): r'''Melody extraction evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.melody.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='pitch_contour')[0] >>> est_ann = est_jam.search(namespace='pitch_contour')[0] >>> scores = jams.eval.melody(ref_ann, est_ann) ''' namespace = 'pitch_contour' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_times, ref_p = ref.to_event_values() est_times, est_p = est.to_event_values() ref_freq = np.asarray([p['frequency'] * (-1)**(~p['voiced']) for p in ref_p]) est_freq = np.asarray([p['frequency'] * (-1)**(~p['voiced']) for p in est_p]) return mir_eval.melody.evaluate(ref_times, ref_freq, est_times, est_freq, **kwargs)
[ "r", "Melody", "extraction", "evaluation" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L366-L411
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b16778399b9528efbd71434842a079f7691a7a66
valid
pattern_to_mireval
Convert a pattern_jku annotation object to mir_eval format. Parameters ---------- ann : jams.Annotation Must have `namespace='pattern_jku'` Returns ------- patterns : list of list of tuples - `patterns[x]` is a list containing all occurrences of pattern x - `patterns[x][y]` is a list containing all notes for occurrence y of pattern x - `patterns[x][y][z]` contains a time-note tuple `(time, midi note)`
jams/eval.py
def pattern_to_mireval(ann): '''Convert a pattern_jku annotation object to mir_eval format. Parameters ---------- ann : jams.Annotation Must have `namespace='pattern_jku'` Returns ------- patterns : list of list of tuples - `patterns[x]` is a list containing all occurrences of pattern x - `patterns[x][y]` is a list containing all notes for occurrence y of pattern x - `patterns[x][y][z]` contains a time-note tuple `(time, midi note)` ''' # It's easier to work with dictionaries, since we can't assume # sequential pattern or occurrence identifiers patterns = defaultdict(lambda: defaultdict(list)) # Iterate over the data in interval-value format for time, observation in zip(*ann.to_event_values()): pattern_id = observation['pattern_id'] occurrence_id = observation['occurrence_id'] obs = (time, observation['midi_pitch']) # Push this note observation into the correct pattern/occurrence patterns[pattern_id][occurrence_id].append(obs) # Convert to list-list-tuple format for mir_eval return [list(_.values()) for _ in six.itervalues(patterns)]
def pattern_to_mireval(ann): '''Convert a pattern_jku annotation object to mir_eval format. Parameters ---------- ann : jams.Annotation Must have `namespace='pattern_jku'` Returns ------- patterns : list of list of tuples - `patterns[x]` is a list containing all occurrences of pattern x - `patterns[x][y]` is a list containing all notes for occurrence y of pattern x - `patterns[x][y][z]` contains a time-note tuple `(time, midi note)` ''' # It's easier to work with dictionaries, since we can't assume # sequential pattern or occurrence identifiers patterns = defaultdict(lambda: defaultdict(list)) # Iterate over the data in interval-value format for time, observation in zip(*ann.to_event_values()): pattern_id = observation['pattern_id'] occurrence_id = observation['occurrence_id'] obs = (time, observation['midi_pitch']) # Push this note observation into the correct pattern/occurrence patterns[pattern_id][occurrence_id].append(obs) # Convert to list-list-tuple format for mir_eval return [list(_.values()) for _ in six.itervalues(patterns)]
[ "Convert", "a", "pattern_jku", "annotation", "object", "to", "mir_eval", "format", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L415-L452
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b16778399b9528efbd71434842a079f7691a7a66
valid
pattern
r'''Pattern detection evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.pattern.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='pattern_jku')[0] >>> est_ann = est_jam.search(namespace='pattern_jku')[0] >>> scores = jams.eval.pattern(ref_ann, est_ann)
jams/eval.py
def pattern(ref, est, **kwargs): r'''Pattern detection evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.pattern.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='pattern_jku')[0] >>> est_ann = est_jam.search(namespace='pattern_jku')[0] >>> scores = jams.eval.pattern(ref_ann, est_ann) ''' namespace = 'pattern_jku' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_patterns = pattern_to_mireval(ref) est_patterns = pattern_to_mireval(est) return mir_eval.pattern.evaluate(ref_patterns, est_patterns, **kwargs)
def pattern(ref, est, **kwargs): r'''Pattern detection evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.pattern.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations >>> ref_ann = ref_jam.search(namespace='pattern_jku')[0] >>> est_ann = est_jam.search(namespace='pattern_jku')[0] >>> scores = jams.eval.pattern(ref_ann, est_ann) ''' namespace = 'pattern_jku' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_patterns = pattern_to_mireval(ref) est_patterns = pattern_to_mireval(est) return mir_eval.pattern.evaluate(ref_patterns, est_patterns, **kwargs)
[ "r", "Pattern", "detection", "evaluation" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L455-L495
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b16778399b9528efbd71434842a079f7691a7a66
valid
transcription
r'''Note transcription evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.transcription.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations. You can use any annotation >>> # type that can be converted to pitch_contour (such as pitch_midi) >>> ref_ann = ref_jam.search(namespace='pitch_contour')[0] >>> est_ann = est_jam.search(namespace='note_hz')[0] >>> scores = jams.eval.transcription(ref_ann, est_ann)
jams/eval.py
def transcription(ref, est, **kwargs): r'''Note transcription evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.transcription.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations. You can use any annotation >>> # type that can be converted to pitch_contour (such as pitch_midi) >>> ref_ann = ref_jam.search(namespace='pitch_contour')[0] >>> est_ann = est_jam.search(namespace='note_hz')[0] >>> scores = jams.eval.transcription(ref_ann, est_ann) ''' namespace = 'pitch_contour' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_intervals, ref_p = ref.to_interval_values() est_intervals, est_p = est.to_interval_values() ref_pitches = np.asarray([p['frequency'] * (-1)**(~p['voiced']) for p in ref_p]) est_pitches = np.asarray([p['frequency'] * (-1)**(~p['voiced']) for p in est_p]) return mir_eval.transcription.evaluate( ref_intervals, ref_pitches, est_intervals, est_pitches, **kwargs)
def transcription(ref, est, **kwargs): r'''Note transcription evaluation Parameters ---------- ref : jams.Annotation Reference annotation object est : jams.Annotation Estimated annotation object kwargs Additional keyword arguments Returns ------- scores : dict Dictionary of scores, where the key is the metric name (str) and the value is the (float) score achieved. See Also -------- mir_eval.transcription.evaluate Examples -------- >>> # Load in the JAMS objects >>> ref_jam = jams.load('reference.jams') >>> est_jam = jams.load('estimated.jams') >>> # Select the first relevant annotations. You can use any annotation >>> # type that can be converted to pitch_contour (such as pitch_midi) >>> ref_ann = ref_jam.search(namespace='pitch_contour')[0] >>> est_ann = est_jam.search(namespace='note_hz')[0] >>> scores = jams.eval.transcription(ref_ann, est_ann) ''' namespace = 'pitch_contour' ref = coerce_annotation(ref, namespace) est = coerce_annotation(est, namespace) ref_intervals, ref_p = ref.to_interval_values() est_intervals, est_p = est.to_interval_values() ref_pitches = np.asarray([p['frequency'] * (-1)**(~p['voiced']) for p in ref_p]) est_pitches = np.asarray([p['frequency'] * (-1)**(~p['voiced']) for p in est_p]) return mir_eval.transcription.evaluate( ref_intervals, ref_pitches, est_intervals, est_pitches, **kwargs)
[ "r", "Note", "transcription", "evaluation" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/eval.py#L498-L542
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b16778399b9528efbd71434842a079f7691a7a66
valid
add_namespace
Add a namespace definition to our working set. Namespace files consist of partial JSON schemas defining the behavior of the `value` and `confidence` fields of an Annotation. Parameters ---------- filename : str Path to json file defining the namespace object
jams/schema.py
def add_namespace(filename): '''Add a namespace definition to our working set. Namespace files consist of partial JSON schemas defining the behavior of the `value` and `confidence` fields of an Annotation. Parameters ---------- filename : str Path to json file defining the namespace object ''' with open(filename, mode='r') as fileobj: __NAMESPACE__.update(json.load(fileobj))
def add_namespace(filename): '''Add a namespace definition to our working set. Namespace files consist of partial JSON schemas defining the behavior of the `value` and `confidence` fields of an Annotation. Parameters ---------- filename : str Path to json file defining the namespace object ''' with open(filename, mode='r') as fileobj: __NAMESPACE__.update(json.load(fileobj))
[ "Add", "a", "namespace", "definition", "to", "our", "working", "set", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schema.py#L35-L47
[ "def", "add_namespace", "(", "filename", ")", ":", "with", "open", "(", "filename", ",", "mode", "=", "'r'", ")", "as", "fileobj", ":", "__NAMESPACE__", ".", "update", "(", "json", ".", "load", "(", "fileobj", ")", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
namespace
Construct a validation schema for a given namespace. Parameters ---------- ns_key : str Namespace key identifier (eg, 'beat' or 'segment_tut') Returns ------- schema : dict JSON schema of `namespace`
jams/schema.py
def namespace(ns_key): '''Construct a validation schema for a given namespace. Parameters ---------- ns_key : str Namespace key identifier (eg, 'beat' or 'segment_tut') Returns ------- schema : dict JSON schema of `namespace` ''' if ns_key not in __NAMESPACE__: raise NamespaceError('Unknown namespace: {:s}'.format(ns_key)) sch = copy.deepcopy(JAMS_SCHEMA['definitions']['SparseObservation']) for key in ['value', 'confidence']: try: sch['properties'][key] = __NAMESPACE__[ns_key][key] except KeyError: pass return sch
def namespace(ns_key): '''Construct a validation schema for a given namespace. Parameters ---------- ns_key : str Namespace key identifier (eg, 'beat' or 'segment_tut') Returns ------- schema : dict JSON schema of `namespace` ''' if ns_key not in __NAMESPACE__: raise NamespaceError('Unknown namespace: {:s}'.format(ns_key)) sch = copy.deepcopy(JAMS_SCHEMA['definitions']['SparseObservation']) for key in ['value', 'confidence']: try: sch['properties'][key] = __NAMESPACE__[ns_key][key] except KeyError: pass return sch
[ "Construct", "a", "validation", "schema", "for", "a", "given", "namespace", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schema.py#L50-L75
[ "def", "namespace", "(", "ns_key", ")", ":", "if", "ns_key", "not", "in", "__NAMESPACE__", ":", "raise", "NamespaceError", "(", "'Unknown namespace: {:s}'", ".", "format", "(", "ns_key", ")", ")", "sch", "=", "copy", ".", "deepcopy", "(", "JAMS_SCHEMA", "[", "'definitions'", "]", "[", "'SparseObservation'", "]", ")", "for", "key", "in", "[", "'value'", ",", "'confidence'", "]", ":", "try", ":", "sch", "[", "'properties'", "]", "[", "key", "]", "=", "__NAMESPACE__", "[", "ns_key", "]", "[", "key", "]", "except", "KeyError", ":", "pass", "return", "sch" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
namespace_array
Construct a validation schema for arrays of a given namespace. Parameters ---------- ns_key : str Namespace key identifier Returns ------- schema : dict JSON schema of `namespace` observation arrays
jams/schema.py
def namespace_array(ns_key): '''Construct a validation schema for arrays of a given namespace. Parameters ---------- ns_key : str Namespace key identifier Returns ------- schema : dict JSON schema of `namespace` observation arrays ''' obs_sch = namespace(ns_key) obs_sch['title'] = 'Observation' sch = copy.deepcopy(JAMS_SCHEMA['definitions']['SparseObservationList']) sch['items'] = obs_sch return sch
def namespace_array(ns_key): '''Construct a validation schema for arrays of a given namespace. Parameters ---------- ns_key : str Namespace key identifier Returns ------- schema : dict JSON schema of `namespace` observation arrays ''' obs_sch = namespace(ns_key) obs_sch['title'] = 'Observation' sch = copy.deepcopy(JAMS_SCHEMA['definitions']['SparseObservationList']) sch['items'] = obs_sch return sch
[ "Construct", "a", "validation", "schema", "for", "arrays", "of", "a", "given", "namespace", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schema.py#L78-L97
[ "def", "namespace_array", "(", "ns_key", ")", ":", "obs_sch", "=", "namespace", "(", "ns_key", ")", "obs_sch", "[", "'title'", "]", "=", "'Observation'", "sch", "=", "copy", ".", "deepcopy", "(", "JAMS_SCHEMA", "[", "'definitions'", "]", "[", "'SparseObservationList'", "]", ")", "sch", "[", "'items'", "]", "=", "obs_sch", "return", "sch" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
values
Return the allowed values for an enumerated namespace. Parameters ---------- ns_key : str Namespace key identifier Returns ------- values : list Raises ------ NamespaceError If `ns_key` is not found, or does not have enumerated values Examples -------- >>> jams.schema.values('tag_gtzan') ['blues', 'classical', 'country', 'disco', 'hip-hop', 'jazz', 'metal', 'pop', 'reggae', 'rock']
jams/schema.py
def values(ns_key): '''Return the allowed values for an enumerated namespace. Parameters ---------- ns_key : str Namespace key identifier Returns ------- values : list Raises ------ NamespaceError If `ns_key` is not found, or does not have enumerated values Examples -------- >>> jams.schema.values('tag_gtzan') ['blues', 'classical', 'country', 'disco', 'hip-hop', 'jazz', 'metal', 'pop', 'reggae', 'rock'] ''' if ns_key not in __NAMESPACE__: raise NamespaceError('Unknown namespace: {:s}'.format(ns_key)) if 'enum' not in __NAMESPACE__[ns_key]['value']: raise NamespaceError('Namespace {:s} is not enumerated'.format(ns_key)) return copy.copy(__NAMESPACE__[ns_key]['value']['enum'])
def values(ns_key): '''Return the allowed values for an enumerated namespace. Parameters ---------- ns_key : str Namespace key identifier Returns ------- values : list Raises ------ NamespaceError If `ns_key` is not found, or does not have enumerated values Examples -------- >>> jams.schema.values('tag_gtzan') ['blues', 'classical', 'country', 'disco', 'hip-hop', 'jazz', 'metal', 'pop', 'reggae', 'rock'] ''' if ns_key not in __NAMESPACE__: raise NamespaceError('Unknown namespace: {:s}'.format(ns_key)) if 'enum' not in __NAMESPACE__[ns_key]['value']: raise NamespaceError('Namespace {:s} is not enumerated'.format(ns_key)) return copy.copy(__NAMESPACE__[ns_key]['value']['enum'])
[ "Return", "the", "allowed", "values", "for", "an", "enumerated", "namespace", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schema.py#L121-L151
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b16778399b9528efbd71434842a079f7691a7a66
valid
get_dtypes
Get the dtypes associated with the value and confidence fields for a given namespace. Parameters ---------- ns_key : str The namespace key in question Returns ------- value_dtype, confidence_dtype : numpy.dtype Type identifiers for value and confidence fields.
jams/schema.py
def get_dtypes(ns_key): '''Get the dtypes associated with the value and confidence fields for a given namespace. Parameters ---------- ns_key : str The namespace key in question Returns ------- value_dtype, confidence_dtype : numpy.dtype Type identifiers for value and confidence fields. ''' # First, get the schema if ns_key not in __NAMESPACE__: raise NamespaceError('Unknown namespace: {:s}'.format(ns_key)) value_dtype = __get_dtype(__NAMESPACE__[ns_key].get('value', {})) confidence_dtype = __get_dtype(__NAMESPACE__[ns_key].get('confidence', {})) return value_dtype, confidence_dtype
def get_dtypes(ns_key): '''Get the dtypes associated with the value and confidence fields for a given namespace. Parameters ---------- ns_key : str The namespace key in question Returns ------- value_dtype, confidence_dtype : numpy.dtype Type identifiers for value and confidence fields. ''' # First, get the schema if ns_key not in __NAMESPACE__: raise NamespaceError('Unknown namespace: {:s}'.format(ns_key)) value_dtype = __get_dtype(__NAMESPACE__[ns_key].get('value', {})) confidence_dtype = __get_dtype(__NAMESPACE__[ns_key].get('confidence', {})) return value_dtype, confidence_dtype
[ "Get", "the", "dtypes", "associated", "with", "the", "value", "and", "confidence", "fields", "for", "a", "given", "namespace", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schema.py#L154-L176
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b16778399b9528efbd71434842a079f7691a7a66
valid
list_namespaces
Print out a listing of available namespaces
jams/schema.py
def list_namespaces(): '''Print out a listing of available namespaces''' print('{:30s}\t{:40s}'.format('NAME', 'DESCRIPTION')) print('-' * 78) for sch in sorted(__NAMESPACE__): desc = __NAMESPACE__[sch]['description'] desc = (desc[:44] + '..') if len(desc) > 46 else desc print('{:30s}\t{:40s}'.format(sch, desc))
def list_namespaces(): '''Print out a listing of available namespaces''' print('{:30s}\t{:40s}'.format('NAME', 'DESCRIPTION')) print('-' * 78) for sch in sorted(__NAMESPACE__): desc = __NAMESPACE__[sch]['description'] desc = (desc[:44] + '..') if len(desc) > 46 else desc print('{:30s}\t{:40s}'.format(sch, desc))
[ "Print", "out", "a", "listing", "of", "available", "namespaces" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schema.py#L179-L186
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b16778399b9528efbd71434842a079f7691a7a66
valid
__get_dtype
Get the dtype associated with a jsonschema type definition Parameters ---------- typespec : dict The schema definition Returns ------- dtype : numpy.dtype The associated dtype
jams/schema.py
def __get_dtype(typespec): '''Get the dtype associated with a jsonschema type definition Parameters ---------- typespec : dict The schema definition Returns ------- dtype : numpy.dtype The associated dtype ''' if 'type' in typespec: return __TYPE_MAP__.get(typespec['type'], np.object_) elif 'enum' in typespec: # Enums map to objects return np.object_ elif 'oneOf' in typespec: # Recurse types = [__get_dtype(v) for v in typespec['oneOf']] # If they're not all equal, return object if all([t == types[0] for t in types]): return types[0] return np.object_
def __get_dtype(typespec): '''Get the dtype associated with a jsonschema type definition Parameters ---------- typespec : dict The schema definition Returns ------- dtype : numpy.dtype The associated dtype ''' if 'type' in typespec: return __TYPE_MAP__.get(typespec['type'], np.object_) elif 'enum' in typespec: # Enums map to objects return np.object_ elif 'oneOf' in typespec: # Recurse types = [__get_dtype(v) for v in typespec['oneOf']] # If they're not all equal, return object if all([t == types[0] for t in types]): return types[0] return np.object_
[ "Get", "the", "dtype", "associated", "with", "a", "jsonschema", "type", "definition" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schema.py#L199-L228
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b16778399b9528efbd71434842a079f7691a7a66
valid
__load_jams_schema
Load the schema file from the package.
jams/schema.py
def __load_jams_schema(): '''Load the schema file from the package.''' schema_file = os.path.join(SCHEMA_DIR, 'jams_schema.json') jams_schema = None with open(resource_filename(__name__, schema_file), mode='r') as fdesc: jams_schema = json.load(fdesc) if jams_schema is None: raise JamsError('Unable to load JAMS schema') return jams_schema
def __load_jams_schema(): '''Load the schema file from the package.''' schema_file = os.path.join(SCHEMA_DIR, 'jams_schema.json') jams_schema = None with open(resource_filename(__name__, schema_file), mode='r') as fdesc: jams_schema = json.load(fdesc) if jams_schema is None: raise JamsError('Unable to load JAMS schema') return jams_schema
[ "Load", "the", "schema", "file", "from", "the", "package", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schema.py#L231-L243
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b16778399b9528efbd71434842a079f7691a7a66
valid
import_lab
r'''Load a .lab file as an Annotation object. .lab files are assumed to have the following format: ``TIME_START\tTIME_END\tANNOTATION`` By default, .lab files are assumed to have columns separated by one or more white-space characters, and have no header or index column information. If the .lab file contains only two columns, then an empty duration field is inferred. If the .lab file contains more than three columns, each row's annotation value is assigned the contents of last non-empty column. Parameters ---------- namespace : str The namespace for the new annotation filename : str Path to the .lab file infer_duration : bool If `True`, interval durations are inferred from `(start, end)` columns, or difference between successive times. If `False`, interval durations are assumed to be explicitly coded as `(start, duration)` columns. If only one time column is given, then durations are set to 0. For instantaneous event annotations (e.g., beats or onsets), this should be set to `False`. parse_options : additional keyword arguments Passed to ``pandas.DataFrame.read_csv`` Returns ------- annotation : Annotation The newly constructed annotation object See Also -------- pandas.DataFrame.read_csv
jams/util.py
def import_lab(namespace, filename, infer_duration=True, **parse_options): r'''Load a .lab file as an Annotation object. .lab files are assumed to have the following format: ``TIME_START\tTIME_END\tANNOTATION`` By default, .lab files are assumed to have columns separated by one or more white-space characters, and have no header or index column information. If the .lab file contains only two columns, then an empty duration field is inferred. If the .lab file contains more than three columns, each row's annotation value is assigned the contents of last non-empty column. Parameters ---------- namespace : str The namespace for the new annotation filename : str Path to the .lab file infer_duration : bool If `True`, interval durations are inferred from `(start, end)` columns, or difference between successive times. If `False`, interval durations are assumed to be explicitly coded as `(start, duration)` columns. If only one time column is given, then durations are set to 0. For instantaneous event annotations (e.g., beats or onsets), this should be set to `False`. parse_options : additional keyword arguments Passed to ``pandas.DataFrame.read_csv`` Returns ------- annotation : Annotation The newly constructed annotation object See Also -------- pandas.DataFrame.read_csv ''' # Create a new annotation object annotation = core.Annotation(namespace) parse_options.setdefault('sep', r'\s+') parse_options.setdefault('engine', 'python') parse_options.setdefault('header', None) parse_options.setdefault('index_col', False) # This is a hack to handle potentially ragged .lab data parse_options.setdefault('names', range(20)) data = pd.read_csv(filename, **parse_options) # Drop all-nan columns data = data.dropna(how='all', axis=1) # Do we need to add a duration column? # This only applies to event annotations if len(data.columns) == 2: # Insert a column of zeros after the timing data.insert(1, 'duration', 0) if infer_duration: data['duration'][:-1] = data.loc[:, 0].diff()[1:].values else: # Convert from time to duration if infer_duration: data.loc[:, 1] -= data[0] for row in data.itertuples(): time, duration = row[1:3] value = [x for x in row[3:] if x is not None][-1] annotation.append(time=time, duration=duration, confidence=1.0, value=value) return annotation
def import_lab(namespace, filename, infer_duration=True, **parse_options): r'''Load a .lab file as an Annotation object. .lab files are assumed to have the following format: ``TIME_START\tTIME_END\tANNOTATION`` By default, .lab files are assumed to have columns separated by one or more white-space characters, and have no header or index column information. If the .lab file contains only two columns, then an empty duration field is inferred. If the .lab file contains more than three columns, each row's annotation value is assigned the contents of last non-empty column. Parameters ---------- namespace : str The namespace for the new annotation filename : str Path to the .lab file infer_duration : bool If `True`, interval durations are inferred from `(start, end)` columns, or difference between successive times. If `False`, interval durations are assumed to be explicitly coded as `(start, duration)` columns. If only one time column is given, then durations are set to 0. For instantaneous event annotations (e.g., beats or onsets), this should be set to `False`. parse_options : additional keyword arguments Passed to ``pandas.DataFrame.read_csv`` Returns ------- annotation : Annotation The newly constructed annotation object See Also -------- pandas.DataFrame.read_csv ''' # Create a new annotation object annotation = core.Annotation(namespace) parse_options.setdefault('sep', r'\s+') parse_options.setdefault('engine', 'python') parse_options.setdefault('header', None) parse_options.setdefault('index_col', False) # This is a hack to handle potentially ragged .lab data parse_options.setdefault('names', range(20)) data = pd.read_csv(filename, **parse_options) # Drop all-nan columns data = data.dropna(how='all', axis=1) # Do we need to add a duration column? # This only applies to event annotations if len(data.columns) == 2: # Insert a column of zeros after the timing data.insert(1, 'duration', 0) if infer_duration: data['duration'][:-1] = data.loc[:, 0].diff()[1:].values else: # Convert from time to duration if infer_duration: data.loc[:, 1] -= data[0] for row in data.itertuples(): time, duration = row[1:3] value = [x for x in row[3:] if x is not None][-1] annotation.append(time=time, duration=duration, confidence=1.0, value=value) return annotation
[ "r", "Load", "a", ".", "lab", "file", "as", "an", "Annotation", "object", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/util.py#L24-L113
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b16778399b9528efbd71434842a079f7691a7a66
valid
expand_filepaths
Expand a list of relative paths to a give base directory. Parameters ---------- base_dir : str The target base directory rel_paths : list (or list-like) Collection of relative path strings Returns ------- expanded_paths : list `rel_paths` rooted at `base_dir` Examples -------- >>> jams.util.expand_filepaths('/data', ['audio', 'beat', 'seglab']) ['/data/audio', '/data/beat', '/data/seglab']
jams/util.py
def expand_filepaths(base_dir, rel_paths): """Expand a list of relative paths to a give base directory. Parameters ---------- base_dir : str The target base directory rel_paths : list (or list-like) Collection of relative path strings Returns ------- expanded_paths : list `rel_paths` rooted at `base_dir` Examples -------- >>> jams.util.expand_filepaths('/data', ['audio', 'beat', 'seglab']) ['/data/audio', '/data/beat', '/data/seglab'] """ return [os.path.join(base_dir, os.path.normpath(rp)) for rp in rel_paths]
def expand_filepaths(base_dir, rel_paths): """Expand a list of relative paths to a give base directory. Parameters ---------- base_dir : str The target base directory rel_paths : list (or list-like) Collection of relative path strings Returns ------- expanded_paths : list `rel_paths` rooted at `base_dir` Examples -------- >>> jams.util.expand_filepaths('/data', ['audio', 'beat', 'seglab']) ['/data/audio', '/data/beat', '/data/seglab'] """ return [os.path.join(base_dir, os.path.normpath(rp)) for rp in rel_paths]
[ "Expand", "a", "list", "of", "relative", "paths", "to", "a", "give", "base", "directory", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/util.py#L116-L138
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b16778399b9528efbd71434842a079f7691a7a66
valid
smkdirs
Safely make a full directory path if it doesn't exist. Parameters ---------- dpath : str Path of directory/directories to create mode : int [default=0777] Permissions for the new directories See also -------- os.makedirs
jams/util.py
def smkdirs(dpath, mode=0o777): """Safely make a full directory path if it doesn't exist. Parameters ---------- dpath : str Path of directory/directories to create mode : int [default=0777] Permissions for the new directories See also -------- os.makedirs """ if not os.path.exists(dpath): os.makedirs(dpath, mode=mode)
def smkdirs(dpath, mode=0o777): """Safely make a full directory path if it doesn't exist. Parameters ---------- dpath : str Path of directory/directories to create mode : int [default=0777] Permissions for the new directories See also -------- os.makedirs """ if not os.path.exists(dpath): os.makedirs(dpath, mode=mode)
[ "Safely", "make", "a", "full", "directory", "path", "if", "it", "doesn", "t", "exist", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/util.py#L141-L157
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b16778399b9528efbd71434842a079f7691a7a66
valid
find_with_extension
Naive depth-search into a directory for files with a given extension. Parameters ---------- in_dir : str Path to search. ext : str File extension to match. depth : int Depth of directories to search. sort : bool Sort the list alphabetically Returns ------- matched : list Collection of matching file paths. Examples -------- >>> jams.util.find_with_extension('Audio', 'wav') ['Audio/LizNelson_Rainfall/LizNelson_Rainfall_MIX.wav', 'Audio/LizNelson_Rainfall/LizNelson_Rainfall_RAW/LizNelson_Rainfall_RAW_01_01.wav', 'Audio/LizNelson_Rainfall/LizNelson_Rainfall_RAW/LizNelson_Rainfall_RAW_02_01.wav', ... 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_02.wav', 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_03.wav', 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_04.wav']
jams/util.py
def find_with_extension(in_dir, ext, depth=3, sort=True): """Naive depth-search into a directory for files with a given extension. Parameters ---------- in_dir : str Path to search. ext : str File extension to match. depth : int Depth of directories to search. sort : bool Sort the list alphabetically Returns ------- matched : list Collection of matching file paths. Examples -------- >>> jams.util.find_with_extension('Audio', 'wav') ['Audio/LizNelson_Rainfall/LizNelson_Rainfall_MIX.wav', 'Audio/LizNelson_Rainfall/LizNelson_Rainfall_RAW/LizNelson_Rainfall_RAW_01_01.wav', 'Audio/LizNelson_Rainfall/LizNelson_Rainfall_RAW/LizNelson_Rainfall_RAW_02_01.wav', ... 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_02.wav', 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_03.wav', 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_04.wav'] """ assert depth >= 1 ext = ext.strip(os.extsep) match = list() for n in range(1, depth+1): wildcard = os.path.sep.join(["*"]*n) search_path = os.path.join(in_dir, os.extsep.join([wildcard, ext])) match += glob.glob(search_path) if sort: match.sort() return match
def find_with_extension(in_dir, ext, depth=3, sort=True): """Naive depth-search into a directory for files with a given extension. Parameters ---------- in_dir : str Path to search. ext : str File extension to match. depth : int Depth of directories to search. sort : bool Sort the list alphabetically Returns ------- matched : list Collection of matching file paths. Examples -------- >>> jams.util.find_with_extension('Audio', 'wav') ['Audio/LizNelson_Rainfall/LizNelson_Rainfall_MIX.wav', 'Audio/LizNelson_Rainfall/LizNelson_Rainfall_RAW/LizNelson_Rainfall_RAW_01_01.wav', 'Audio/LizNelson_Rainfall/LizNelson_Rainfall_RAW/LizNelson_Rainfall_RAW_02_01.wav', ... 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_02.wav', 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_03.wav', 'Audio/Phoenix_ScotchMorris/Phoenix_ScotchMorris_STEMS/Phoenix_ScotchMorris_STEM_04.wav'] """ assert depth >= 1 ext = ext.strip(os.extsep) match = list() for n in range(1, depth+1): wildcard = os.path.sep.join(["*"]*n) search_path = os.path.join(in_dir, os.extsep.join([wildcard, ext])) match += glob.glob(search_path) if sort: match.sort() return match
[ "Naive", "depth", "-", "search", "into", "a", "directory", "for", "files", "with", "a", "given", "extension", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/util.py#L182-L223
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b16778399b9528efbd71434842a079f7691a7a66
valid
get_comments
Get the metadata from a jam and an annotation, combined as a string. Parameters ---------- jam : JAMS The jams object ann : Annotation An annotation object Returns ------- comments : str The jam.file_metadata and ann.annotation_metadata, combined and serialized
scripts/jams_to_lab.py
def get_comments(jam, ann): '''Get the metadata from a jam and an annotation, combined as a string. Parameters ---------- jam : JAMS The jams object ann : Annotation An annotation object Returns ------- comments : str The jam.file_metadata and ann.annotation_metadata, combined and serialized ''' jam_comments = jam.file_metadata.__json__ ann_comments = ann.annotation_metadata.__json__ return json.dumps({'metadata': jam_comments, 'annotation metadata': ann_comments}, indent=2)
def get_comments(jam, ann): '''Get the metadata from a jam and an annotation, combined as a string. Parameters ---------- jam : JAMS The jams object ann : Annotation An annotation object Returns ------- comments : str The jam.file_metadata and ann.annotation_metadata, combined and serialized ''' jam_comments = jam.file_metadata.__json__ ann_comments = ann.annotation_metadata.__json__ return json.dumps({'metadata': jam_comments, 'annotation metadata': ann_comments}, indent=2)
[ "Get", "the", "metadata", "from", "a", "jam", "and", "an", "annotation", "combined", "as", "a", "string", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/scripts/jams_to_lab.py#L36-L56
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b16778399b9528efbd71434842a079f7691a7a66
valid
lab_dump
Save an annotation as a lab/csv. Parameters ---------- ann : Annotation The annotation object comment : str The comment string header filename : str The output filename sep : str The separator string for output comment_char : str The character used to denote comments
scripts/jams_to_lab.py
def lab_dump(ann, comment, filename, sep, comment_char): '''Save an annotation as a lab/csv. Parameters ---------- ann : Annotation The annotation object comment : str The comment string header filename : str The output filename sep : str The separator string for output comment_char : str The character used to denote comments ''' intervals, values = ann.to_interval_values() frame = pd.DataFrame(columns=['Time', 'End Time', 'Label'], data={'Time': intervals[:, 0], 'End Time': intervals[:, 1], 'Label': values}) with open(filename, 'w') as fdesc: for line in comment.split('\n'): fdesc.write('{:s} {:s}\n'.format(comment_char, line)) frame.to_csv(path_or_buf=fdesc, index=False, sep=sep)
def lab_dump(ann, comment, filename, sep, comment_char): '''Save an annotation as a lab/csv. Parameters ---------- ann : Annotation The annotation object comment : str The comment string header filename : str The output filename sep : str The separator string for output comment_char : str The character used to denote comments ''' intervals, values = ann.to_interval_values() frame = pd.DataFrame(columns=['Time', 'End Time', 'Label'], data={'Time': intervals[:, 0], 'End Time': intervals[:, 1], 'Label': values}) with open(filename, 'w') as fdesc: for line in comment.split('\n'): fdesc.write('{:s} {:s}\n'.format(comment_char, line)) frame.to_csv(path_or_buf=fdesc, index=False, sep=sep)
[ "Save", "an", "annotation", "as", "a", "lab", "/", "csv", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/scripts/jams_to_lab.py#L59-L91
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b16778399b9528efbd71434842a079f7691a7a66
valid
convert_jams
Convert jams to labs. Parameters ---------- jams_file : str The path on disk to the jams file in question output_prefix : str The file path prefix of the outputs csv : bool Whether to output in csv (True) or lab (False) format comment_char : str The character used to denote comments namespaces : list-like The set of namespace patterns to match for output
scripts/jams_to_lab.py
def convert_jams(jams_file, output_prefix, csv=False, comment_char='#', namespaces=None): '''Convert jams to labs. Parameters ---------- jams_file : str The path on disk to the jams file in question output_prefix : str The file path prefix of the outputs csv : bool Whether to output in csv (True) or lab (False) format comment_char : str The character used to denote comments namespaces : list-like The set of namespace patterns to match for output ''' if namespaces is None: raise ValueError('No namespaces provided. Try ".*" for all namespaces.') jam = jams.load(jams_file) # Get all the annotations # Filter down to the unique ones # For each annotation # generate the comment string # generate the output filename # dump to csv # Make a counter object for each namespace type counter = collections.Counter() annotations = [] for query in namespaces: annotations.extend(jam.search(namespace=query)) if csv: suffix = 'csv' sep = ',' else: suffix = 'lab' sep = '\t' for ann in annotations: index = counter[ann.namespace] counter[ann.namespace] += 1 filename = os.path.extsep.join([get_output_name(output_prefix, ann.namespace, index), suffix]) comment = get_comments(jam, ann) # Dump to disk lab_dump(ann, comment, filename, sep, comment_char)
def convert_jams(jams_file, output_prefix, csv=False, comment_char='#', namespaces=None): '''Convert jams to labs. Parameters ---------- jams_file : str The path on disk to the jams file in question output_prefix : str The file path prefix of the outputs csv : bool Whether to output in csv (True) or lab (False) format comment_char : str The character used to denote comments namespaces : list-like The set of namespace patterns to match for output ''' if namespaces is None: raise ValueError('No namespaces provided. Try ".*" for all namespaces.') jam = jams.load(jams_file) # Get all the annotations # Filter down to the unique ones # For each annotation # generate the comment string # generate the output filename # dump to csv # Make a counter object for each namespace type counter = collections.Counter() annotations = [] for query in namespaces: annotations.extend(jam.search(namespace=query)) if csv: suffix = 'csv' sep = ',' else: suffix = 'lab' sep = '\t' for ann in annotations: index = counter[ann.namespace] counter[ann.namespace] += 1 filename = os.path.extsep.join([get_output_name(output_prefix, ann.namespace, index), suffix]) comment = get_comments(jam, ann) # Dump to disk lab_dump(ann, comment, filename, sep, comment_char)
[ "Convert", "jams", "to", "labs", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/scripts/jams_to_lab.py#L94-L153
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b16778399b9528efbd71434842a079f7691a7a66
valid
parse_arguments
Parse arguments from the command line
scripts/jams_to_lab.py
def parse_arguments(args): '''Parse arguments from the command line''' parser = argparse.ArgumentParser(description='Convert JAMS to .lab files') parser.add_argument('-c', '--comma-separated', dest='csv', action='store_true', default=False, help='Output in .csv instead of .lab') parser.add_argument('--comment', dest='comment_char', type=str, default='#', help='Comment character') parser.add_argument('-n', '--namespace', dest='namespaces', nargs='+', default=['.*'], help='One or more namespaces to output. Default is all.') parser.add_argument('jams_file', help='Path to the input jams file') parser.add_argument('output_prefix', help='Prefix for output files') return vars(parser.parse_args(args))
def parse_arguments(args): '''Parse arguments from the command line''' parser = argparse.ArgumentParser(description='Convert JAMS to .lab files') parser.add_argument('-c', '--comma-separated', dest='csv', action='store_true', default=False, help='Output in .csv instead of .lab') parser.add_argument('--comment', dest='comment_char', type=str, default='#', help='Comment character') parser.add_argument('-n', '--namespace', dest='namespaces', nargs='+', default=['.*'], help='One or more namespaces to output. Default is all.') parser.add_argument('jams_file', help='Path to the input jams file') parser.add_argument('output_prefix', help='Prefix for output files') return vars(parser.parse_args(args))
[ "Parse", "arguments", "from", "the", "command", "line" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/scripts/jams_to_lab.py#L156-L182
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b16778399b9528efbd71434842a079f7691a7a66
valid
_conversion
A decorator to register namespace conversions. Usage ----- >>> @conversion('tag_open', 'tag_.*') ... def tag_to_open(annotation): ... annotation.namespace = 'tag_open' ... return annotation
jams/nsconvert.py
def _conversion(target, source): '''A decorator to register namespace conversions. Usage ----- >>> @conversion('tag_open', 'tag_.*') ... def tag_to_open(annotation): ... annotation.namespace = 'tag_open' ... return annotation ''' def register(func): '''This decorator registers func as mapping source to target''' __CONVERSION__[target][source] = func return func return register
def _conversion(target, source): '''A decorator to register namespace conversions. Usage ----- >>> @conversion('tag_open', 'tag_.*') ... def tag_to_open(annotation): ... annotation.namespace = 'tag_open' ... return annotation ''' def register(func): '''This decorator registers func as mapping source to target''' __CONVERSION__[target][source] = func return func return register
[ "A", "decorator", "to", "register", "namespace", "conversions", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/nsconvert.py#L28-L44
[ "def", "_conversion", "(", "target", ",", "source", ")", ":", "def", "register", "(", "func", ")", ":", "'''This decorator registers func as mapping source to target'''", "__CONVERSION__", "[", "target", "]", "[", "source", "]", "=", "func", "return", "func", "return", "register" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
convert
Convert a given annotation to the target namespace. Parameters ---------- annotation : jams.Annotation An annotation object target_namespace : str The target namespace Returns ------- mapped_annotation : jams.Annotation if `annotation` already belongs to `target_namespace`, then it is returned directly. otherwise, `annotation` is copied and automatically converted to the target namespace. Raises ------ SchemaError if the input annotation fails to validate NamespaceError if no conversion is possible Examples -------- Convert frequency measurements in Hz to MIDI >>> ann_midi = jams.convert(ann_hz, 'note_midi') And back to Hz >>> ann_hz2 = jams.convert(ann_midi, 'note_hz')
jams/nsconvert.py
def convert(annotation, target_namespace): '''Convert a given annotation to the target namespace. Parameters ---------- annotation : jams.Annotation An annotation object target_namespace : str The target namespace Returns ------- mapped_annotation : jams.Annotation if `annotation` already belongs to `target_namespace`, then it is returned directly. otherwise, `annotation` is copied and automatically converted to the target namespace. Raises ------ SchemaError if the input annotation fails to validate NamespaceError if no conversion is possible Examples -------- Convert frequency measurements in Hz to MIDI >>> ann_midi = jams.convert(ann_hz, 'note_midi') And back to Hz >>> ann_hz2 = jams.convert(ann_midi, 'note_hz') ''' # First, validate the input. If this fails, we can't auto-convert. annotation.validate(strict=True) # If we're already in the target namespace, do nothing if annotation.namespace == target_namespace: return annotation if target_namespace in __CONVERSION__: # Otherwise, make a copy to mangle annotation = deepcopy(annotation) # Look for a way to map this namespace to the target for source in __CONVERSION__[target_namespace]: if annotation.search(namespace=source): return __CONVERSION__[target_namespace][source](annotation) # No conversion possible raise NamespaceError('Unable to convert annotation from namespace=' '"{0}" to "{1}"'.format(annotation.namespace, target_namespace))
def convert(annotation, target_namespace): '''Convert a given annotation to the target namespace. Parameters ---------- annotation : jams.Annotation An annotation object target_namespace : str The target namespace Returns ------- mapped_annotation : jams.Annotation if `annotation` already belongs to `target_namespace`, then it is returned directly. otherwise, `annotation` is copied and automatically converted to the target namespace. Raises ------ SchemaError if the input annotation fails to validate NamespaceError if no conversion is possible Examples -------- Convert frequency measurements in Hz to MIDI >>> ann_midi = jams.convert(ann_hz, 'note_midi') And back to Hz >>> ann_hz2 = jams.convert(ann_midi, 'note_hz') ''' # First, validate the input. If this fails, we can't auto-convert. annotation.validate(strict=True) # If we're already in the target namespace, do nothing if annotation.namespace == target_namespace: return annotation if target_namespace in __CONVERSION__: # Otherwise, make a copy to mangle annotation = deepcopy(annotation) # Look for a way to map this namespace to the target for source in __CONVERSION__[target_namespace]: if annotation.search(namespace=source): return __CONVERSION__[target_namespace][source](annotation) # No conversion possible raise NamespaceError('Unable to convert annotation from namespace=' '"{0}" to "{1}"'.format(annotation.namespace, target_namespace))
[ "Convert", "a", "given", "annotation", "to", "the", "target", "namespace", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/nsconvert.py#L47-L105
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b16778399b9528efbd71434842a079f7691a7a66
valid
can_convert
Test if an annotation can be mapped to a target namespace Parameters ---------- annotation : jams.Annotation An annotation object target_namespace : str The target namespace Returns ------- True if `annotation` can be automatically converted to `target_namespace` False otherwise
jams/nsconvert.py
def can_convert(annotation, target_namespace): '''Test if an annotation can be mapped to a target namespace Parameters ---------- annotation : jams.Annotation An annotation object target_namespace : str The target namespace Returns ------- True if `annotation` can be automatically converted to `target_namespace` False otherwise ''' # If we're already in the target namespace, do nothing if annotation.namespace == target_namespace: return True if target_namespace in __CONVERSION__: # Look for a way to map this namespace to the target for source in __CONVERSION__[target_namespace]: if annotation.search(namespace=source): return True return False
def can_convert(annotation, target_namespace): '''Test if an annotation can be mapped to a target namespace Parameters ---------- annotation : jams.Annotation An annotation object target_namespace : str The target namespace Returns ------- True if `annotation` can be automatically converted to `target_namespace` False otherwise ''' # If we're already in the target namespace, do nothing if annotation.namespace == target_namespace: return True if target_namespace in __CONVERSION__: # Look for a way to map this namespace to the target for source in __CONVERSION__[target_namespace]: if annotation.search(namespace=source): return True return False
[ "Test", "if", "an", "annotation", "can", "be", "mapped", "to", "a", "target", "namespace" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/nsconvert.py#L108-L138
[ "def", "can_convert", "(", "annotation", ",", "target_namespace", ")", ":", "# If we're already in the target namespace, do nothing", "if", "annotation", ".", "namespace", "==", "target_namespace", ":", "return", "True", "if", "target_namespace", "in", "__CONVERSION__", ":", "# Look for a way to map this namespace to the target", "for", "source", "in", "__CONVERSION__", "[", "target_namespace", "]", ":", "if", "annotation", ".", "search", "(", "namespace", "=", "source", ")", ":", "return", "True", "return", "False" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
pitch_hz_to_contour
Convert a pitch_hz annotation to a contour
jams/nsconvert.py
def pitch_hz_to_contour(annotation): '''Convert a pitch_hz annotation to a contour''' annotation.namespace = 'pitch_contour' data = annotation.pop_data() for obs in data: annotation.append(time=obs.time, duration=obs.duration, confidence=obs.confidence, value=dict(index=0, frequency=np.abs(obs.value), voiced=obs.value > 0)) return annotation
def pitch_hz_to_contour(annotation): '''Convert a pitch_hz annotation to a contour''' annotation.namespace = 'pitch_contour' data = annotation.pop_data() for obs in data: annotation.append(time=obs.time, duration=obs.duration, confidence=obs.confidence, value=dict(index=0, frequency=np.abs(obs.value), voiced=obs.value > 0)) return annotation
[ "Convert", "a", "pitch_hz", "annotation", "to", "a", "contour" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/nsconvert.py#L142-L153
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b16778399b9528efbd71434842a079f7691a7a66
valid
note_hz_to_midi
Convert a pitch_hz annotation to pitch_midi
jams/nsconvert.py
def note_hz_to_midi(annotation): '''Convert a pitch_hz annotation to pitch_midi''' annotation.namespace = 'note_midi' data = annotation.pop_data() for obs in data: annotation.append(time=obs.time, duration=obs.duration, confidence=obs.confidence, value=12 * (np.log2(obs.value) - np.log2(440.0)) + 69) return annotation
def note_hz_to_midi(annotation): '''Convert a pitch_hz annotation to pitch_midi''' annotation.namespace = 'note_midi' data = annotation.pop_data() for obs in data: annotation.append(time=obs.time, duration=obs.duration, confidence=obs.confidence, value=12 * (np.log2(obs.value) - np.log2(440.0)) + 69) return annotation
[ "Convert", "a", "pitch_hz", "annotation", "to", "pitch_midi" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/nsconvert.py#L179-L191
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b16778399b9528efbd71434842a079f7691a7a66
valid
scaper_to_tag
Convert scaper annotations to tag_open
jams/nsconvert.py
def scaper_to_tag(annotation): '''Convert scaper annotations to tag_open''' annotation.namespace = 'tag_open' data = annotation.pop_data() for obs in data: annotation.append(time=obs.time, duration=obs.duration, confidence=obs.confidence, value=obs.value['label']) return annotation
def scaper_to_tag(annotation): '''Convert scaper annotations to tag_open''' annotation.namespace = 'tag_open' data = annotation.pop_data() for obs in data: annotation.append(time=obs.time, duration=obs.duration, confidence=obs.confidence, value=obs.value['label']) return annotation
[ "Convert", "scaper", "annotations", "to", "tag_open" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/nsconvert.py#L242-L252
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b16778399b9528efbd71434842a079f7691a7a66
valid
deprecated
This is a decorator which can be used to mark functions as deprecated. It will result in a warning being emitted when the function is used.
jams/core.py
def deprecated(version, version_removed): '''This is a decorator which can be used to mark functions as deprecated. It will result in a warning being emitted when the function is used.''' def __wrapper(func, *args, **kwargs): '''Warn the user, and then proceed.''' code = six.get_function_code(func) warnings.warn_explicit( "{:s}.{:s}\n\tDeprecated as of JAMS version {:s}." "\n\tIt will be removed in JAMS version {:s}." .format(func.__module__, func.__name__, version, version_removed), category=DeprecationWarning, filename=code.co_filename, lineno=code.co_firstlineno + 1 ) return func(*args, **kwargs) return decorator(__wrapper)
def deprecated(version, version_removed): '''This is a decorator which can be used to mark functions as deprecated. It will result in a warning being emitted when the function is used.''' def __wrapper(func, *args, **kwargs): '''Warn the user, and then proceed.''' code = six.get_function_code(func) warnings.warn_explicit( "{:s}.{:s}\n\tDeprecated as of JAMS version {:s}." "\n\tIt will be removed in JAMS version {:s}." .format(func.__module__, func.__name__, version, version_removed), category=DeprecationWarning, filename=code.co_filename, lineno=code.co_firstlineno + 1 ) return func(*args, **kwargs) return decorator(__wrapper)
[ "This", "is", "a", "decorator", "which", "can", "be", "used", "to", "mark", "functions", "as", "deprecated", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L63-L83
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b16778399b9528efbd71434842a079f7691a7a66
valid
_open
An intelligent wrapper for ``open``. Parameters ---------- name_or_fdesc : string-type or open file descriptor If a string type, refers to the path to a file on disk. If an open file descriptor, it is returned as-is. mode : string The mode with which to open the file. See ``open`` for details. fmt : string ['auto', 'jams', 'json', 'jamz'] The encoding for the input/output stream. If `auto`, the format is inferred from the filename extension. Otherwise, use the specified coding. See Also -------- open gzip.open
jams/core.py
def _open(name_or_fdesc, mode='r', fmt='auto'): '''An intelligent wrapper for ``open``. Parameters ---------- name_or_fdesc : string-type or open file descriptor If a string type, refers to the path to a file on disk. If an open file descriptor, it is returned as-is. mode : string The mode with which to open the file. See ``open`` for details. fmt : string ['auto', 'jams', 'json', 'jamz'] The encoding for the input/output stream. If `auto`, the format is inferred from the filename extension. Otherwise, use the specified coding. See Also -------- open gzip.open ''' open_map = {'jams': open, 'json': open, 'jamz': gzip.open, 'gz': gzip.open} # If we've been given an open descriptor, do the right thing if hasattr(name_or_fdesc, 'read') or hasattr(name_or_fdesc, 'write'): yield name_or_fdesc elif isinstance(name_or_fdesc, six.string_types): # Infer the opener from the extension if fmt == 'auto': _, ext = os.path.splitext(name_or_fdesc) # Pull off the extension separator ext = ext[1:] else: ext = fmt try: ext = ext.lower() # Force text mode if we're using gzip if ext in ['jamz', 'gz'] and 't' not in mode: mode = '{:s}t'.format(mode) with open_map[ext](name_or_fdesc, mode=mode) as fdesc: yield fdesc except KeyError: raise ParameterError('Unknown JAMS extension ' 'format: "{:s}"'.format(ext)) else: # Don't know how to handle this. Raise a parameter error raise ParameterError('Invalid filename or ' 'descriptor: {}'.format(name_or_fdesc))
def _open(name_or_fdesc, mode='r', fmt='auto'): '''An intelligent wrapper for ``open``. Parameters ---------- name_or_fdesc : string-type or open file descriptor If a string type, refers to the path to a file on disk. If an open file descriptor, it is returned as-is. mode : string The mode with which to open the file. See ``open`` for details. fmt : string ['auto', 'jams', 'json', 'jamz'] The encoding for the input/output stream. If `auto`, the format is inferred from the filename extension. Otherwise, use the specified coding. See Also -------- open gzip.open ''' open_map = {'jams': open, 'json': open, 'jamz': gzip.open, 'gz': gzip.open} # If we've been given an open descriptor, do the right thing if hasattr(name_or_fdesc, 'read') or hasattr(name_or_fdesc, 'write'): yield name_or_fdesc elif isinstance(name_or_fdesc, six.string_types): # Infer the opener from the extension if fmt == 'auto': _, ext = os.path.splitext(name_or_fdesc) # Pull off the extension separator ext = ext[1:] else: ext = fmt try: ext = ext.lower() # Force text mode if we're using gzip if ext in ['jamz', 'gz'] and 't' not in mode: mode = '{:s}t'.format(mode) with open_map[ext](name_or_fdesc, mode=mode) as fdesc: yield fdesc except KeyError: raise ParameterError('Unknown JAMS extension ' 'format: "{:s}"'.format(ext)) else: # Don't know how to handle this. Raise a parameter error raise ParameterError('Invalid filename or ' 'descriptor: {}'.format(name_or_fdesc))
[ "An", "intelligent", "wrapper", "for", "open", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L87-L152
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b16778399b9528efbd71434842a079f7691a7a66
valid
load
r"""Load a JAMS Annotation from a file. Parameters ---------- path_or_file : str or file-like Path to the JAMS file to load OR An open file handle to load from. validate : bool Attempt to validate the JAMS object strict : bool if `validate == True`, enforce strict schema validation fmt : str ['auto', 'jams', 'jamz'] The encoding format of the input If `auto`, encoding is inferred from the file name. If the input is an open file handle, `jams` encoding is used. Returns ------- jam : JAMS The loaded JAMS object Raises ------ SchemaError if `validate == True`, `strict==True`, and validation fails See also -------- JAMS.validate JAMS.save Examples -------- >>> # Load a jams object from a file name >>> J = jams.load('data.jams') >>> # Or from an open file descriptor >>> with open('data.jams', 'r') as fdesc: ... J = jams.load(fdesc) >>> # Non-strict validation >>> J = jams.load('data.jams', strict=False) >>> # No validation at all >>> J = jams.load('data.jams', validate=False)
jams/core.py
def load(path_or_file, validate=True, strict=True, fmt='auto'): r"""Load a JAMS Annotation from a file. Parameters ---------- path_or_file : str or file-like Path to the JAMS file to load OR An open file handle to load from. validate : bool Attempt to validate the JAMS object strict : bool if `validate == True`, enforce strict schema validation fmt : str ['auto', 'jams', 'jamz'] The encoding format of the input If `auto`, encoding is inferred from the file name. If the input is an open file handle, `jams` encoding is used. Returns ------- jam : JAMS The loaded JAMS object Raises ------ SchemaError if `validate == True`, `strict==True`, and validation fails See also -------- JAMS.validate JAMS.save Examples -------- >>> # Load a jams object from a file name >>> J = jams.load('data.jams') >>> # Or from an open file descriptor >>> with open('data.jams', 'r') as fdesc: ... J = jams.load(fdesc) >>> # Non-strict validation >>> J = jams.load('data.jams', strict=False) >>> # No validation at all >>> J = jams.load('data.jams', validate=False) """ with _open(path_or_file, mode='r', fmt=fmt) as fdesc: jam = JAMS(**json.load(fdesc)) if validate: jam.validate(strict=strict) return jam
def load(path_or_file, validate=True, strict=True, fmt='auto'): r"""Load a JAMS Annotation from a file. Parameters ---------- path_or_file : str or file-like Path to the JAMS file to load OR An open file handle to load from. validate : bool Attempt to validate the JAMS object strict : bool if `validate == True`, enforce strict schema validation fmt : str ['auto', 'jams', 'jamz'] The encoding format of the input If `auto`, encoding is inferred from the file name. If the input is an open file handle, `jams` encoding is used. Returns ------- jam : JAMS The loaded JAMS object Raises ------ SchemaError if `validate == True`, `strict==True`, and validation fails See also -------- JAMS.validate JAMS.save Examples -------- >>> # Load a jams object from a file name >>> J = jams.load('data.jams') >>> # Or from an open file descriptor >>> with open('data.jams', 'r') as fdesc: ... J = jams.load(fdesc) >>> # Non-strict validation >>> J = jams.load('data.jams', strict=False) >>> # No validation at all >>> J = jams.load('data.jams', validate=False) """ with _open(path_or_file, mode='r', fmt=fmt) as fdesc: jam = JAMS(**json.load(fdesc)) if validate: jam.validate(strict=strict) return jam
[ "r", "Load", "a", "JAMS", "Annotation", "from", "a", "file", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L155-L218
[ "def", "load", "(", "path_or_file", ",", "validate", "=", "True", ",", "strict", "=", "True", ",", "fmt", "=", "'auto'", ")", ":", "with", "_open", "(", "path_or_file", ",", "mode", "=", "'r'", ",", "fmt", "=", "fmt", ")", "as", "fdesc", ":", "jam", "=", "JAMS", "(", "*", "*", "json", ".", "load", "(", "fdesc", ")", ")", "if", "validate", ":", "jam", ".", "validate", "(", "strict", "=", "strict", ")", "return", "jam" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
query_pop
Pop a prefix from a query string. Parameters ---------- query : str The query string prefix : str The prefix string to pop, if it exists sep : str The string to separate fields Returns ------- popped : str `query` with a `prefix` removed from the front (if found) or `query` if the prefix was not found Examples -------- >>> query_pop('Annotation.namespace', 'Annotation') 'namespace' >>> query_pop('namespace', 'Annotation') 'namespace'
jams/core.py
def query_pop(query, prefix, sep='.'): '''Pop a prefix from a query string. Parameters ---------- query : str The query string prefix : str The prefix string to pop, if it exists sep : str The string to separate fields Returns ------- popped : str `query` with a `prefix` removed from the front (if found) or `query` if the prefix was not found Examples -------- >>> query_pop('Annotation.namespace', 'Annotation') 'namespace' >>> query_pop('namespace', 'Annotation') 'namespace' ''' terms = query.split(sep) if terms[0] == prefix: terms = terms[1:] return sep.join(terms)
def query_pop(query, prefix, sep='.'): '''Pop a prefix from a query string. Parameters ---------- query : str The query string prefix : str The prefix string to pop, if it exists sep : str The string to separate fields Returns ------- popped : str `query` with a `prefix` removed from the front (if found) or `query` if the prefix was not found Examples -------- >>> query_pop('Annotation.namespace', 'Annotation') 'namespace' >>> query_pop('namespace', 'Annotation') 'namespace' ''' terms = query.split(sep) if terms[0] == prefix: terms = terms[1:] return sep.join(terms)
[ "Pop", "a", "prefix", "from", "a", "query", "string", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L2009-L2044
[ "def", "query_pop", "(", "query", ",", "prefix", ",", "sep", "=", "'.'", ")", ":", "terms", "=", "query", ".", "split", "(", "sep", ")", "if", "terms", "[", "0", "]", "==", "prefix", ":", "terms", "=", "terms", "[", "1", ":", "]", "return", "sep", ".", "join", "(", "terms", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
match_query
Test if a string matches a query. Parameters ---------- string : str The string to test query : string, callable, or object Either a regular expression, callable function, or object. Returns ------- match : bool `True` if: - `query` is a callable and `query(string) == True` - `query` is a regular expression and `re.match(query, string)` - or `string == query` for any other query `False` otherwise
jams/core.py
def match_query(string, query): '''Test if a string matches a query. Parameters ---------- string : str The string to test query : string, callable, or object Either a regular expression, callable function, or object. Returns ------- match : bool `True` if: - `query` is a callable and `query(string) == True` - `query` is a regular expression and `re.match(query, string)` - or `string == query` for any other query `False` otherwise ''' if six.callable(query): return query(string) elif (isinstance(query, six.string_types) and isinstance(string, six.string_types)): return re.match(query, string) is not None else: return query == string
def match_query(string, query): '''Test if a string matches a query. Parameters ---------- string : str The string to test query : string, callable, or object Either a regular expression, callable function, or object. Returns ------- match : bool `True` if: - `query` is a callable and `query(string) == True` - `query` is a regular expression and `re.match(query, string)` - or `string == query` for any other query `False` otherwise ''' if six.callable(query): return query(string) elif (isinstance(query, six.string_types) and isinstance(string, six.string_types)): return re.match(query, string) is not None else: return query == string
[ "Test", "if", "a", "string", "matches", "a", "query", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L2047-L2078
[ "def", "match_query", "(", "string", ",", "query", ")", ":", "if", "six", ".", "callable", "(", "query", ")", ":", "return", "query", "(", "string", ")", "elif", "(", "isinstance", "(", "query", ",", "six", ".", "string_types", ")", "and", "isinstance", "(", "string", ",", "six", ".", "string_types", ")", ")", ":", "return", "re", ".", "match", "(", "query", ",", "string", ")", "is", "not", "None", "else", ":", "return", "query", "==", "string" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
serialize_obj
Custom serialization functionality for working with advanced data types. - numpy arrays are converted to lists - lists are recursively serialized element-wise
jams/core.py
def serialize_obj(obj): '''Custom serialization functionality for working with advanced data types. - numpy arrays are converted to lists - lists are recursively serialized element-wise ''' if isinstance(obj, np.integer): return int(obj) elif isinstance(obj, np.floating): return float(obj) elif isinstance(obj, np.ndarray): return obj.tolist() elif isinstance(obj, list): return [serialize_obj(x) for x in obj] elif isinstance(obj, Observation): return {k: serialize_obj(v) for k, v in six.iteritems(obj._asdict())} return obj
def serialize_obj(obj): '''Custom serialization functionality for working with advanced data types. - numpy arrays are converted to lists - lists are recursively serialized element-wise ''' if isinstance(obj, np.integer): return int(obj) elif isinstance(obj, np.floating): return float(obj) elif isinstance(obj, np.ndarray): return obj.tolist() elif isinstance(obj, list): return [serialize_obj(x) for x in obj] elif isinstance(obj, Observation): return {k: serialize_obj(v) for k, v in six.iteritems(obj._asdict())} return obj
[ "Custom", "serialization", "functionality", "for", "working", "with", "advanced", "data", "types", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L2081-L2104
[ "def", "serialize_obj", "(", "obj", ")", ":", "if", "isinstance", "(", "obj", ",", "np", ".", "integer", ")", ":", "return", "int", "(", "obj", ")", "elif", "isinstance", "(", "obj", ",", "np", ".", "floating", ")", ":", "return", "float", "(", "obj", ")", "elif", "isinstance", "(", "obj", ",", "np", ".", "ndarray", ")", ":", "return", "obj", ".", "tolist", "(", ")", "elif", "isinstance", "(", "obj", ",", "list", ")", ":", "return", "[", "serialize_obj", "(", "x", ")", "for", "x", "in", "obj", "]", "elif", "isinstance", "(", "obj", ",", "Observation", ")", ":", "return", "{", "k", ":", "serialize_obj", "(", "v", ")", "for", "k", ",", "v", "in", "six", ".", "iteritems", "(", "obj", ".", "_asdict", "(", ")", ")", "}", "return", "obj" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
summary
Helper function to format repr strings for JObjects and friends. Parameters ---------- obj The object to repr indent : int >= 0 indent each new line by `indent` spaces Returns ------- r : str If `obj` has a `__summary__` method, it is used. If `obj` is a `SortedKeyList`, then it returns a description of the length of the list. Otherwise, `repr(obj)`.
jams/core.py
def summary(obj, indent=0): '''Helper function to format repr strings for JObjects and friends. Parameters ---------- obj The object to repr indent : int >= 0 indent each new line by `indent` spaces Returns ------- r : str If `obj` has a `__summary__` method, it is used. If `obj` is a `SortedKeyList`, then it returns a description of the length of the list. Otherwise, `repr(obj)`. ''' if hasattr(obj, '__summary__'): rep = obj.__summary__() elif isinstance(obj, SortedKeyList): rep = '<{:d} observations>'.format(len(obj)) else: rep = repr(obj) return rep.replace('\n', '\n' + ' ' * indent)
def summary(obj, indent=0): '''Helper function to format repr strings for JObjects and friends. Parameters ---------- obj The object to repr indent : int >= 0 indent each new line by `indent` spaces Returns ------- r : str If `obj` has a `__summary__` method, it is used. If `obj` is a `SortedKeyList`, then it returns a description of the length of the list. Otherwise, `repr(obj)`. ''' if hasattr(obj, '__summary__'): rep = obj.__summary__() elif isinstance(obj, SortedKeyList): rep = '<{:d} observations>'.format(len(obj)) else: rep = repr(obj) return rep.replace('\n', '\n' + ' ' * indent)
[ "Helper", "function", "to", "format", "repr", "strings", "for", "JObjects", "and", "friends", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L2107-L2135
[ "def", "summary", "(", "obj", ",", "indent", "=", "0", ")", ":", "if", "hasattr", "(", "obj", ",", "'__summary__'", ")", ":", "rep", "=", "obj", ".", "__summary__", "(", ")", "elif", "isinstance", "(", "obj", ",", "SortedKeyList", ")", ":", "rep", "=", "'<{:d} observations>'", ".", "format", "(", "len", "(", "obj", ")", ")", "else", ":", "rep", "=", "repr", "(", "obj", ")", "return", "rep", ".", "replace", "(", "'\\n'", ",", "'\\n'", "+", "' '", "*", "indent", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
JObject.update
Update the attributes of a JObject. Parameters ---------- kwargs Keyword arguments of the form `attribute=new_value` Examples -------- >>> J = jams.JObject(foo=5) >>> J.dumps() '{"foo": 5}' >>> J.update(bar='baz') >>> J.dumps() '{"foo": 5, "bar": "baz"}'
jams/core.py
def update(self, **kwargs): '''Update the attributes of a JObject. Parameters ---------- kwargs Keyword arguments of the form `attribute=new_value` Examples -------- >>> J = jams.JObject(foo=5) >>> J.dumps() '{"foo": 5}' >>> J.update(bar='baz') >>> J.dumps() '{"foo": 5, "bar": "baz"}' ''' for name, value in six.iteritems(kwargs): setattr(self, name, value)
def update(self, **kwargs): '''Update the attributes of a JObject. Parameters ---------- kwargs Keyword arguments of the form `attribute=new_value` Examples -------- >>> J = jams.JObject(foo=5) >>> J.dumps() '{"foo": 5}' >>> J.update(bar='baz') >>> J.dumps() '{"foo": 5, "bar": "baz"}' ''' for name, value in six.iteritems(kwargs): setattr(self, name, value)
[ "Update", "the", "attributes", "of", "a", "JObject", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L436-L454
[ "def", "update", "(", "self", ",", "*", "*", "kwargs", ")", ":", "for", "name", ",", "value", "in", "six", ".", "iteritems", "(", "kwargs", ")", ":", "setattr", "(", "self", ",", "name", ",", "value", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
JObject.search
Query this object (and its descendants). Parameters ---------- kwargs Each `(key, value)` pair encodes a search field in `key` and a target value in `value`. `key` must be a string, and should correspond to a property in the JAMS object hierarchy, e.g., 'Annotation.namespace` or `email` `value` must be either an object (tested for equality), a string describing a search pattern (regular expression), or a lambda function which evaluates to `True` if the candidate object matches the search criteria and `False` otherwise. Returns ------- match : bool `True` if any of the search keys match the specified value, `False` otherwise, or if the search keys do not exist within the object. Examples -------- >>> J = jams.JObject(foo=5, needle='quick brown fox') >>> J.search(needle='.*brown.*') True >>> J.search(needle='.*orange.*') False >>> J.search(badger='.*brown.*') False >>> J.search(foo=5) True >>> J.search(foo=10) False >>> J.search(foo=lambda x: x < 10) True >>> J.search(foo=lambda x: x > 10) False
jams/core.py
def search(self, **kwargs): '''Query this object (and its descendants). Parameters ---------- kwargs Each `(key, value)` pair encodes a search field in `key` and a target value in `value`. `key` must be a string, and should correspond to a property in the JAMS object hierarchy, e.g., 'Annotation.namespace` or `email` `value` must be either an object (tested for equality), a string describing a search pattern (regular expression), or a lambda function which evaluates to `True` if the candidate object matches the search criteria and `False` otherwise. Returns ------- match : bool `True` if any of the search keys match the specified value, `False` otherwise, or if the search keys do not exist within the object. Examples -------- >>> J = jams.JObject(foo=5, needle='quick brown fox') >>> J.search(needle='.*brown.*') True >>> J.search(needle='.*orange.*') False >>> J.search(badger='.*brown.*') False >>> J.search(foo=5) True >>> J.search(foo=10) False >>> J.search(foo=lambda x: x < 10) True >>> J.search(foo=lambda x: x > 10) False ''' match = False r_query = {} myself = self.__class__.__name__ # Pop this object name off the query for k, value in six.iteritems(kwargs): k_pop = query_pop(k, myself) if k_pop: r_query[k_pop] = value if not r_query: return False for key in r_query: if hasattr(self, key): match |= match_query(getattr(self, key), r_query[key]) if not match: for attr in dir(self): obj = getattr(self, attr) if isinstance(obj, JObject): match |= obj.search(**r_query) return match
def search(self, **kwargs): '''Query this object (and its descendants). Parameters ---------- kwargs Each `(key, value)` pair encodes a search field in `key` and a target value in `value`. `key` must be a string, and should correspond to a property in the JAMS object hierarchy, e.g., 'Annotation.namespace` or `email` `value` must be either an object (tested for equality), a string describing a search pattern (regular expression), or a lambda function which evaluates to `True` if the candidate object matches the search criteria and `False` otherwise. Returns ------- match : bool `True` if any of the search keys match the specified value, `False` otherwise, or if the search keys do not exist within the object. Examples -------- >>> J = jams.JObject(foo=5, needle='quick brown fox') >>> J.search(needle='.*brown.*') True >>> J.search(needle='.*orange.*') False >>> J.search(badger='.*brown.*') False >>> J.search(foo=5) True >>> J.search(foo=10) False >>> J.search(foo=lambda x: x < 10) True >>> J.search(foo=lambda x: x > 10) False ''' match = False r_query = {} myself = self.__class__.__name__ # Pop this object name off the query for k, value in six.iteritems(kwargs): k_pop = query_pop(k, myself) if k_pop: r_query[k_pop] = value if not r_query: return False for key in r_query: if hasattr(self, key): match |= match_query(getattr(self, key), r_query[key]) if not match: for attr in dir(self): obj = getattr(self, attr) if isinstance(obj, JObject): match |= obj.search(**r_query) return match
[ "Query", "this", "object", "(", "and", "its", "descendants", ")", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L490-L559
[ "def", "search", "(", "self", ",", "*", "*", "kwargs", ")", ":", "match", "=", "False", "r_query", "=", "{", "}", "myself", "=", "self", ".", "__class__", ".", "__name__", "# Pop this object name off the query", "for", "k", ",", "value", "in", "six", ".", "iteritems", "(", "kwargs", ")", ":", "k_pop", "=", "query_pop", "(", "k", ",", "myself", ")", "if", "k_pop", ":", "r_query", "[", "k_pop", "]", "=", "value", "if", "not", "r_query", ":", "return", "False", "for", "key", "in", "r_query", ":", "if", "hasattr", "(", "self", ",", "key", ")", ":", "match", "|=", "match_query", "(", "getattr", "(", "self", ",", "key", ")", ",", "r_query", "[", "key", "]", ")", "if", "not", "match", ":", "for", "attr", "in", "dir", "(", "self", ")", ":", "obj", "=", "getattr", "(", "self", ",", "attr", ")", "if", "isinstance", "(", "obj", ",", "JObject", ")", ":", "match", "|=", "obj", ".", "search", "(", "*", "*", "r_query", ")", "return", "match" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
JObject.validate
Validate a JObject against its schema Parameters ---------- strict : bool Enforce strict schema validation Returns ------- valid : bool True if the jam validates False if not, and `strict==False` Raises ------ SchemaError If `strict==True` and `jam` fails validation
jams/core.py
def validate(self, strict=True): '''Validate a JObject against its schema Parameters ---------- strict : bool Enforce strict schema validation Returns ------- valid : bool True if the jam validates False if not, and `strict==False` Raises ------ SchemaError If `strict==True` and `jam` fails validation ''' valid = True try: jsonschema.validate(self.__json__, self.__schema__) except jsonschema.ValidationError as invalid: if strict: raise SchemaError(str(invalid)) else: warnings.warn(str(invalid)) valid = False return valid
def validate(self, strict=True): '''Validate a JObject against its schema Parameters ---------- strict : bool Enforce strict schema validation Returns ------- valid : bool True if the jam validates False if not, and `strict==False` Raises ------ SchemaError If `strict==True` and `jam` fails validation ''' valid = True try: jsonschema.validate(self.__json__, self.__schema__) except jsonschema.ValidationError as invalid: if strict: raise SchemaError(str(invalid)) else: warnings.warn(str(invalid)) valid = False return valid
[ "Validate", "a", "JObject", "against", "its", "schema" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L561-L594
[ "def", "validate", "(", "self", ",", "strict", "=", "True", ")", ":", "valid", "=", "True", "try", ":", "jsonschema", ".", "validate", "(", "self", ".", "__json__", ",", "self", ".", "__schema__", ")", "except", "jsonschema", ".", "ValidationError", "as", "invalid", ":", "if", "strict", ":", "raise", "SchemaError", "(", "str", "(", "invalid", ")", ")", "else", ":", "warnings", ".", "warn", "(", "str", "(", "invalid", ")", ")", "valid", "=", "False", "return", "valid" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.append
Append an observation to the data field Parameters ---------- time : float >= 0 duration : float >= 0 The time and duration of the new observation, in seconds value confidence The value and confidence of the new observations. Types and values should conform to the namespace of the Annotation object. Examples -------- >>> ann = jams.Annotation(namespace='chord') >>> ann.append(time=3, duration=2, value='E#')
jams/core.py
def append(self, time=None, duration=None, value=None, confidence=None): '''Append an observation to the data field Parameters ---------- time : float >= 0 duration : float >= 0 The time and duration of the new observation, in seconds value confidence The value and confidence of the new observations. Types and values should conform to the namespace of the Annotation object. Examples -------- >>> ann = jams.Annotation(namespace='chord') >>> ann.append(time=3, duration=2, value='E#') ''' self.data.add(Observation(time=float(time), duration=float(duration), value=value, confidence=confidence))
def append(self, time=None, duration=None, value=None, confidence=None): '''Append an observation to the data field Parameters ---------- time : float >= 0 duration : float >= 0 The time and duration of the new observation, in seconds value confidence The value and confidence of the new observations. Types and values should conform to the namespace of the Annotation object. Examples -------- >>> ann = jams.Annotation(namespace='chord') >>> ann.append(time=3, duration=2, value='E#') ''' self.data.add(Observation(time=float(time), duration=float(duration), value=value, confidence=confidence))
[ "Append", "an", "observation", "to", "the", "data", "field" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L675-L699
[ "def", "append", "(", "self", ",", "time", "=", "None", ",", "duration", "=", "None", ",", "value", "=", "None", ",", "confidence", "=", "None", ")", ":", "self", ".", "data", ".", "add", "(", "Observation", "(", "time", "=", "float", "(", "time", ")", ",", "duration", "=", "float", "(", "duration", ")", ",", "value", "=", "value", ",", "confidence", "=", "confidence", ")", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.append_records
Add observations from row-major storage. This is primarily useful for deserializing sparsely packed data. Parameters ---------- records : iterable of dicts or Observations Each element of `records` corresponds to one observation.
jams/core.py
def append_records(self, records): '''Add observations from row-major storage. This is primarily useful for deserializing sparsely packed data. Parameters ---------- records : iterable of dicts or Observations Each element of `records` corresponds to one observation. ''' for obs in records: if isinstance(obs, Observation): self.append(**obs._asdict()) else: self.append(**obs)
def append_records(self, records): '''Add observations from row-major storage. This is primarily useful for deserializing sparsely packed data. Parameters ---------- records : iterable of dicts or Observations Each element of `records` corresponds to one observation. ''' for obs in records: if isinstance(obs, Observation): self.append(**obs._asdict()) else: self.append(**obs)
[ "Add", "observations", "from", "row", "-", "major", "storage", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L701-L715
[ "def", "append_records", "(", "self", ",", "records", ")", ":", "for", "obs", "in", "records", ":", "if", "isinstance", "(", "obs", ",", "Observation", ")", ":", "self", ".", "append", "(", "*", "*", "obs", ".", "_asdict", "(", ")", ")", "else", ":", "self", ".", "append", "(", "*", "*", "obs", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.append_columns
Add observations from column-major storage. This is primarily used for deserializing densely packed data. Parameters ---------- columns : dict of lists Keys must be `time, duration, value, confidence`, and each much be a list of equal length.
jams/core.py
def append_columns(self, columns): '''Add observations from column-major storage. This is primarily used for deserializing densely packed data. Parameters ---------- columns : dict of lists Keys must be `time, duration, value, confidence`, and each much be a list of equal length. ''' self.append_records([dict(time=t, duration=d, value=v, confidence=c) for (t, d, v, c) in six.moves.zip(columns['time'], columns['duration'], columns['value'], columns['confidence'])])
def append_columns(self, columns): '''Add observations from column-major storage. This is primarily used for deserializing densely packed data. Parameters ---------- columns : dict of lists Keys must be `time, duration, value, confidence`, and each much be a list of equal length. ''' self.append_records([dict(time=t, duration=d, value=v, confidence=c) for (t, d, v, c) in six.moves.zip(columns['time'], columns['duration'], columns['value'], columns['confidence'])])
[ "Add", "observations", "from", "column", "-", "major", "storage", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L717-L734
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b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.validate
Validate this annotation object against the JAMS schema, and its data against the namespace schema. Parameters ---------- strict : bool If `True`, then schema violations will cause an Exception. If `False`, then schema violations will issue a warning. Returns ------- valid : bool `True` if the object conforms to schema. `False` if the object fails to conform to schema, but `strict == False`. Raises ------ SchemaError If `strict == True` and the object fails validation See Also -------- JObject.validate
jams/core.py
def validate(self, strict=True): '''Validate this annotation object against the JAMS schema, and its data against the namespace schema. Parameters ---------- strict : bool If `True`, then schema violations will cause an Exception. If `False`, then schema violations will issue a warning. Returns ------- valid : bool `True` if the object conforms to schema. `False` if the object fails to conform to schema, but `strict == False`. Raises ------ SchemaError If `strict == True` and the object fails validation See Also -------- JObject.validate ''' # Get the schema for this annotation ann_schema = schema.namespace_array(self.namespace) valid = True try: jsonschema.validate(self.__json_light__(data=False), schema.JAMS_SCHEMA) # validate each record in the frame data_ser = [serialize_obj(obs) for obs in self.data] jsonschema.validate(data_ser, ann_schema) except jsonschema.ValidationError as invalid: if strict: raise SchemaError(str(invalid)) else: warnings.warn(str(invalid)) valid = False return valid
def validate(self, strict=True): '''Validate this annotation object against the JAMS schema, and its data against the namespace schema. Parameters ---------- strict : bool If `True`, then schema violations will cause an Exception. If `False`, then schema violations will issue a warning. Returns ------- valid : bool `True` if the object conforms to schema. `False` if the object fails to conform to schema, but `strict == False`. Raises ------ SchemaError If `strict == True` and the object fails validation See Also -------- JObject.validate ''' # Get the schema for this annotation ann_schema = schema.namespace_array(self.namespace) valid = True try: jsonschema.validate(self.__json_light__(data=False), schema.JAMS_SCHEMA) # validate each record in the frame data_ser = [serialize_obj(obs) for obs in self.data] jsonschema.validate(data_ser, ann_schema) except jsonschema.ValidationError as invalid: if strict: raise SchemaError(str(invalid)) else: warnings.warn(str(invalid)) valid = False return valid
[ "Validate", "this", "annotation", "object", "against", "the", "JAMS", "schema", "and", "its", "data", "against", "the", "namespace", "schema", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L736-L783
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b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.trim
Trim the annotation and return as a new `Annotation` object. Trimming will result in the new annotation only containing observations that occur in the intersection of the time range spanned by the annotation and the time range specified by the user. The new annotation will span the time range ``[trim_start, trim_end]`` where ``trim_start = max(self.time, start_time)`` and ``trim_end = min(self.time + self.duration, end_time)``. If ``strict=False`` (default) observations that start before ``trim_start`` and end after it will be trimmed such that they start at ``trim_start``, and similarly observations that start before ``trim_end`` and end after it will be trimmed to end at ``trim_end``. If ``strict=True`` such borderline observations will be discarded. The new duration of the annotation will be ``trim_end - trim_start``. Note that if the range defined by ``[start_time, end_time]`` doesn't intersect with the original time range spanned by the annotation the resulting annotation will contain no observations, will have the same start time as the original annotation and have duration 0. This function also copies over all the annotation metadata from the original annotation and documents the trim operation by adding a list of tuples to the annotation's sandbox keyed by ``Annotation.sandbox.trim`` which documents each trim operation with a tuple ``(start_time, end_time, trim_start, trim_end)``. Parameters ---------- start_time : float The desired start time for the trimmed annotation in seconds. end_time The desired end time for the trimmed annotation in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (given by ``[trim_start, trim_end]`` as described above), i.e. observations that start before and end after either the trim start or end time, will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- ann_trimmed : Annotation The trimmed annotation, returned as a new jams.Annotation object. If the trim range specified by ``[start_time, end_time]`` does not intersect at all with the original time range of the annotation a warning will be issued and the returned annotation will be empty. Raises ------ ParameterError If ``end_time`` is not greater than ``start_time``. Examples -------- >>> ann = jams.Annotation(namespace='tag_open', time=2, duration=8) >>> ann.append(time=2, duration=2, value='one') >>> ann.append(time=4, duration=2, value='two') >>> ann.append(time=6, duration=2, value='three') >>> ann.append(time=7, duration=2, value='four') >>> ann.append(time=8, duration=2, value='five') >>> ann_trim = ann.trim(5, 8, strict=False) >>> print(ann_trim.time, ann_trim.duration) (5, 3) >>> ann_trim.to_dataframe() time duration value confidence 0 5 1 two None 1 6 2 three None 2 7 1 four None >>> ann_trim_strict = ann.trim(5, 8, strict=True) >>> print(ann_trim_strict.time, ann_trim_strict.duration) (5, 3) >>> ann_trim_strict.to_dataframe() time duration value confidence 0 6 2 three None
jams/core.py
def trim(self, start_time, end_time, strict=False): ''' Trim the annotation and return as a new `Annotation` object. Trimming will result in the new annotation only containing observations that occur in the intersection of the time range spanned by the annotation and the time range specified by the user. The new annotation will span the time range ``[trim_start, trim_end]`` where ``trim_start = max(self.time, start_time)`` and ``trim_end = min(self.time + self.duration, end_time)``. If ``strict=False`` (default) observations that start before ``trim_start`` and end after it will be trimmed such that they start at ``trim_start``, and similarly observations that start before ``trim_end`` and end after it will be trimmed to end at ``trim_end``. If ``strict=True`` such borderline observations will be discarded. The new duration of the annotation will be ``trim_end - trim_start``. Note that if the range defined by ``[start_time, end_time]`` doesn't intersect with the original time range spanned by the annotation the resulting annotation will contain no observations, will have the same start time as the original annotation and have duration 0. This function also copies over all the annotation metadata from the original annotation and documents the trim operation by adding a list of tuples to the annotation's sandbox keyed by ``Annotation.sandbox.trim`` which documents each trim operation with a tuple ``(start_time, end_time, trim_start, trim_end)``. Parameters ---------- start_time : float The desired start time for the trimmed annotation in seconds. end_time The desired end time for the trimmed annotation in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (given by ``[trim_start, trim_end]`` as described above), i.e. observations that start before and end after either the trim start or end time, will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- ann_trimmed : Annotation The trimmed annotation, returned as a new jams.Annotation object. If the trim range specified by ``[start_time, end_time]`` does not intersect at all with the original time range of the annotation a warning will be issued and the returned annotation will be empty. Raises ------ ParameterError If ``end_time`` is not greater than ``start_time``. Examples -------- >>> ann = jams.Annotation(namespace='tag_open', time=2, duration=8) >>> ann.append(time=2, duration=2, value='one') >>> ann.append(time=4, duration=2, value='two') >>> ann.append(time=6, duration=2, value='three') >>> ann.append(time=7, duration=2, value='four') >>> ann.append(time=8, duration=2, value='five') >>> ann_trim = ann.trim(5, 8, strict=False) >>> print(ann_trim.time, ann_trim.duration) (5, 3) >>> ann_trim.to_dataframe() time duration value confidence 0 5 1 two None 1 6 2 three None 2 7 1 four None >>> ann_trim_strict = ann.trim(5, 8, strict=True) >>> print(ann_trim_strict.time, ann_trim_strict.duration) (5, 3) >>> ann_trim_strict.to_dataframe() time duration value confidence 0 6 2 three None ''' # Check for basic start_time and end_time validity if end_time <= start_time: raise ParameterError( 'end_time must be greater than start_time.') # If the annotation does not have a set duration value, we'll assume # trimming is possible (up to the user to ensure this is valid). if self.duration is None: orig_time = start_time orig_duration = end_time - start_time warnings.warn( "Annotation.duration is not defined, cannot check " "for temporal intersection, assuming the annotation " "is valid between start_time and end_time.") else: orig_time = self.time orig_duration = self.duration # Check whether there is intersection between the trim range and # annotation: if not raise a warning and set trim_start and trim_end # appropriately. if start_time > (orig_time + orig_duration) or (end_time < orig_time): warnings.warn( 'Time range defined by [start_time,end_time] does not ' 'intersect with the time range spanned by this annotation, ' 'the trimmed annotation will be empty.') trim_start = self.time trim_end = trim_start else: # Determine new range trim_start = max(orig_time, start_time) trim_end = min(orig_time + orig_duration, end_time) # Create new annotation with same namespace/metadata ann_trimmed = Annotation( self.namespace, data=None, annotation_metadata=self.annotation_metadata, sandbox=self.sandbox, time=trim_start, duration=trim_end - trim_start) # Selectively add observations based on their start time / duration # We do this rather than copying and directly manipulating the # annotation' data frame (which might be faster) since this way trim is # independent of the internal data representation. for obs in self.data: obs_start = obs.time obs_end = obs_start + obs.duration if obs_start < trim_end and obs_end > trim_start: new_start = max(obs_start, trim_start) new_end = min(obs_end, trim_end) new_duration = new_end - new_start if ((not strict) or (new_start == obs_start and new_end == obs_end)): ann_trimmed.append(time=new_start, duration=new_duration, value=obs.value, confidence=obs.confidence) if 'trim' not in ann_trimmed.sandbox.keys(): ann_trimmed.sandbox.update( trim=[{'start_time': start_time, 'end_time': end_time, 'trim_start': trim_start, 'trim_end': trim_end}]) else: ann_trimmed.sandbox.trim.append( {'start_time': start_time, 'end_time': end_time, 'trim_start': trim_start, 'trim_end': trim_end}) return ann_trimmed
def trim(self, start_time, end_time, strict=False): ''' Trim the annotation and return as a new `Annotation` object. Trimming will result in the new annotation only containing observations that occur in the intersection of the time range spanned by the annotation and the time range specified by the user. The new annotation will span the time range ``[trim_start, trim_end]`` where ``trim_start = max(self.time, start_time)`` and ``trim_end = min(self.time + self.duration, end_time)``. If ``strict=False`` (default) observations that start before ``trim_start`` and end after it will be trimmed such that they start at ``trim_start``, and similarly observations that start before ``trim_end`` and end after it will be trimmed to end at ``trim_end``. If ``strict=True`` such borderline observations will be discarded. The new duration of the annotation will be ``trim_end - trim_start``. Note that if the range defined by ``[start_time, end_time]`` doesn't intersect with the original time range spanned by the annotation the resulting annotation will contain no observations, will have the same start time as the original annotation and have duration 0. This function also copies over all the annotation metadata from the original annotation and documents the trim operation by adding a list of tuples to the annotation's sandbox keyed by ``Annotation.sandbox.trim`` which documents each trim operation with a tuple ``(start_time, end_time, trim_start, trim_end)``. Parameters ---------- start_time : float The desired start time for the trimmed annotation in seconds. end_time The desired end time for the trimmed annotation in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (given by ``[trim_start, trim_end]`` as described above), i.e. observations that start before and end after either the trim start or end time, will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- ann_trimmed : Annotation The trimmed annotation, returned as a new jams.Annotation object. If the trim range specified by ``[start_time, end_time]`` does not intersect at all with the original time range of the annotation a warning will be issued and the returned annotation will be empty. Raises ------ ParameterError If ``end_time`` is not greater than ``start_time``. Examples -------- >>> ann = jams.Annotation(namespace='tag_open', time=2, duration=8) >>> ann.append(time=2, duration=2, value='one') >>> ann.append(time=4, duration=2, value='two') >>> ann.append(time=6, duration=2, value='three') >>> ann.append(time=7, duration=2, value='four') >>> ann.append(time=8, duration=2, value='five') >>> ann_trim = ann.trim(5, 8, strict=False) >>> print(ann_trim.time, ann_trim.duration) (5, 3) >>> ann_trim.to_dataframe() time duration value confidence 0 5 1 two None 1 6 2 three None 2 7 1 four None >>> ann_trim_strict = ann.trim(5, 8, strict=True) >>> print(ann_trim_strict.time, ann_trim_strict.duration) (5, 3) >>> ann_trim_strict.to_dataframe() time duration value confidence 0 6 2 three None ''' # Check for basic start_time and end_time validity if end_time <= start_time: raise ParameterError( 'end_time must be greater than start_time.') # If the annotation does not have a set duration value, we'll assume # trimming is possible (up to the user to ensure this is valid). if self.duration is None: orig_time = start_time orig_duration = end_time - start_time warnings.warn( "Annotation.duration is not defined, cannot check " "for temporal intersection, assuming the annotation " "is valid between start_time and end_time.") else: orig_time = self.time orig_duration = self.duration # Check whether there is intersection between the trim range and # annotation: if not raise a warning and set trim_start and trim_end # appropriately. if start_time > (orig_time + orig_duration) or (end_time < orig_time): warnings.warn( 'Time range defined by [start_time,end_time] does not ' 'intersect with the time range spanned by this annotation, ' 'the trimmed annotation will be empty.') trim_start = self.time trim_end = trim_start else: # Determine new range trim_start = max(orig_time, start_time) trim_end = min(orig_time + orig_duration, end_time) # Create new annotation with same namespace/metadata ann_trimmed = Annotation( self.namespace, data=None, annotation_metadata=self.annotation_metadata, sandbox=self.sandbox, time=trim_start, duration=trim_end - trim_start) # Selectively add observations based on their start time / duration # We do this rather than copying and directly manipulating the # annotation' data frame (which might be faster) since this way trim is # independent of the internal data representation. for obs in self.data: obs_start = obs.time obs_end = obs_start + obs.duration if obs_start < trim_end and obs_end > trim_start: new_start = max(obs_start, trim_start) new_end = min(obs_end, trim_end) new_duration = new_end - new_start if ((not strict) or (new_start == obs_start and new_end == obs_end)): ann_trimmed.append(time=new_start, duration=new_duration, value=obs.value, confidence=obs.confidence) if 'trim' not in ann_trimmed.sandbox.keys(): ann_trimmed.sandbox.update( trim=[{'start_time': start_time, 'end_time': end_time, 'trim_start': trim_start, 'trim_end': trim_end}]) else: ann_trimmed.sandbox.trim.append( {'start_time': start_time, 'end_time': end_time, 'trim_start': trim_start, 'trim_end': trim_end}) return ann_trimmed
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marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L785-L941
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b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.slice
Slice the annotation and return as a new `Annotation` object. Slicing has the same effect as trimming (see `Annotation.trim`) except that while trimming does not modify the start time of the annotation or the observations it contains, slicing will set the new annotation's start time to ``max(0, trimmed_annotation.time - start_time)`` and the start time of its observations will be set with respect to this new reference start time. This function documents the slice operation by adding a list of tuples to the annotation's sandbox keyed by ``Annotation.sandbox.slice`` which documents each slice operation with a tuple ``(start_time, end_time, slice_start, slice_end)``, where ``slice_start`` and ``slice_end`` are given by ``trim_start`` and ``trim_end`` (see `Annotation.trim`). Since slicing is implemented using trimming, the trimming operation will also be documented in ``Annotation.sandbox.trim`` as described in `Annotation.trim`. This function is useful for example when trimming an audio file, allowing the user to trim the annotation while ensuring all time information matches the new trimmed audio file. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slice (see `Annotation.trim` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the slice range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- sliced_ann : Annotation The sliced annotation. See Also -------- Annotation.trim Examples -------- >>> ann = jams.Annotation(namespace='tag_open', time=2, duration=8) >>> ann.append(time=2, duration=2, value='one') >>> ann.append(time=4, duration=2, value='two') >>> ann.append(time=6, duration=2, value='three') >>> ann.append(time=7, duration=2, value='four') >>> ann.append(time=8, duration=2, value='five') >>> ann_slice = ann.slice(5, 8, strict=False) >>> print(ann_slice.time, ann_slice.duration) (0, 3) >>> ann_slice.to_dataframe() time duration value confidence 0 0.0 1.0 two None 1 1.0 2.0 three None 2 2.0 1.0 four None >>> ann_slice_strict = ann.slice(5, 8, strict=True) >>> print(ann_slice_strict.time, ann_slice_strict.duration) (0, 3) >>> ann_slice_strict.to_dataframe() time duration value confidence 0 1.0 2.0 three None
jams/core.py
def slice(self, start_time, end_time, strict=False): ''' Slice the annotation and return as a new `Annotation` object. Slicing has the same effect as trimming (see `Annotation.trim`) except that while trimming does not modify the start time of the annotation or the observations it contains, slicing will set the new annotation's start time to ``max(0, trimmed_annotation.time - start_time)`` and the start time of its observations will be set with respect to this new reference start time. This function documents the slice operation by adding a list of tuples to the annotation's sandbox keyed by ``Annotation.sandbox.slice`` which documents each slice operation with a tuple ``(start_time, end_time, slice_start, slice_end)``, where ``slice_start`` and ``slice_end`` are given by ``trim_start`` and ``trim_end`` (see `Annotation.trim`). Since slicing is implemented using trimming, the trimming operation will also be documented in ``Annotation.sandbox.trim`` as described in `Annotation.trim`. This function is useful for example when trimming an audio file, allowing the user to trim the annotation while ensuring all time information matches the new trimmed audio file. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slice (see `Annotation.trim` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the slice range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- sliced_ann : Annotation The sliced annotation. See Also -------- Annotation.trim Examples -------- >>> ann = jams.Annotation(namespace='tag_open', time=2, duration=8) >>> ann.append(time=2, duration=2, value='one') >>> ann.append(time=4, duration=2, value='two') >>> ann.append(time=6, duration=2, value='three') >>> ann.append(time=7, duration=2, value='four') >>> ann.append(time=8, duration=2, value='five') >>> ann_slice = ann.slice(5, 8, strict=False) >>> print(ann_slice.time, ann_slice.duration) (0, 3) >>> ann_slice.to_dataframe() time duration value confidence 0 0.0 1.0 two None 1 1.0 2.0 three None 2 2.0 1.0 four None >>> ann_slice_strict = ann.slice(5, 8, strict=True) >>> print(ann_slice_strict.time, ann_slice_strict.duration) (0, 3) >>> ann_slice_strict.to_dataframe() time duration value confidence 0 1.0 2.0 three None ''' # start by trimming the annotation sliced_ann = self.trim(start_time, end_time, strict=strict) raw_data = sliced_ann.pop_data() # now adjust the start time of the annotation and the observations it # contains. for obs in raw_data: new_time = max(0, obs.time - start_time) # if obs.time > start_time, # duration doesn't change # if obs.time < start_time, # duration shrinks by start_time - obs.time sliced_ann.append(time=new_time, duration=obs.duration, value=obs.value, confidence=obs.confidence) ref_time = sliced_ann.time slice_start = ref_time slice_end = ref_time + sliced_ann.duration if 'slice' not in sliced_ann.sandbox.keys(): sliced_ann.sandbox.update( slice=[{'start_time': start_time, 'end_time': end_time, 'slice_start': slice_start, 'slice_end': slice_end}]) else: sliced_ann.sandbox.slice.append( {'start_time': start_time, 'end_time': end_time, 'slice_start': slice_start, 'slice_end': slice_end}) # Update the timing for the sliced annotation sliced_ann.time = max(0, ref_time - start_time) return sliced_ann
def slice(self, start_time, end_time, strict=False): ''' Slice the annotation and return as a new `Annotation` object. Slicing has the same effect as trimming (see `Annotation.trim`) except that while trimming does not modify the start time of the annotation or the observations it contains, slicing will set the new annotation's start time to ``max(0, trimmed_annotation.time - start_time)`` and the start time of its observations will be set with respect to this new reference start time. This function documents the slice operation by adding a list of tuples to the annotation's sandbox keyed by ``Annotation.sandbox.slice`` which documents each slice operation with a tuple ``(start_time, end_time, slice_start, slice_end)``, where ``slice_start`` and ``slice_end`` are given by ``trim_start`` and ``trim_end`` (see `Annotation.trim`). Since slicing is implemented using trimming, the trimming operation will also be documented in ``Annotation.sandbox.trim`` as described in `Annotation.trim`. This function is useful for example when trimming an audio file, allowing the user to trim the annotation while ensuring all time information matches the new trimmed audio file. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slice (see `Annotation.trim` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the slice range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- sliced_ann : Annotation The sliced annotation. See Also -------- Annotation.trim Examples -------- >>> ann = jams.Annotation(namespace='tag_open', time=2, duration=8) >>> ann.append(time=2, duration=2, value='one') >>> ann.append(time=4, duration=2, value='two') >>> ann.append(time=6, duration=2, value='three') >>> ann.append(time=7, duration=2, value='four') >>> ann.append(time=8, duration=2, value='five') >>> ann_slice = ann.slice(5, 8, strict=False) >>> print(ann_slice.time, ann_slice.duration) (0, 3) >>> ann_slice.to_dataframe() time duration value confidence 0 0.0 1.0 two None 1 1.0 2.0 three None 2 2.0 1.0 four None >>> ann_slice_strict = ann.slice(5, 8, strict=True) >>> print(ann_slice_strict.time, ann_slice_strict.duration) (0, 3) >>> ann_slice_strict.to_dataframe() time duration value confidence 0 1.0 2.0 three None ''' # start by trimming the annotation sliced_ann = self.trim(start_time, end_time, strict=strict) raw_data = sliced_ann.pop_data() # now adjust the start time of the annotation and the observations it # contains. for obs in raw_data: new_time = max(0, obs.time - start_time) # if obs.time > start_time, # duration doesn't change # if obs.time < start_time, # duration shrinks by start_time - obs.time sliced_ann.append(time=new_time, duration=obs.duration, value=obs.value, confidence=obs.confidence) ref_time = sliced_ann.time slice_start = ref_time slice_end = ref_time + sliced_ann.duration if 'slice' not in sliced_ann.sandbox.keys(): sliced_ann.sandbox.update( slice=[{'start_time': start_time, 'end_time': end_time, 'slice_start': slice_start, 'slice_end': slice_end}]) else: sliced_ann.sandbox.slice.append( {'start_time': start_time, 'end_time': end_time, 'slice_start': slice_start, 'slice_end': slice_end}) # Update the timing for the sliced annotation sliced_ann.time = max(0, ref_time - start_time) return sliced_ann
[ "Slice", "the", "annotation", "and", "return", "as", "a", "new", "Annotation", "object", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L943-L1050
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b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.pop_data
Replace this observation's data with a fresh container. Returns ------- annotation_data : SortedKeyList The original annotation data container
jams/core.py
def pop_data(self): '''Replace this observation's data with a fresh container. Returns ------- annotation_data : SortedKeyList The original annotation data container ''' data = self.data self.data = SortedKeyList(key=self._key) return data
def pop_data(self): '''Replace this observation's data with a fresh container. Returns ------- annotation_data : SortedKeyList The original annotation data container ''' data = self.data self.data = SortedKeyList(key=self._key) return data
[ "Replace", "this", "observation", "s", "data", "with", "a", "fresh", "container", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1052-L1063
[ "def", "pop_data", "(", "self", ")", ":", "data", "=", "self", ".", "data", "self", ".", "data", "=", "SortedKeyList", "(", "key", "=", "self", ".", "_key", ")", "return", "data" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.to_interval_values
Extract observation data in a `mir_eval`-friendly format. Returns ------- intervals : np.ndarray [shape=(n, 2), dtype=float] Start- and end-times of all valued intervals `intervals[i, :] = [time[i], time[i] + duration[i]]` labels : list List view of value field.
jams/core.py
def to_interval_values(self): '''Extract observation data in a `mir_eval`-friendly format. Returns ------- intervals : np.ndarray [shape=(n, 2), dtype=float] Start- and end-times of all valued intervals `intervals[i, :] = [time[i], time[i] + duration[i]]` labels : list List view of value field. ''' ints, vals = [], [] for obs in self.data: ints.append([obs.time, obs.time + obs.duration]) vals.append(obs.value) if not ints: return np.empty(shape=(0, 2), dtype=float), [] return np.array(ints), vals
def to_interval_values(self): '''Extract observation data in a `mir_eval`-friendly format. Returns ------- intervals : np.ndarray [shape=(n, 2), dtype=float] Start- and end-times of all valued intervals `intervals[i, :] = [time[i], time[i] + duration[i]]` labels : list List view of value field. ''' ints, vals = [], [] for obs in self.data: ints.append([obs.time, obs.time + obs.duration]) vals.append(obs.value) if not ints: return np.empty(shape=(0, 2), dtype=float), [] return np.array(ints), vals
[ "Extract", "observation", "data", "in", "a", "mir_eval", "-", "friendly", "format", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1065-L1087
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b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.to_event_values
Extract observation data in a `mir_eval`-friendly format. Returns ------- times : np.ndarray [shape=(n,), dtype=float] Start-time of all observations labels : list List view of value field.
jams/core.py
def to_event_values(self): '''Extract observation data in a `mir_eval`-friendly format. Returns ------- times : np.ndarray [shape=(n,), dtype=float] Start-time of all observations labels : list List view of value field. ''' ints, vals = [], [] for obs in self.data: ints.append(obs.time) vals.append(obs.value) return np.array(ints), vals
def to_event_values(self): '''Extract observation data in a `mir_eval`-friendly format. Returns ------- times : np.ndarray [shape=(n,), dtype=float] Start-time of all observations labels : list List view of value field. ''' ints, vals = [], [] for obs in self.data: ints.append(obs.time) vals.append(obs.value) return np.array(ints), vals
[ "Extract", "observation", "data", "in", "a", "mir_eval", "-", "friendly", "format", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1089-L1105
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b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.to_samples
Sample the annotation at specified times. Parameters ---------- times : np.ndarray, non-negative, ndim=1 The times (in seconds) to sample the annotation confidence : bool If `True`, return both values and confidences. If `False` (default) only return values. Returns ------- values : list `values[i]` is a list of observation values for intervals that cover `times[i]`. confidence : list (optional) `confidence` values corresponding to `values`
jams/core.py
def to_samples(self, times, confidence=False): '''Sample the annotation at specified times. Parameters ---------- times : np.ndarray, non-negative, ndim=1 The times (in seconds) to sample the annotation confidence : bool If `True`, return both values and confidences. If `False` (default) only return values. Returns ------- values : list `values[i]` is a list of observation values for intervals that cover `times[i]`. confidence : list (optional) `confidence` values corresponding to `values` ''' times = np.asarray(times) if times.ndim != 1 or np.any(times < 0): raise ParameterError('times must be 1-dimensional and non-negative') idx = np.argsort(times) samples = times[idx] values = [list() for _ in samples] confidences = [list() for _ in samples] for obs in self.data: start = np.searchsorted(samples, obs.time) end = np.searchsorted(samples, obs.time + obs.duration, side='right') for i in range(start, end): values[idx[i]].append(obs.value) confidences[idx[i]].append(obs.confidence) if confidence: return values, confidences else: return values
def to_samples(self, times, confidence=False): '''Sample the annotation at specified times. Parameters ---------- times : np.ndarray, non-negative, ndim=1 The times (in seconds) to sample the annotation confidence : bool If `True`, return both values and confidences. If `False` (default) only return values. Returns ------- values : list `values[i]` is a list of observation values for intervals that cover `times[i]`. confidence : list (optional) `confidence` values corresponding to `values` ''' times = np.asarray(times) if times.ndim != 1 or np.any(times < 0): raise ParameterError('times must be 1-dimensional and non-negative') idx = np.argsort(times) samples = times[idx] values = [list() for _ in samples] confidences = [list() for _ in samples] for obs in self.data: start = np.searchsorted(samples, obs.time) end = np.searchsorted(samples, obs.time + obs.duration, side='right') for i in range(start, end): values[idx[i]].append(obs.value) confidences[idx[i]].append(obs.confidence) if confidence: return values, confidences else: return values
[ "Sample", "the", "annotation", "at", "specified", "times", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1121-L1162
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b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation.to_html
Render this annotation list in HTML Returns ------- rendered : str An HTML table containing this annotation's data.
jams/core.py
def to_html(self, max_rows=None): '''Render this annotation list in HTML Returns ------- rendered : str An HTML table containing this annotation's data. ''' n = len(self.data) div_id = _get_divid(self) out = r''' <div class="panel panel-default"> <div class="panel-heading" role="tab" id="heading-{0}"> <button type="button" data-toggle="collapse" data-parent="#accordion" href="#{0}" aria-expanded="false" class="collapsed btn btn-info btn-block" aria-controls="{0}"> {1:s} <span class="badge pull-right">{2:d}</span> </button> </div>'''.format(div_id, self.namespace, n) out += r''' <div id="{0}" class="panel-collapse collapse" role="tabpanel" aria-labelledby="heading-{0}"> <div class="panel-body">'''.format(div_id) out += r'''<div class="pull-right"> {} </div>'''.format(self.annotation_metadata._repr_html_()) out += r'''<div class="pull-right clearfix"> {} </div>'''.format(self.sandbox._repr_html_()) # -- Annotation content starts here out += r'''<div><table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>time</th> <th>duration</th> <th>value</th> <th>confidence</th> </tr> </thead>'''.format(self.namespace, n) out += r'''<tbody>''' if max_rows is None or n <= max_rows: out += self._fmt_rows(0, n) else: out += self._fmt_rows(0, max_rows//2) out += r'''<tr> <th>...</th> <td>...</td> <td>...</td> <td>...</td> <td>...</td> </tr>''' out += self._fmt_rows(n-max_rows//2, n) out += r'''</tbody>''' out += r'''</table></div>''' out += r'''</div></div></div>''' return out
def to_html(self, max_rows=None): '''Render this annotation list in HTML Returns ------- rendered : str An HTML table containing this annotation's data. ''' n = len(self.data) div_id = _get_divid(self) out = r''' <div class="panel panel-default"> <div class="panel-heading" role="tab" id="heading-{0}"> <button type="button" data-toggle="collapse" data-parent="#accordion" href="#{0}" aria-expanded="false" class="collapsed btn btn-info btn-block" aria-controls="{0}"> {1:s} <span class="badge pull-right">{2:d}</span> </button> </div>'''.format(div_id, self.namespace, n) out += r''' <div id="{0}" class="panel-collapse collapse" role="tabpanel" aria-labelledby="heading-{0}"> <div class="panel-body">'''.format(div_id) out += r'''<div class="pull-right"> {} </div>'''.format(self.annotation_metadata._repr_html_()) out += r'''<div class="pull-right clearfix"> {} </div>'''.format(self.sandbox._repr_html_()) # -- Annotation content starts here out += r'''<div><table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>time</th> <th>duration</th> <th>value</th> <th>confidence</th> </tr> </thead>'''.format(self.namespace, n) out += r'''<tbody>''' if max_rows is None or n <= max_rows: out += self._fmt_rows(0, n) else: out += self._fmt_rows(0, max_rows//2) out += r'''<tr> <th>...</th> <td>...</td> <td>...</td> <td>...</td> <td>...</td> </tr>''' out += self._fmt_rows(n-max_rows//2, n) out += r'''</tbody>''' out += r'''</table></div>''' out += r'''</div></div></div>''' return out
[ "Render", "this", "annotation", "list", "in", "HTML" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1167-L1237
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b16778399b9528efbd71434842a079f7691a7a66
valid
Annotation._key
Provides sorting index for Observation objects
jams/core.py
def _key(cls, obs): '''Provides sorting index for Observation objects''' if not isinstance(obs, Observation): raise JamsError('{} must be of type jams.Observation'.format(obs)) return obs.time
def _key(cls, obs): '''Provides sorting index for Observation objects''' if not isinstance(obs, Observation): raise JamsError('{} must be of type jams.Observation'.format(obs)) return obs.time
[ "Provides", "sorting", "index", "for", "Observation", "objects" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1305-L1310
[ "def", "_key", "(", "cls", ",", "obs", ")", ":", "if", "not", "isinstance", "(", "obs", ",", "Observation", ")", ":", "raise", "JamsError", "(", "'{} must be of type jams.Observation'", ".", "format", "(", "obs", ")", ")", "return", "obs", ".", "time" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
AnnotationArray.search
Filter the annotation array down to only those Annotation objects matching the query. Parameters ---------- kwargs : search parameters See JObject.search Returns ------- results : AnnotationArray An annotation array of the objects matching the query See Also -------- JObject.search
jams/core.py
def search(self, **kwargs): '''Filter the annotation array down to only those Annotation objects matching the query. Parameters ---------- kwargs : search parameters See JObject.search Returns ------- results : AnnotationArray An annotation array of the objects matching the query See Also -------- JObject.search ''' results = AnnotationArray() for annotation in self: if annotation.search(**kwargs): results.append(annotation) return results
def search(self, **kwargs): '''Filter the annotation array down to only those Annotation objects matching the query. Parameters ---------- kwargs : search parameters See JObject.search Returns ------- results : AnnotationArray An annotation array of the objects matching the query See Also -------- JObject.search ''' results = AnnotationArray() for annotation in self: if annotation.search(**kwargs): results.append(annotation) return results
[ "Filter", "the", "annotation", "array", "down", "to", "only", "those", "Annotation", "objects", "matching", "the", "query", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1504-L1530
[ "def", "search", "(", "self", ",", "*", "*", "kwargs", ")", ":", "results", "=", "AnnotationArray", "(", ")", "for", "annotation", "in", "self", ":", "if", "annotation", ".", "search", "(", "*", "*", "kwargs", ")", ":", "results", ".", "append", "(", "annotation", ")", "return", "results" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
AnnotationArray.trim
Trim every annotation contained in the annotation array using `Annotation.trim` and return as a new `AnnotationArray`. See `Annotation.trim` for details about trimming. This function does not modify the annotations in the original annotation array. Parameters ---------- start_time : float The desired start time for the trimmed annotations in seconds. end_time The desired end time for trimmed annotations in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (see `Annotation.trim` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- trimmed_array : AnnotationArray An annotation array where every annotation has been trimmed.
jams/core.py
def trim(self, start_time, end_time, strict=False): ''' Trim every annotation contained in the annotation array using `Annotation.trim` and return as a new `AnnotationArray`. See `Annotation.trim` for details about trimming. This function does not modify the annotations in the original annotation array. Parameters ---------- start_time : float The desired start time for the trimmed annotations in seconds. end_time The desired end time for trimmed annotations in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (see `Annotation.trim` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- trimmed_array : AnnotationArray An annotation array where every annotation has been trimmed. ''' trimmed_array = AnnotationArray() for ann in self: trimmed_array.append(ann.trim(start_time, end_time, strict=strict)) return trimmed_array
def trim(self, start_time, end_time, strict=False): ''' Trim every annotation contained in the annotation array using `Annotation.trim` and return as a new `AnnotationArray`. See `Annotation.trim` for details about trimming. This function does not modify the annotations in the original annotation array. Parameters ---------- start_time : float The desired start time for the trimmed annotations in seconds. end_time The desired end time for trimmed annotations in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (see `Annotation.trim` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- trimmed_array : AnnotationArray An annotation array where every annotation has been trimmed. ''' trimmed_array = AnnotationArray() for ann in self: trimmed_array.append(ann.trim(start_time, end_time, strict=strict)) return trimmed_array
[ "Trim", "every", "annotation", "contained", "in", "the", "annotation", "array", "using", "Annotation", ".", "trim", "and", "return", "as", "a", "new", "AnnotationArray", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1548-L1581
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b16778399b9528efbd71434842a079f7691a7a66
valid
AnnotationArray.slice
Slice every annotation contained in the annotation array using `Annotation.slice` and return as a new AnnotationArray See `Annotation.slice` for details about slicing. This function does not modify the annotations in the original annotation array. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slicing range (see `Annotation.slice` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- sliced_array : AnnotationArray An annotation array where every annotation has been sliced.
jams/core.py
def slice(self, start_time, end_time, strict=False): ''' Slice every annotation contained in the annotation array using `Annotation.slice` and return as a new AnnotationArray See `Annotation.slice` for details about slicing. This function does not modify the annotations in the original annotation array. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slicing range (see `Annotation.slice` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- sliced_array : AnnotationArray An annotation array where every annotation has been sliced. ''' sliced_array = AnnotationArray() for ann in self: sliced_array.append(ann.slice(start_time, end_time, strict=strict)) return sliced_array
def slice(self, start_time, end_time, strict=False): ''' Slice every annotation contained in the annotation array using `Annotation.slice` and return as a new AnnotationArray See `Annotation.slice` for details about slicing. This function does not modify the annotations in the original annotation array. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slicing range (see `Annotation.slice` for details) will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- sliced_array : AnnotationArray An annotation array where every annotation has been sliced. ''' sliced_array = AnnotationArray() for ann in self: sliced_array.append(ann.slice(start_time, end_time, strict=strict)) return sliced_array
[ "Slice", "every", "annotation", "contained", "in", "the", "annotation", "array", "using", "Annotation", ".", "slice", "and", "return", "as", "a", "new", "AnnotationArray" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1583-L1616
[ "def", "slice", "(", "self", ",", "start_time", ",", "end_time", ",", "strict", "=", "False", ")", ":", "sliced_array", "=", "AnnotationArray", "(", ")", "for", "ann", "in", "self", ":", "sliced_array", ".", "append", "(", "ann", ".", "slice", "(", "start_time", ",", "end_time", ",", "strict", "=", "strict", ")", ")", "return", "sliced_array" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
JAMS.add
Add the contents of another jam to this object. Note that, by default, this method fails if file_metadata is not identical and raises a ValueError; either resolve this manually (because conflicts should almost never happen), force an 'overwrite', or tell the method to 'ignore' the metadata of the object being added. Parameters ---------- jam: JAMS object Object to add to this jam on_conflict: str, default='fail' Strategy for resolving metadata conflicts; one of ['fail', 'overwrite', or 'ignore']. Raises ------ ParameterError if `on_conflict` is an unknown value JamsError If a conflict is detected and `on_conflict='fail'`
jams/core.py
def add(self, jam, on_conflict='fail'): """Add the contents of another jam to this object. Note that, by default, this method fails if file_metadata is not identical and raises a ValueError; either resolve this manually (because conflicts should almost never happen), force an 'overwrite', or tell the method to 'ignore' the metadata of the object being added. Parameters ---------- jam: JAMS object Object to add to this jam on_conflict: str, default='fail' Strategy for resolving metadata conflicts; one of ['fail', 'overwrite', or 'ignore']. Raises ------ ParameterError if `on_conflict` is an unknown value JamsError If a conflict is detected and `on_conflict='fail'` """ if on_conflict not in ['overwrite', 'fail', 'ignore']: raise ParameterError("on_conflict='{}' is not in ['fail', " "'overwrite', 'ignore'].".format(on_conflict)) if not self.file_metadata == jam.file_metadata: if on_conflict == 'overwrite': self.file_metadata = jam.file_metadata elif on_conflict == 'fail': raise JamsError("Metadata conflict! " "Resolve manually or force-overwrite it.") self.annotations.extend(jam.annotations) self.sandbox.update(**jam.sandbox)
def add(self, jam, on_conflict='fail'): """Add the contents of another jam to this object. Note that, by default, this method fails if file_metadata is not identical and raises a ValueError; either resolve this manually (because conflicts should almost never happen), force an 'overwrite', or tell the method to 'ignore' the metadata of the object being added. Parameters ---------- jam: JAMS object Object to add to this jam on_conflict: str, default='fail' Strategy for resolving metadata conflicts; one of ['fail', 'overwrite', or 'ignore']. Raises ------ ParameterError if `on_conflict` is an unknown value JamsError If a conflict is detected and `on_conflict='fail'` """ if on_conflict not in ['overwrite', 'fail', 'ignore']: raise ParameterError("on_conflict='{}' is not in ['fail', " "'overwrite', 'ignore'].".format(on_conflict)) if not self.file_metadata == jam.file_metadata: if on_conflict == 'overwrite': self.file_metadata = jam.file_metadata elif on_conflict == 'fail': raise JamsError("Metadata conflict! " "Resolve manually or force-overwrite it.") self.annotations.extend(jam.annotations) self.sandbox.update(**jam.sandbox)
[ "Add", "the", "contents", "of", "another", "jam", "to", "this", "object", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1674-L1712
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b16778399b9528efbd71434842a079f7691a7a66
valid
JAMS.save
Serialize annotation as a JSON formatted stream to file. Parameters ---------- path_or_file : str or file-like Path to save the JAMS object on disk OR An open file descriptor to write into strict : bool Force strict schema validation fmt : str ['auto', 'jams', 'jamz'] The output encoding format. If `auto`, it is inferred from the file name. If the input is an open file handle, `jams` encoding is used. Raises ------ SchemaError If `strict == True` and the JAMS object fails schema or namespace validation. See also -------- validate
jams/core.py
def save(self, path_or_file, strict=True, fmt='auto'): """Serialize annotation as a JSON formatted stream to file. Parameters ---------- path_or_file : str or file-like Path to save the JAMS object on disk OR An open file descriptor to write into strict : bool Force strict schema validation fmt : str ['auto', 'jams', 'jamz'] The output encoding format. If `auto`, it is inferred from the file name. If the input is an open file handle, `jams` encoding is used. Raises ------ SchemaError If `strict == True` and the JAMS object fails schema or namespace validation. See also -------- validate """ self.validate(strict=strict) with _open(path_or_file, mode='w', fmt=fmt) as fdesc: json.dump(self.__json__, fdesc, indent=2)
def save(self, path_or_file, strict=True, fmt='auto'): """Serialize annotation as a JSON formatted stream to file. Parameters ---------- path_or_file : str or file-like Path to save the JAMS object on disk OR An open file descriptor to write into strict : bool Force strict schema validation fmt : str ['auto', 'jams', 'jamz'] The output encoding format. If `auto`, it is inferred from the file name. If the input is an open file handle, `jams` encoding is used. Raises ------ SchemaError If `strict == True` and the JAMS object fails schema or namespace validation. See also -------- validate """ self.validate(strict=strict) with _open(path_or_file, mode='w', fmt=fmt) as fdesc: json.dump(self.__json__, fdesc, indent=2)
[ "Serialize", "annotation", "as", "a", "JSON", "formatted", "stream", "to", "file", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1743-L1779
[ "def", "save", "(", "self", ",", "path_or_file", ",", "strict", "=", "True", ",", "fmt", "=", "'auto'", ")", ":", "self", ".", "validate", "(", "strict", "=", "strict", ")", "with", "_open", "(", "path_or_file", ",", "mode", "=", "'w'", ",", "fmt", "=", "fmt", ")", "as", "fdesc", ":", "json", ".", "dump", "(", "self", ".", "__json__", ",", "fdesc", ",", "indent", "=", "2", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
JAMS.validate
Validate a JAMS object against the schema. Parameters ---------- strict : bool If `True`, an exception will be raised on validation failure. If `False`, a warning will be raised on validation failure. Returns ------- valid : bool `True` if the object passes schema validation. `False` otherwise. Raises ------ SchemaError If `strict==True` and the JAMS object does not match the schema See Also -------- jsonschema.validate
jams/core.py
def validate(self, strict=True): '''Validate a JAMS object against the schema. Parameters ---------- strict : bool If `True`, an exception will be raised on validation failure. If `False`, a warning will be raised on validation failure. Returns ------- valid : bool `True` if the object passes schema validation. `False` otherwise. Raises ------ SchemaError If `strict==True` and the JAMS object does not match the schema See Also -------- jsonschema.validate ''' valid = True try: jsonschema.validate(self.__json_light__, schema.JAMS_SCHEMA) for ann in self.annotations: if isinstance(ann, Annotation): valid &= ann.validate(strict=strict) else: msg = '{} is not a well-formed JAMS Annotation'.format(ann) valid = False if strict: raise SchemaError(msg) else: warnings.warn(str(msg)) except jsonschema.ValidationError as invalid: if strict: raise SchemaError(str(invalid)) else: warnings.warn(str(invalid)) valid = False return valid
def validate(self, strict=True): '''Validate a JAMS object against the schema. Parameters ---------- strict : bool If `True`, an exception will be raised on validation failure. If `False`, a warning will be raised on validation failure. Returns ------- valid : bool `True` if the object passes schema validation. `False` otherwise. Raises ------ SchemaError If `strict==True` and the JAMS object does not match the schema See Also -------- jsonschema.validate ''' valid = True try: jsonschema.validate(self.__json_light__, schema.JAMS_SCHEMA) for ann in self.annotations: if isinstance(ann, Annotation): valid &= ann.validate(strict=strict) else: msg = '{} is not a well-formed JAMS Annotation'.format(ann) valid = False if strict: raise SchemaError(msg) else: warnings.warn(str(msg)) except jsonschema.ValidationError as invalid: if strict: raise SchemaError(str(invalid)) else: warnings.warn(str(invalid)) valid = False return valid
[ "Validate", "a", "JAMS", "object", "against", "the", "schema", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1781-L1829
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b16778399b9528efbd71434842a079f7691a7a66
valid
JAMS.trim
Trim all the annotations inside the jam and return as a new `JAMS` object. See `Annotation.trim` for details about how the annotations are trimmed. This operation is also documented in the jam-level sandbox with a list keyed by ``JAMS.sandbox.trim`` containing a tuple for each jam-level trim of the form ``(start_time, end_time)``. This function also copies over all of the file metadata from the original jam. Note: trimming does not affect the duration of the jam, i.e. the value of ``JAMS.file_metadata.duration`` will be the same for the original and trimmed jams. Parameters ---------- start_time : float The desired start time for the trimmed annotations in seconds. end_time The desired end time for trimmed annotations in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (see `Annotation.trim` for details), will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- jam_trimmed : JAMS The trimmed jam with trimmed annotations, returned as a new JAMS object.
jams/core.py
def trim(self, start_time, end_time, strict=False): ''' Trim all the annotations inside the jam and return as a new `JAMS` object. See `Annotation.trim` for details about how the annotations are trimmed. This operation is also documented in the jam-level sandbox with a list keyed by ``JAMS.sandbox.trim`` containing a tuple for each jam-level trim of the form ``(start_time, end_time)``. This function also copies over all of the file metadata from the original jam. Note: trimming does not affect the duration of the jam, i.e. the value of ``JAMS.file_metadata.duration`` will be the same for the original and trimmed jams. Parameters ---------- start_time : float The desired start time for the trimmed annotations in seconds. end_time The desired end time for trimmed annotations in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (see `Annotation.trim` for details), will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- jam_trimmed : JAMS The trimmed jam with trimmed annotations, returned as a new JAMS object. ''' # Make sure duration is set in file metadata if self.file_metadata.duration is None: raise JamsError( 'Duration must be set (jam.file_metadata.duration) before ' 'trimming can be performed.') # Make sure start and end times are within the file start/end times if not (0 <= start_time <= end_time <= float( self.file_metadata.duration)): raise ParameterError( 'start_time and end_time must be within the original file ' 'duration ({:f}) and end_time cannot be smaller than ' 'start_time.'.format(float(self.file_metadata.duration))) # Create a new jams jam_trimmed = JAMS(annotations=None, file_metadata=self.file_metadata, sandbox=self.sandbox) # trim annotations jam_trimmed.annotations = self.annotations.trim( start_time, end_time, strict=strict) # Document jam-level trim in top level sandbox if 'trim' not in jam_trimmed.sandbox.keys(): jam_trimmed.sandbox.update( trim=[{'start_time': start_time, 'end_time': end_time}]) else: jam_trimmed.sandbox.trim.append( {'start_time': start_time, 'end_time': end_time}) return jam_trimmed
def trim(self, start_time, end_time, strict=False): ''' Trim all the annotations inside the jam and return as a new `JAMS` object. See `Annotation.trim` for details about how the annotations are trimmed. This operation is also documented in the jam-level sandbox with a list keyed by ``JAMS.sandbox.trim`` containing a tuple for each jam-level trim of the form ``(start_time, end_time)``. This function also copies over all of the file metadata from the original jam. Note: trimming does not affect the duration of the jam, i.e. the value of ``JAMS.file_metadata.duration`` will be the same for the original and trimmed jams. Parameters ---------- start_time : float The desired start time for the trimmed annotations in seconds. end_time The desired end time for trimmed annotations in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the trimming range (see `Annotation.trim` for details), will have their time and/or duration adjusted such that only the part of the observation that lies within the trim range is kept. When ``True`` such observations are discarded and not included in the trimmed annotation. Returns ------- jam_trimmed : JAMS The trimmed jam with trimmed annotations, returned as a new JAMS object. ''' # Make sure duration is set in file metadata if self.file_metadata.duration is None: raise JamsError( 'Duration must be set (jam.file_metadata.duration) before ' 'trimming can be performed.') # Make sure start and end times are within the file start/end times if not (0 <= start_time <= end_time <= float( self.file_metadata.duration)): raise ParameterError( 'start_time and end_time must be within the original file ' 'duration ({:f}) and end_time cannot be smaller than ' 'start_time.'.format(float(self.file_metadata.duration))) # Create a new jams jam_trimmed = JAMS(annotations=None, file_metadata=self.file_metadata, sandbox=self.sandbox) # trim annotations jam_trimmed.annotations = self.annotations.trim( start_time, end_time, strict=strict) # Document jam-level trim in top level sandbox if 'trim' not in jam_trimmed.sandbox.keys(): jam_trimmed.sandbox.update( trim=[{'start_time': start_time, 'end_time': end_time}]) else: jam_trimmed.sandbox.trim.append( {'start_time': start_time, 'end_time': end_time}) return jam_trimmed
[ "Trim", "all", "the", "annotations", "inside", "the", "jam", "and", "return", "as", "a", "new", "JAMS", "object", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1831-L1903
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b16778399b9528efbd71434842a079f7691a7a66
valid
JAMS.slice
Slice all the annotations inside the jam and return as a new `JAMS` object. See `Annotation.slice` for details about how the annotations are sliced. This operation is also documented in the jam-level sandbox with a list keyed by ``JAMS.sandbox.slice`` containing a tuple for each jam-level slice of the form ``(start_time, end_time)``. Since slicing is implemented using trimming, the operation will also be documented in ``JAMS.sandbox.trim`` as described in `JAMS.trim`. This function also copies over all of the file metadata from the original jam. Note: slicing will affect the duration of the jam, i.e. the new value of ``JAMS.file_metadata.duration`` will be ``end_time - start_time``. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slicing range (see `Annotation.slice` for details), will have their time and/or duration adjusted such that only the part of the observation that lies within the slice range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- jam_sliced: JAMS The sliced jam with sliced annotations, returned as a new JAMS object.
jams/core.py
def slice(self, start_time, end_time, strict=False): ''' Slice all the annotations inside the jam and return as a new `JAMS` object. See `Annotation.slice` for details about how the annotations are sliced. This operation is also documented in the jam-level sandbox with a list keyed by ``JAMS.sandbox.slice`` containing a tuple for each jam-level slice of the form ``(start_time, end_time)``. Since slicing is implemented using trimming, the operation will also be documented in ``JAMS.sandbox.trim`` as described in `JAMS.trim`. This function also copies over all of the file metadata from the original jam. Note: slicing will affect the duration of the jam, i.e. the new value of ``JAMS.file_metadata.duration`` will be ``end_time - start_time``. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slicing range (see `Annotation.slice` for details), will have their time and/or duration adjusted such that only the part of the observation that lies within the slice range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- jam_sliced: JAMS The sliced jam with sliced annotations, returned as a new JAMS object. ''' # Make sure duration is set in file metadata if self.file_metadata.duration is None: raise JamsError( 'Duration must be set (jam.file_metadata.duration) before ' 'slicing can be performed.') # Make sure start and end times are within the file start/end times if (start_time < 0 or start_time > float(self.file_metadata.duration) or end_time < start_time or end_time > float(self.file_metadata.duration)): raise ParameterError( 'start_time and end_time must be within the original file ' 'duration ({:f}) and end_time cannot be smaller than ' 'start_time.'.format(float(self.file_metadata.duration))) # Create a new jams jam_sliced = JAMS(annotations=None, file_metadata=self.file_metadata, sandbox=self.sandbox) # trim annotations jam_sliced.annotations = self.annotations.slice( start_time, end_time, strict=strict) # adjust dutation jam_sliced.file_metadata.duration = end_time - start_time # Document jam-level trim in top level sandbox if 'slice' not in jam_sliced.sandbox.keys(): jam_sliced.sandbox.update( slice=[{'start_time': start_time, 'end_time': end_time}]) else: jam_sliced.sandbox.slice.append( {'start_time': start_time, 'end_time': end_time}) return jam_sliced
def slice(self, start_time, end_time, strict=False): ''' Slice all the annotations inside the jam and return as a new `JAMS` object. See `Annotation.slice` for details about how the annotations are sliced. This operation is also documented in the jam-level sandbox with a list keyed by ``JAMS.sandbox.slice`` containing a tuple for each jam-level slice of the form ``(start_time, end_time)``. Since slicing is implemented using trimming, the operation will also be documented in ``JAMS.sandbox.trim`` as described in `JAMS.trim`. This function also copies over all of the file metadata from the original jam. Note: slicing will affect the duration of the jam, i.e. the new value of ``JAMS.file_metadata.duration`` will be ``end_time - start_time``. Parameters ---------- start_time : float The desired start time for slicing in seconds. end_time The desired end time for slicing in seconds. Must be greater than ``start_time``. strict : bool When ``False`` (default) observations that lie at the boundaries of the slicing range (see `Annotation.slice` for details), will have their time and/or duration adjusted such that only the part of the observation that lies within the slice range is kept. When ``True`` such observations are discarded and not included in the sliced annotation. Returns ------- jam_sliced: JAMS The sliced jam with sliced annotations, returned as a new JAMS object. ''' # Make sure duration is set in file metadata if self.file_metadata.duration is None: raise JamsError( 'Duration must be set (jam.file_metadata.duration) before ' 'slicing can be performed.') # Make sure start and end times are within the file start/end times if (start_time < 0 or start_time > float(self.file_metadata.duration) or end_time < start_time or end_time > float(self.file_metadata.duration)): raise ParameterError( 'start_time and end_time must be within the original file ' 'duration ({:f}) and end_time cannot be smaller than ' 'start_time.'.format(float(self.file_metadata.duration))) # Create a new jams jam_sliced = JAMS(annotations=None, file_metadata=self.file_metadata, sandbox=self.sandbox) # trim annotations jam_sliced.annotations = self.annotations.slice( start_time, end_time, strict=strict) # adjust dutation jam_sliced.file_metadata.duration = end_time - start_time # Document jam-level trim in top level sandbox if 'slice' not in jam_sliced.sandbox.keys(): jam_sliced.sandbox.update( slice=[{'start_time': start_time, 'end_time': end_time}]) else: jam_sliced.sandbox.slice.append( {'start_time': start_time, 'end_time': end_time}) return jam_sliced
[ "Slice", "all", "the", "annotations", "inside", "the", "jam", "and", "return", "as", "a", "new", "JAMS", "object", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/core.py#L1905-L1984
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b16778399b9528efbd71434842a079f7691a7a66
valid
pprint_jobject
Pretty-print a jobject. Parameters ---------- obj : jams.JObject kwargs additional parameters to `json.dumps` Returns ------- string A simplified display of `obj` contents.
jams/display.py
def pprint_jobject(obj, **kwargs): '''Pretty-print a jobject. Parameters ---------- obj : jams.JObject kwargs additional parameters to `json.dumps` Returns ------- string A simplified display of `obj` contents. ''' obj_simple = {k: v for k, v in six.iteritems(obj.__json__) if v} string = json.dumps(obj_simple, **kwargs) # Suppress braces and quotes string = re.sub(r'[{}"]', '', string) # Kill trailing commas string = re.sub(r',\n', '\n', string) # Kill blank lines string = re.sub(r'^\s*$', '', string) return string
def pprint_jobject(obj, **kwargs): '''Pretty-print a jobject. Parameters ---------- obj : jams.JObject kwargs additional parameters to `json.dumps` Returns ------- string A simplified display of `obj` contents. ''' obj_simple = {k: v for k, v in six.iteritems(obj.__json__) if v} string = json.dumps(obj_simple, **kwargs) # Suppress braces and quotes string = re.sub(r'[{}"]', '', string) # Kill trailing commas string = re.sub(r',\n', '\n', string) # Kill blank lines string = re.sub(r'^\s*$', '', string) return string
[ "Pretty", "-", "print", "a", "jobject", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L32-L61
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b16778399b9528efbd71434842a079f7691a7a66
valid
intervals
Plotting wrapper for labeled intervals
jams/display.py
def intervals(annotation, **kwargs): '''Plotting wrapper for labeled intervals''' times, labels = annotation.to_interval_values() return mir_eval.display.labeled_intervals(times, labels, **kwargs)
def intervals(annotation, **kwargs): '''Plotting wrapper for labeled intervals''' times, labels = annotation.to_interval_values() return mir_eval.display.labeled_intervals(times, labels, **kwargs)
[ "Plotting", "wrapper", "for", "labeled", "intervals" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L64-L68
[ "def", "intervals", "(", "annotation", ",", "*", "*", "kwargs", ")", ":", "times", ",", "labels", "=", "annotation", ".", "to_interval_values", "(", ")", "return", "mir_eval", ".", "display", ".", "labeled_intervals", "(", "times", ",", "labels", ",", "*", "*", "kwargs", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
hierarchy
Plotting wrapper for hierarchical segmentations
jams/display.py
def hierarchy(annotation, **kwargs): '''Plotting wrapper for hierarchical segmentations''' htimes, hlabels = hierarchy_flatten(annotation) htimes = [np.asarray(_) for _ in htimes] return mir_eval.display.hierarchy(htimes, hlabels, **kwargs)
def hierarchy(annotation, **kwargs): '''Plotting wrapper for hierarchical segmentations''' htimes, hlabels = hierarchy_flatten(annotation) htimes = [np.asarray(_) for _ in htimes] return mir_eval.display.hierarchy(htimes, hlabels, **kwargs)
[ "Plotting", "wrapper", "for", "hierarchical", "segmentations" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L71-L76
[ "def", "hierarchy", "(", "annotation", ",", "*", "*", "kwargs", ")", ":", "htimes", ",", "hlabels", "=", "hierarchy_flatten", "(", "annotation", ")", "htimes", "=", "[", "np", ".", "asarray", "(", "_", ")", "for", "_", "in", "htimes", "]", "return", "mir_eval", ".", "display", ".", "hierarchy", "(", "htimes", ",", "hlabels", ",", "*", "*", "kwargs", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
pitch_contour
Plotting wrapper for pitch contours
jams/display.py
def pitch_contour(annotation, **kwargs): '''Plotting wrapper for pitch contours''' ax = kwargs.pop('ax', None) # If the annotation is empty, we need to construct a new axes ax = mir_eval.display.__get_axes(ax=ax)[0] times, values = annotation.to_interval_values() indices = np.unique([v['index'] for v in values]) for idx in indices: rows = [i for (i, v) in enumerate(values) if v['index'] == idx] freqs = np.asarray([values[r]['frequency'] for r in rows]) unvoiced = ~np.asarray([values[r]['voiced'] for r in rows]) freqs[unvoiced] *= -1 ax = mir_eval.display.pitch(times[rows, 0], freqs, unvoiced=True, ax=ax, **kwargs) return ax
def pitch_contour(annotation, **kwargs): '''Plotting wrapper for pitch contours''' ax = kwargs.pop('ax', None) # If the annotation is empty, we need to construct a new axes ax = mir_eval.display.__get_axes(ax=ax)[0] times, values = annotation.to_interval_values() indices = np.unique([v['index'] for v in values]) for idx in indices: rows = [i for (i, v) in enumerate(values) if v['index'] == idx] freqs = np.asarray([values[r]['frequency'] for r in rows]) unvoiced = ~np.asarray([values[r]['voiced'] for r in rows]) freqs[unvoiced] *= -1 ax = mir_eval.display.pitch(times[rows, 0], freqs, unvoiced=True, ax=ax, **kwargs) return ax
[ "Plotting", "wrapper", "for", "pitch", "contours" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L79-L99
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b16778399b9528efbd71434842a079f7691a7a66
valid
event
Plotting wrapper for events
jams/display.py
def event(annotation, **kwargs): '''Plotting wrapper for events''' times, values = annotation.to_interval_values() if any(values): labels = values else: labels = None return mir_eval.display.events(times, labels=labels, **kwargs)
def event(annotation, **kwargs): '''Plotting wrapper for events''' times, values = annotation.to_interval_values() if any(values): labels = values else: labels = None return mir_eval.display.events(times, labels=labels, **kwargs)
[ "Plotting", "wrapper", "for", "events" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L102-L112
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b16778399b9528efbd71434842a079f7691a7a66
valid
beat_position
Plotting wrapper for beat-position data
jams/display.py
def beat_position(annotation, **kwargs): '''Plotting wrapper for beat-position data''' times, values = annotation.to_interval_values() labels = [_['position'] for _ in values] # TODO: plot time signature, measure number return mir_eval.display.events(times, labels=labels, **kwargs)
def beat_position(annotation, **kwargs): '''Plotting wrapper for beat-position data''' times, values = annotation.to_interval_values() labels = [_['position'] for _ in values] # TODO: plot time signature, measure number return mir_eval.display.events(times, labels=labels, **kwargs)
[ "Plotting", "wrapper", "for", "beat", "-", "position", "data" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L115-L123
[ "def", "beat_position", "(", "annotation", ",", "*", "*", "kwargs", ")", ":", "times", ",", "values", "=", "annotation", ".", "to_interval_values", "(", ")", "labels", "=", "[", "_", "[", "'position'", "]", "for", "_", "in", "values", "]", "# TODO: plot time signature, measure number", "return", "mir_eval", ".", "display", ".", "events", "(", "times", ",", "labels", "=", "labels", ",", "*", "*", "kwargs", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
piano_roll
Plotting wrapper for piano rolls
jams/display.py
def piano_roll(annotation, **kwargs): '''Plotting wrapper for piano rolls''' times, midi = annotation.to_interval_values() return mir_eval.display.piano_roll(times, midi=midi, **kwargs)
def piano_roll(annotation, **kwargs): '''Plotting wrapper for piano rolls''' times, midi = annotation.to_interval_values() return mir_eval.display.piano_roll(times, midi=midi, **kwargs)
[ "Plotting", "wrapper", "for", "piano", "rolls" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L126-L130
[ "def", "piano_roll", "(", "annotation", ",", "*", "*", "kwargs", ")", ":", "times", ",", "midi", "=", "annotation", ".", "to_interval_values", "(", ")", "return", "mir_eval", ".", "display", ".", "piano_roll", "(", "times", ",", "midi", "=", "midi", ",", "*", "*", "kwargs", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
display
Visualize a jams annotation through mir_eval Parameters ---------- annotation : jams.Annotation The annotation to display meta : bool If `True`, include annotation metadata in the figure kwargs Additional keyword arguments to mir_eval.display functions Returns ------- ax Axis handles for the new display Raises ------ NamespaceError If the annotation cannot be visualized
jams/display.py
def display(annotation, meta=True, **kwargs): '''Visualize a jams annotation through mir_eval Parameters ---------- annotation : jams.Annotation The annotation to display meta : bool If `True`, include annotation metadata in the figure kwargs Additional keyword arguments to mir_eval.display functions Returns ------- ax Axis handles for the new display Raises ------ NamespaceError If the annotation cannot be visualized ''' for namespace, func in six.iteritems(VIZ_MAPPING): try: ann = coerce_annotation(annotation, namespace) axes = func(ann, **kwargs) # Title should correspond to original namespace, not the coerced version axes.set_title(annotation.namespace) if meta: description = pprint_jobject(annotation.annotation_metadata, indent=2) anchored_box = AnchoredText(description.strip('\n'), loc=2, frameon=True, bbox_to_anchor=(1.02, 1.0), bbox_transform=axes.transAxes, borderpad=0.0) axes.add_artist(anchored_box) axes.figure.subplots_adjust(right=0.8) return axes except NamespaceError: pass raise NamespaceError('Unable to visualize annotation of namespace="{:s}"' .format(annotation.namespace))
def display(annotation, meta=True, **kwargs): '''Visualize a jams annotation through mir_eval Parameters ---------- annotation : jams.Annotation The annotation to display meta : bool If `True`, include annotation metadata in the figure kwargs Additional keyword arguments to mir_eval.display functions Returns ------- ax Axis handles for the new display Raises ------ NamespaceError If the annotation cannot be visualized ''' for namespace, func in six.iteritems(VIZ_MAPPING): try: ann = coerce_annotation(annotation, namespace) axes = func(ann, **kwargs) # Title should correspond to original namespace, not the coerced version axes.set_title(annotation.namespace) if meta: description = pprint_jobject(annotation.annotation_metadata, indent=2) anchored_box = AnchoredText(description.strip('\n'), loc=2, frameon=True, bbox_to_anchor=(1.02, 1.0), bbox_transform=axes.transAxes, borderpad=0.0) axes.add_artist(anchored_box) axes.figure.subplots_adjust(right=0.8) return axes except NamespaceError: pass raise NamespaceError('Unable to visualize annotation of namespace="{:s}"' .format(annotation.namespace))
[ "Visualize", "a", "jams", "annotation", "through", "mir_eval" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L146-L197
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b16778399b9528efbd71434842a079f7691a7a66
valid
display_multi
Display multiple annotations with shared axes Parameters ---------- annotations : jams.AnnotationArray A collection of annotations to display fig_kw : dict Keyword arguments to `plt.figure` meta : bool If `True`, display annotation metadata for each annotation kwargs Additional keyword arguments to the `mir_eval.display` routines Returns ------- fig The created figure axs List of subplot axes corresponding to each displayed annotation
jams/display.py
def display_multi(annotations, fig_kw=None, meta=True, **kwargs): '''Display multiple annotations with shared axes Parameters ---------- annotations : jams.AnnotationArray A collection of annotations to display fig_kw : dict Keyword arguments to `plt.figure` meta : bool If `True`, display annotation metadata for each annotation kwargs Additional keyword arguments to the `mir_eval.display` routines Returns ------- fig The created figure axs List of subplot axes corresponding to each displayed annotation ''' if fig_kw is None: fig_kw = dict() fig_kw.setdefault('sharex', True) fig_kw.setdefault('squeeze', True) # Filter down to coercable annotations first display_annotations = [] for ann in annotations: for namespace in VIZ_MAPPING: if can_convert(ann, namespace): display_annotations.append(ann) break # If there are no displayable annotations, fail here if not len(display_annotations): raise ParameterError('No displayable annotations found') fig, axs = plt.subplots(nrows=len(display_annotations), ncols=1, **fig_kw) # MPL is stupid when making singleton subplots. # We catch this and make it always iterable. if len(display_annotations) == 1: axs = [axs] for ann, ax in zip(display_annotations, axs): kwargs['ax'] = ax display(ann, meta=meta, **kwargs) return fig, axs
def display_multi(annotations, fig_kw=None, meta=True, **kwargs): '''Display multiple annotations with shared axes Parameters ---------- annotations : jams.AnnotationArray A collection of annotations to display fig_kw : dict Keyword arguments to `plt.figure` meta : bool If `True`, display annotation metadata for each annotation kwargs Additional keyword arguments to the `mir_eval.display` routines Returns ------- fig The created figure axs List of subplot axes corresponding to each displayed annotation ''' if fig_kw is None: fig_kw = dict() fig_kw.setdefault('sharex', True) fig_kw.setdefault('squeeze', True) # Filter down to coercable annotations first display_annotations = [] for ann in annotations: for namespace in VIZ_MAPPING: if can_convert(ann, namespace): display_annotations.append(ann) break # If there are no displayable annotations, fail here if not len(display_annotations): raise ParameterError('No displayable annotations found') fig, axs = plt.subplots(nrows=len(display_annotations), ncols=1, **fig_kw) # MPL is stupid when making singleton subplots. # We catch this and make it always iterable. if len(display_annotations) == 1: axs = [axs] for ann, ax in zip(display_annotations, axs): kwargs['ax'] = ax display(ann, meta=meta, **kwargs) return fig, axs
[ "Display", "multiple", "annotations", "with", "shared", "axes" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/display.py#L200-L253
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b16778399b9528efbd71434842a079f7691a7a66
valid
mkclick
Generate a click sample. This replicates functionality from mir_eval.sonify.clicks, but exposes the target frequency and duration.
jams/sonify.py
def mkclick(freq, sr=22050, duration=0.1): '''Generate a click sample. This replicates functionality from mir_eval.sonify.clicks, but exposes the target frequency and duration. ''' times = np.arange(int(sr * duration)) click = np.sin(2 * np.pi * times * freq / float(sr)) click *= np.exp(- times / (1e-2 * sr)) return click
def mkclick(freq, sr=22050, duration=0.1): '''Generate a click sample. This replicates functionality from mir_eval.sonify.clicks, but exposes the target frequency and duration. ''' times = np.arange(int(sr * duration)) click = np.sin(2 * np.pi * times * freq / float(sr)) click *= np.exp(- times / (1e-2 * sr)) return click
[ "Generate", "a", "click", "sample", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/sonify.py#L25-L36
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b16778399b9528efbd71434842a079f7691a7a66
valid
clicks
Sonify events with clicks. This uses mir_eval.sonify.clicks, and is appropriate for instantaneous events such as beats or segment boundaries.
jams/sonify.py
def clicks(annotation, sr=22050, length=None, **kwargs): '''Sonify events with clicks. This uses mir_eval.sonify.clicks, and is appropriate for instantaneous events such as beats or segment boundaries. ''' interval, _ = annotation.to_interval_values() return filter_kwargs(mir_eval.sonify.clicks, interval[:, 0], fs=sr, length=length, **kwargs)
def clicks(annotation, sr=22050, length=None, **kwargs): '''Sonify events with clicks. This uses mir_eval.sonify.clicks, and is appropriate for instantaneous events such as beats or segment boundaries. ''' interval, _ = annotation.to_interval_values() return filter_kwargs(mir_eval.sonify.clicks, interval[:, 0], fs=sr, length=length, **kwargs)
[ "Sonify", "events", "with", "clicks", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/sonify.py#L39-L49
[ "def", "clicks", "(", "annotation", ",", "sr", "=", "22050", ",", "length", "=", "None", ",", "*", "*", "kwargs", ")", ":", "interval", ",", "_", "=", "annotation", ".", "to_interval_values", "(", ")", "return", "filter_kwargs", "(", "mir_eval", ".", "sonify", ".", "clicks", ",", "interval", "[", ":", ",", "0", "]", ",", "fs", "=", "sr", ",", "length", "=", "length", ",", "*", "*", "kwargs", ")" ]
b16778399b9528efbd71434842a079f7691a7a66
valid
downbeat
Sonify beats and downbeats together.
jams/sonify.py
def downbeat(annotation, sr=22050, length=None, **kwargs): '''Sonify beats and downbeats together. ''' beat_click = mkclick(440 * 2, sr=sr) downbeat_click = mkclick(440 * 3, sr=sr) intervals, values = annotation.to_interval_values() beats, downbeats = [], [] for time, value in zip(intervals[:, 0], values): if value['position'] == 1: downbeats.append(time) else: beats.append(time) if length is None: length = int(sr * np.max(intervals)) + len(beat_click) + 1 y = filter_kwargs(mir_eval.sonify.clicks, np.asarray(beats), fs=sr, length=length, click=beat_click) y += filter_kwargs(mir_eval.sonify.clicks, np.asarray(downbeats), fs=sr, length=length, click=downbeat_click) return y
def downbeat(annotation, sr=22050, length=None, **kwargs): '''Sonify beats and downbeats together. ''' beat_click = mkclick(440 * 2, sr=sr) downbeat_click = mkclick(440 * 3, sr=sr) intervals, values = annotation.to_interval_values() beats, downbeats = [], [] for time, value in zip(intervals[:, 0], values): if value['position'] == 1: downbeats.append(time) else: beats.append(time) if length is None: length = int(sr * np.max(intervals)) + len(beat_click) + 1 y = filter_kwargs(mir_eval.sonify.clicks, np.asarray(beats), fs=sr, length=length, click=beat_click) y += filter_kwargs(mir_eval.sonify.clicks, np.asarray(downbeats), fs=sr, length=length, click=downbeat_click) return y
[ "Sonify", "beats", "and", "downbeats", "together", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/sonify.py#L52-L80
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b16778399b9528efbd71434842a079f7691a7a66
valid
multi_segment
Sonify multi-level segmentations
jams/sonify.py
def multi_segment(annotation, sr=22050, length=None, **kwargs): '''Sonify multi-level segmentations''' # Pentatonic scale, because why not PENT = [1, 32./27, 4./3, 3./2, 16./9] DURATION = 0.1 h_int, _ = hierarchy_flatten(annotation) if length is None: length = int(sr * (max(np.max(_) for _ in h_int) + 1. / DURATION) + 1) y = 0.0 for ints, (oc, scale) in zip(h_int, product(range(3, 3 + len(h_int)), PENT)): click = mkclick(440.0 * scale * oc, sr=sr, duration=DURATION) y = y + filter_kwargs(mir_eval.sonify.clicks, np.unique(ints), fs=sr, length=length, click=click) return y
def multi_segment(annotation, sr=22050, length=None, **kwargs): '''Sonify multi-level segmentations''' # Pentatonic scale, because why not PENT = [1, 32./27, 4./3, 3./2, 16./9] DURATION = 0.1 h_int, _ = hierarchy_flatten(annotation) if length is None: length = int(sr * (max(np.max(_) for _ in h_int) + 1. / DURATION) + 1) y = 0.0 for ints, (oc, scale) in zip(h_int, product(range(3, 3 + len(h_int)), PENT)): click = mkclick(440.0 * scale * oc, sr=sr, duration=DURATION) y = y + filter_kwargs(mir_eval.sonify.clicks, np.unique(ints), fs=sr, length=length, click=click) return y
[ "Sonify", "multi", "-", "level", "segmentations" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/sonify.py#L83-L103
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b16778399b9528efbd71434842a079f7691a7a66
valid
chord
Sonify chords This uses mir_eval.sonify.chords.
jams/sonify.py
def chord(annotation, sr=22050, length=None, **kwargs): '''Sonify chords This uses mir_eval.sonify.chords. ''' intervals, chords = annotation.to_interval_values() return filter_kwargs(mir_eval.sonify.chords, chords, intervals, fs=sr, length=length, **kwargs)
def chord(annotation, sr=22050, length=None, **kwargs): '''Sonify chords This uses mir_eval.sonify.chords. ''' intervals, chords = annotation.to_interval_values() return filter_kwargs(mir_eval.sonify.chords, chords, intervals, fs=sr, length=length, **kwargs)
[ "Sonify", "chords" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/sonify.py#L106-L117
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b16778399b9528efbd71434842a079f7691a7a66
valid
pitch_contour
Sonify pitch contours. This uses mir_eval.sonify.pitch_contour, and should only be applied to pitch annotations using the pitch_contour namespace. Each contour is sonified independently, and the resulting waveforms are summed together.
jams/sonify.py
def pitch_contour(annotation, sr=22050, length=None, **kwargs): '''Sonify pitch contours. This uses mir_eval.sonify.pitch_contour, and should only be applied to pitch annotations using the pitch_contour namespace. Each contour is sonified independently, and the resulting waveforms are summed together. ''' # Map contours to lists of observations times = defaultdict(list) freqs = defaultdict(list) for obs in annotation: times[obs.value['index']].append(obs.time) freqs[obs.value['index']].append(obs.value['frequency'] * (-1)**(~obs.value['voiced'])) y_out = 0.0 for ix in times: y_out = y_out + filter_kwargs(mir_eval.sonify.pitch_contour, np.asarray(times[ix]), np.asarray(freqs[ix]), fs=sr, length=length, **kwargs) if length is None: length = len(y_out) return y_out
def pitch_contour(annotation, sr=22050, length=None, **kwargs): '''Sonify pitch contours. This uses mir_eval.sonify.pitch_contour, and should only be applied to pitch annotations using the pitch_contour namespace. Each contour is sonified independently, and the resulting waveforms are summed together. ''' # Map contours to lists of observations times = defaultdict(list) freqs = defaultdict(list) for obs in annotation: times[obs.value['index']].append(obs.time) freqs[obs.value['index']].append(obs.value['frequency'] * (-1)**(~obs.value['voiced'])) y_out = 0.0 for ix in times: y_out = y_out + filter_kwargs(mir_eval.sonify.pitch_contour, np.asarray(times[ix]), np.asarray(freqs[ix]), fs=sr, length=length, **kwargs) if length is None: length = len(y_out) return y_out
[ "Sonify", "pitch", "contours", "." ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/sonify.py#L120-L150
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b16778399b9528efbd71434842a079f7691a7a66
valid
piano_roll
Sonify a piano-roll This uses mir_eval.sonify.time_frequency, and is appropriate for sparse transcription data, e.g., annotations in the `note_midi` namespace.
jams/sonify.py
def piano_roll(annotation, sr=22050, length=None, **kwargs): '''Sonify a piano-roll This uses mir_eval.sonify.time_frequency, and is appropriate for sparse transcription data, e.g., annotations in the `note_midi` namespace. ''' intervals, pitches = annotation.to_interval_values() # Construct the pitchogram pitch_map = {f: idx for idx, f in enumerate(np.unique(pitches))} gram = np.zeros((len(pitch_map), len(intervals))) for col, f in enumerate(pitches): gram[pitch_map[f], col] = 1 return filter_kwargs(mir_eval.sonify.time_frequency, gram, pitches, intervals, sr, length=length, **kwargs)
def piano_roll(annotation, sr=22050, length=None, **kwargs): '''Sonify a piano-roll This uses mir_eval.sonify.time_frequency, and is appropriate for sparse transcription data, e.g., annotations in the `note_midi` namespace. ''' intervals, pitches = annotation.to_interval_values() # Construct the pitchogram pitch_map = {f: idx for idx, f in enumerate(np.unique(pitches))} gram = np.zeros((len(pitch_map), len(intervals))) for col, f in enumerate(pitches): gram[pitch_map[f], col] = 1 return filter_kwargs(mir_eval.sonify.time_frequency, gram, pitches, intervals, sr, length=length, **kwargs)
[ "Sonify", "a", "piano", "-", "roll" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/sonify.py#L153-L173
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b16778399b9528efbd71434842a079f7691a7a66
valid
sonify
Sonify a jams annotation through mir_eval Parameters ---------- annotation : jams.Annotation The annotation to sonify sr = : positive number The sampling rate of the output waveform duration : float (optional) Optional length (in seconds) of the output waveform kwargs Additional keyword arguments to mir_eval.sonify functions Returns ------- y_sonified : np.ndarray The waveform of the sonified annotation Raises ------ NamespaceError If the annotation has an un-sonifiable namespace
jams/sonify.py
def sonify(annotation, sr=22050, duration=None, **kwargs): '''Sonify a jams annotation through mir_eval Parameters ---------- annotation : jams.Annotation The annotation to sonify sr = : positive number The sampling rate of the output waveform duration : float (optional) Optional length (in seconds) of the output waveform kwargs Additional keyword arguments to mir_eval.sonify functions Returns ------- y_sonified : np.ndarray The waveform of the sonified annotation Raises ------ NamespaceError If the annotation has an un-sonifiable namespace ''' length = None if duration is None: duration = annotation.duration if duration is not None: length = int(duration * sr) # If the annotation can be directly sonified, try that first if annotation.namespace in SONIFY_MAPPING: ann = coerce_annotation(annotation, annotation.namespace) return SONIFY_MAPPING[annotation.namespace](ann, sr=sr, length=length, **kwargs) for namespace, func in six.iteritems(SONIFY_MAPPING): try: ann = coerce_annotation(annotation, namespace) return func(ann, sr=sr, length=length, **kwargs) except NamespaceError: pass raise NamespaceError('Unable to sonify annotation of namespace="{:s}"' .format(annotation.namespace))
def sonify(annotation, sr=22050, duration=None, **kwargs): '''Sonify a jams annotation through mir_eval Parameters ---------- annotation : jams.Annotation The annotation to sonify sr = : positive number The sampling rate of the output waveform duration : float (optional) Optional length (in seconds) of the output waveform kwargs Additional keyword arguments to mir_eval.sonify functions Returns ------- y_sonified : np.ndarray The waveform of the sonified annotation Raises ------ NamespaceError If the annotation has an un-sonifiable namespace ''' length = None if duration is None: duration = annotation.duration if duration is not None: length = int(duration * sr) # If the annotation can be directly sonified, try that first if annotation.namespace in SONIFY_MAPPING: ann = coerce_annotation(annotation, annotation.namespace) return SONIFY_MAPPING[annotation.namespace](ann, sr=sr, length=length, **kwargs) for namespace, func in six.iteritems(SONIFY_MAPPING): try: ann = coerce_annotation(annotation, namespace) return func(ann, sr=sr, length=length, **kwargs) except NamespaceError: pass raise NamespaceError('Unable to sonify annotation of namespace="{:s}"' .format(annotation.namespace))
[ "Sonify", "a", "jams", "annotation", "through", "mir_eval" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/sonify.py#L187-L239
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b16778399b9528efbd71434842a079f7691a7a66
valid
validate
Validate a jams file against a schema
jams/schemata/validate.py
def validate(schema_file=None, jams_files=None): '''Validate a jams file against a schema''' schema = load_json(schema_file) for jams_file in jams_files: try: jams = load_json(jams_file) jsonschema.validate(jams, schema) print '{:s} was successfully validated'.format(jams_file) except jsonschema.ValidationError as exc: print '{:s} was NOT successfully validated'.format(jams_file) print exc
def validate(schema_file=None, jams_files=None): '''Validate a jams file against a schema''' schema = load_json(schema_file) for jams_file in jams_files: try: jams = load_json(jams_file) jsonschema.validate(jams, schema) print '{:s} was successfully validated'.format(jams_file) except jsonschema.ValidationError as exc: print '{:s} was NOT successfully validated'.format(jams_file) print exc
[ "Validate", "a", "jams", "file", "against", "a", "schema" ]
marl/jams
python
https://github.com/marl/jams/blob/b16778399b9528efbd71434842a079f7691a7a66/jams/schemata/validate.py#L31-L44
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b16778399b9528efbd71434842a079f7691a7a66
valid
StreamSASLHandler.make_stream_features
Add SASL features to the <features/> element of the stream. [receving entity only] :returns: update <features/> element.
pyxmpp2/streamsasl.py
def make_stream_features(self, stream, features): """Add SASL features to the <features/> element of the stream. [receving entity only] :returns: update <features/> element.""" mechs = self.settings['sasl_mechanisms'] if mechs and not stream.authenticated: sub = ElementTree.SubElement(features, MECHANISMS_TAG) for mech in mechs: if mech in sasl.SERVER_MECHANISMS: ElementTree.SubElement(sub, MECHANISM_TAG).text = mech return features
def make_stream_features(self, stream, features): """Add SASL features to the <features/> element of the stream. [receving entity only] :returns: update <features/> element.""" mechs = self.settings['sasl_mechanisms'] if mechs and not stream.authenticated: sub = ElementTree.SubElement(features, MECHANISMS_TAG) for mech in mechs: if mech in sasl.SERVER_MECHANISMS: ElementTree.SubElement(sub, MECHANISM_TAG).text = mech return features
[ "Add", "SASL", "features", "to", "the", "<features", "/", ">", "element", "of", "the", "stream", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L98-L110
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler.handle_stream_features
Process incoming <stream:features/> element. [initiating entity only]
pyxmpp2/streamsasl.py
def handle_stream_features(self, stream, features): """Process incoming <stream:features/> element. [initiating entity only] """ element = features.find(MECHANISMS_TAG) self.peer_sasl_mechanisms = [] if element is None: return None for sub in element: if sub.tag != MECHANISM_TAG: continue self.peer_sasl_mechanisms.append(sub.text) if stream.authenticated or not self.peer_sasl_mechanisms: return StreamFeatureNotHandled("SASL", mandatory = True) username = self.settings.get("username") if not username: # TODO: other rules for s2s if stream.me.local: username = stream.me.local else: username = None self._sasl_authenticate(stream, username, self.settings.get("authzid")) return StreamFeatureHandled("SASL", mandatory = True)
def handle_stream_features(self, stream, features): """Process incoming <stream:features/> element. [initiating entity only] """ element = features.find(MECHANISMS_TAG) self.peer_sasl_mechanisms = [] if element is None: return None for sub in element: if sub.tag != MECHANISM_TAG: continue self.peer_sasl_mechanisms.append(sub.text) if stream.authenticated or not self.peer_sasl_mechanisms: return StreamFeatureNotHandled("SASL", mandatory = True) username = self.settings.get("username") if not username: # TODO: other rules for s2s if stream.me.local: username = stream.me.local else: username = None self._sasl_authenticate(stream, username, self.settings.get("authzid")) return StreamFeatureHandled("SASL", mandatory = True)
[ "Process", "incoming", "<stream", ":", "features", "/", ">", "element", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L112-L137
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler.process_sasl_auth
Process incoming <sasl:auth/> element. [receiving entity only]
pyxmpp2/streamsasl.py
def process_sasl_auth(self, stream, element): """Process incoming <sasl:auth/> element. [receiving entity only] """ if self.authenticator: logger.debug("Authentication already started") return False password_db = self.settings["password_database"] mechanism = element.get("mechanism") if not mechanism: stream.send_stream_error("bad-format") raise FatalStreamError("<sasl:auth/> with no mechanism") stream.auth_method_used = mechanism self.authenticator = sasl.server_authenticator_factory(mechanism, password_db) content = element.text.encode("us-ascii") ret = self.authenticator.start(stream.auth_properties, a2b_base64(content)) if isinstance(ret, sasl.Success): element = ElementTree.Element(SUCCESS_TAG) element.text = ret.encode() elif isinstance(ret, sasl.Challenge): element = ElementTree.Element(CHALLENGE_TAG) element.text = ret.encode() else: element = ElementTree.Element(FAILURE_TAG) ElementTree.SubElement(element, SASL_QNP + ret.reason) stream.write_element(element) if isinstance(ret, sasl.Success): self._handle_auth_success(stream, ret) elif isinstance(ret, sasl.Failure): raise SASLAuthenticationFailed("SASL authentication failed: {0}" .format(ret.reason)) return True
def process_sasl_auth(self, stream, element): """Process incoming <sasl:auth/> element. [receiving entity only] """ if self.authenticator: logger.debug("Authentication already started") return False password_db = self.settings["password_database"] mechanism = element.get("mechanism") if not mechanism: stream.send_stream_error("bad-format") raise FatalStreamError("<sasl:auth/> with no mechanism") stream.auth_method_used = mechanism self.authenticator = sasl.server_authenticator_factory(mechanism, password_db) content = element.text.encode("us-ascii") ret = self.authenticator.start(stream.auth_properties, a2b_base64(content)) if isinstance(ret, sasl.Success): element = ElementTree.Element(SUCCESS_TAG) element.text = ret.encode() elif isinstance(ret, sasl.Challenge): element = ElementTree.Element(CHALLENGE_TAG) element.text = ret.encode() else: element = ElementTree.Element(FAILURE_TAG) ElementTree.SubElement(element, SASL_QNP + ret.reason) stream.write_element(element) if isinstance(ret, sasl.Success): self._handle_auth_success(stream, ret) elif isinstance(ret, sasl.Failure): raise SASLAuthenticationFailed("SASL authentication failed: {0}" .format(ret.reason)) return True
[ "Process", "incoming", "<sasl", ":", "auth", "/", ">", "element", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L140-L180
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler._handle_auth_success
Handle successful authentication. Send <success/> and mark the stream peer authenticated. [receiver only]
pyxmpp2/streamsasl.py
def _handle_auth_success(self, stream, success): """Handle successful authentication. Send <success/> and mark the stream peer authenticated. [receiver only] """ if not self._check_authorization(success.properties, stream): element = ElementTree.Element(FAILURE_TAG) ElementTree.SubElement(element, SASL_QNP + "invalid-authzid") return True authzid = success.properties.get("authzid") if authzid: peer = JID(success.authzid) elif "username" in success.properties: peer = JID(success.properties["username"], stream.me.domain) else: # anonymous peer = None stream.set_peer_authenticated(peer, True)
def _handle_auth_success(self, stream, success): """Handle successful authentication. Send <success/> and mark the stream peer authenticated. [receiver only] """ if not self._check_authorization(success.properties, stream): element = ElementTree.Element(FAILURE_TAG) ElementTree.SubElement(element, SASL_QNP + "invalid-authzid") return True authzid = success.properties.get("authzid") if authzid: peer = JID(success.authzid) elif "username" in success.properties: peer = JID(success.properties["username"], stream.me.domain) else: # anonymous peer = None stream.set_peer_authenticated(peer, True)
[ "Handle", "successful", "authentication", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L182-L201
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler._process_sasl_challenge
Process incoming <sasl:challenge/> element. [initiating entity only]
pyxmpp2/streamsasl.py
def _process_sasl_challenge(self, stream, element): """Process incoming <sasl:challenge/> element. [initiating entity only] """ if not self.authenticator: logger.debug("Unexpected SASL challenge") return False content = element.text.encode("us-ascii") ret = self.authenticator.challenge(a2b_base64(content)) if isinstance(ret, sasl.Response): element = ElementTree.Element(RESPONSE_TAG) element.text = ret.encode() else: element = ElementTree.Element(ABORT_TAG) stream.write_element(element) if isinstance(ret, sasl.Failure): stream.disconnect() raise SASLAuthenticationFailed("SASL authentication failed") return True
def _process_sasl_challenge(self, stream, element): """Process incoming <sasl:challenge/> element. [initiating entity only] """ if not self.authenticator: logger.debug("Unexpected SASL challenge") return False content = element.text.encode("us-ascii") ret = self.authenticator.challenge(a2b_base64(content)) if isinstance(ret, sasl.Response): element = ElementTree.Element(RESPONSE_TAG) element.text = ret.encode() else: element = ElementTree.Element(ABORT_TAG) stream.write_element(element) if isinstance(ret, sasl.Failure): stream.disconnect() raise SASLAuthenticationFailed("SASL authentication failed") return True
[ "Process", "incoming", "<sasl", ":", "challenge", "/", ">", "element", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L204-L227
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler._process_sasl_response
Process incoming <sasl:response/> element. [receiving entity only]
pyxmpp2/streamsasl.py
def _process_sasl_response(self, stream, element): """Process incoming <sasl:response/> element. [receiving entity only] """ if not self.authenticator: logger.debug("Unexpected SASL response") return False content = element.text.encode("us-ascii") ret = self.authenticator.response(a2b_base64(content)) if isinstance(ret, sasl.Success): element = ElementTree.Element(SUCCESS_TAG) element.text = ret.encode() elif isinstance(ret, sasl.Challenge): element = ElementTree.Element(CHALLENGE_TAG) element.text = ret.encode() else: element = ElementTree.Element(FAILURE_TAG) ElementTree.SubElement(element, SASL_QNP + ret.reason) stream.write_element(element) if isinstance(ret, sasl.Success): self._handle_auth_success(stream, ret) elif isinstance(ret, sasl.Failure): raise SASLAuthenticationFailed("SASL authentication failed: {0!r}" .format(ret.reson)) return True
def _process_sasl_response(self, stream, element): """Process incoming <sasl:response/> element. [receiving entity only] """ if not self.authenticator: logger.debug("Unexpected SASL response") return False content = element.text.encode("us-ascii") ret = self.authenticator.response(a2b_base64(content)) if isinstance(ret, sasl.Success): element = ElementTree.Element(SUCCESS_TAG) element.text = ret.encode() elif isinstance(ret, sasl.Challenge): element = ElementTree.Element(CHALLENGE_TAG) element.text = ret.encode() else: element = ElementTree.Element(FAILURE_TAG) ElementTree.SubElement(element, SASL_QNP + ret.reason) stream.write_element(element) if isinstance(ret, sasl.Success): self._handle_auth_success(stream, ret) elif isinstance(ret, sasl.Failure): raise SASLAuthenticationFailed("SASL authentication failed: {0!r}" .format(ret.reson)) return True
[ "Process", "incoming", "<sasl", ":", "response", "/", ">", "element", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L230-L258
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler._check_authorization
Check authorization id and other properties returned by the authentication mechanism. [receiving entity only] Allow only no authzid or authzid equal to current username@domain FIXME: other rules in s2s :Parameters: - `properties`: data obtained during authentication :Types: - `properties`: mapping :return: `True` if user is authorized to use a provided authzid :returntype: `bool`
pyxmpp2/streamsasl.py
def _check_authorization(self, properties, stream): """Check authorization id and other properties returned by the authentication mechanism. [receiving entity only] Allow only no authzid or authzid equal to current username@domain FIXME: other rules in s2s :Parameters: - `properties`: data obtained during authentication :Types: - `properties`: mapping :return: `True` if user is authorized to use a provided authzid :returntype: `bool` """ authzid = properties.get("authzid") if not authzid: return True try: jid = JID(authzid) except ValueError: return False if "username" not in properties: result = False elif jid.local != properties["username"]: result = False elif jid.domain != stream.me.domain: result = False elif jid.resource: result = False else: result = True return result
def _check_authorization(self, properties, stream): """Check authorization id and other properties returned by the authentication mechanism. [receiving entity only] Allow only no authzid or authzid equal to current username@domain FIXME: other rules in s2s :Parameters: - `properties`: data obtained during authentication :Types: - `properties`: mapping :return: `True` if user is authorized to use a provided authzid :returntype: `bool` """ authzid = properties.get("authzid") if not authzid: return True try: jid = JID(authzid) except ValueError: return False if "username" not in properties: result = False elif jid.local != properties["username"]: result = False elif jid.domain != stream.me.domain: result = False elif jid.resource: result = False else: result = True return result
[ "Check", "authorization", "id", "and", "other", "properties", "returned", "by", "the", "authentication", "mechanism", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L260-L296
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler._process_sasl_success
Process incoming <sasl:success/> element. [initiating entity only]
pyxmpp2/streamsasl.py
def _process_sasl_success(self, stream, element): """Process incoming <sasl:success/> element. [initiating entity only] """ if not self.authenticator: logger.debug("Unexpected SASL response") return False content = element.text if content: data = a2b_base64(content.encode("us-ascii")) else: data = None ret = self.authenticator.finish(data) if isinstance(ret, sasl.Success): logger.debug("SASL authentication succeeded") authzid = ret.properties.get("authzid") if authzid: me = JID(authzid) elif "username" in ret.properties: # FIXME: other rules for server me = JID(ret.properties["username"], stream.peer.domain) else: me = None stream.set_authenticated(me, True) else: logger.debug("SASL authentication failed") raise SASLAuthenticationFailed("Additional success data" " procesing failed") return True
def _process_sasl_success(self, stream, element): """Process incoming <sasl:success/> element. [initiating entity only] """ if not self.authenticator: logger.debug("Unexpected SASL response") return False content = element.text if content: data = a2b_base64(content.encode("us-ascii")) else: data = None ret = self.authenticator.finish(data) if isinstance(ret, sasl.Success): logger.debug("SASL authentication succeeded") authzid = ret.properties.get("authzid") if authzid: me = JID(authzid) elif "username" in ret.properties: # FIXME: other rules for server me = JID(ret.properties["username"], stream.peer.domain) else: me = None stream.set_authenticated(me, True) else: logger.debug("SASL authentication failed") raise SASLAuthenticationFailed("Additional success data" " procesing failed") return True
[ "Process", "incoming", "<sasl", ":", "success", "/", ">", "element", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L299-L331
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler._process_sasl_failure
Process incoming <sasl:failure/> element. [initiating entity only]
pyxmpp2/streamsasl.py
def _process_sasl_failure(self, stream, element): """Process incoming <sasl:failure/> element. [initiating entity only] """ _unused = stream if not self.authenticator: logger.debug("Unexpected SASL response") return False logger.debug("SASL authentication failed: {0!r}".format( element_to_unicode(element))) raise SASLAuthenticationFailed("SASL authentication failed")
def _process_sasl_failure(self, stream, element): """Process incoming <sasl:failure/> element. [initiating entity only] """ _unused = stream if not self.authenticator: logger.debug("Unexpected SASL response") return False logger.debug("SASL authentication failed: {0!r}".format( element_to_unicode(element))) raise SASLAuthenticationFailed("SASL authentication failed")
[ "Process", "incoming", "<sasl", ":", "failure", "/", ">", "element", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L334-L346
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler._process_sasl_abort
Process incoming <sasl:abort/> element. [receiving entity only]
pyxmpp2/streamsasl.py
def _process_sasl_abort(self, stream, element): """Process incoming <sasl:abort/> element. [receiving entity only]""" _unused, _unused = stream, element if not self.authenticator: logger.debug("Unexpected SASL response") return False self.authenticator = None logger.debug("SASL authentication aborted") return True
def _process_sasl_abort(self, stream, element): """Process incoming <sasl:abort/> element. [receiving entity only]""" _unused, _unused = stream, element if not self.authenticator: logger.debug("Unexpected SASL response") return False self.authenticator = None logger.debug("SASL authentication aborted") return True
[ "Process", "incoming", "<sasl", ":", "abort", "/", ">", "element", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L349-L360
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
StreamSASLHandler._sasl_authenticate
Start SASL authentication process. [initiating entity only] :Parameters: - `username`: user name. - `authzid`: authorization ID. - `mechanism`: SASL mechanism to use.
pyxmpp2/streamsasl.py
def _sasl_authenticate(self, stream, username, authzid): """Start SASL authentication process. [initiating entity only] :Parameters: - `username`: user name. - `authzid`: authorization ID. - `mechanism`: SASL mechanism to use.""" if not stream.initiator: raise SASLAuthenticationFailed("Only initiating entity start" " SASL authentication") if stream.features is None or not self.peer_sasl_mechanisms: raise SASLNotAvailable("Peer doesn't support SASL") props = dict(stream.auth_properties) if not props.get("service-domain") and ( stream.peer and stream.peer.domain): props["service-domain"] = stream.peer.domain if username is not None: props["username"] = username if authzid is not None: props["authzid"] = authzid if "password" in self.settings: props["password"] = self.settings["password"] props["available_mechanisms"] = self.peer_sasl_mechanisms enabled = sasl.filter_mechanism_list( self.settings['sasl_mechanisms'], props, self.settings['insecure_auth']) if not enabled: raise SASLNotAvailable( "None of SASL mechanism selected can be used") props["enabled_mechanisms"] = enabled mechanism = None for mech in enabled: if mech in self.peer_sasl_mechanisms: mechanism = mech break if not mechanism: raise SASLMechanismNotAvailable("Peer doesn't support any of" " our SASL mechanisms") logger.debug("Our mechanism: {0!r}".format(mechanism)) stream.auth_method_used = mechanism self.authenticator = sasl.client_authenticator_factory(mechanism) initial_response = self.authenticator.start(props) if not isinstance(initial_response, sasl.Response): raise SASLAuthenticationFailed("SASL initiation failed") element = ElementTree.Element(AUTH_TAG) element.set("mechanism", mechanism) if initial_response.data: if initial_response.encode: element.text = initial_response.encode() else: element.text = initial_response.data stream.write_element(element)
def _sasl_authenticate(self, stream, username, authzid): """Start SASL authentication process. [initiating entity only] :Parameters: - `username`: user name. - `authzid`: authorization ID. - `mechanism`: SASL mechanism to use.""" if not stream.initiator: raise SASLAuthenticationFailed("Only initiating entity start" " SASL authentication") if stream.features is None or not self.peer_sasl_mechanisms: raise SASLNotAvailable("Peer doesn't support SASL") props = dict(stream.auth_properties) if not props.get("service-domain") and ( stream.peer and stream.peer.domain): props["service-domain"] = stream.peer.domain if username is not None: props["username"] = username if authzid is not None: props["authzid"] = authzid if "password" in self.settings: props["password"] = self.settings["password"] props["available_mechanisms"] = self.peer_sasl_mechanisms enabled = sasl.filter_mechanism_list( self.settings['sasl_mechanisms'], props, self.settings['insecure_auth']) if not enabled: raise SASLNotAvailable( "None of SASL mechanism selected can be used") props["enabled_mechanisms"] = enabled mechanism = None for mech in enabled: if mech in self.peer_sasl_mechanisms: mechanism = mech break if not mechanism: raise SASLMechanismNotAvailable("Peer doesn't support any of" " our SASL mechanisms") logger.debug("Our mechanism: {0!r}".format(mechanism)) stream.auth_method_used = mechanism self.authenticator = sasl.client_authenticator_factory(mechanism) initial_response = self.authenticator.start(props) if not isinstance(initial_response, sasl.Response): raise SASLAuthenticationFailed("SASL initiation failed") element = ElementTree.Element(AUTH_TAG) element.set("mechanism", mechanism) if initial_response.data: if initial_response.encode: element.text = initial_response.encode() else: element.text = initial_response.data stream.write_element(element)
[ "Start", "SASL", "authentication", "process", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/streamsasl.py#L362-L419
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
timeout_handler
Method decorator generator for decorating event handlers. To be used on `TimeoutHandler` subclass methods only. :Parameters: - `interval`: interval (in seconds) before the method will be called. - `recurring`: When `True`, the handler will be called each `interval` seconds, when `False` it will be called only once. If `True`, then the handler should return the next interval or `None` if it should not be called again. :Types: - `interval`: `float` - `recurring`: `bool`
pyxmpp2/mainloop/interfaces.py
def timeout_handler(interval, recurring = None): """Method decorator generator for decorating event handlers. To be used on `TimeoutHandler` subclass methods only. :Parameters: - `interval`: interval (in seconds) before the method will be called. - `recurring`: When `True`, the handler will be called each `interval` seconds, when `False` it will be called only once. If `True`, then the handler should return the next interval or `None` if it should not be called again. :Types: - `interval`: `float` - `recurring`: `bool` """ def decorator(func): """The decorator""" func._pyxmpp_timeout = interval func._pyxmpp_recurring = recurring return func return decorator
def timeout_handler(interval, recurring = None): """Method decorator generator for decorating event handlers. To be used on `TimeoutHandler` subclass methods only. :Parameters: - `interval`: interval (in seconds) before the method will be called. - `recurring`: When `True`, the handler will be called each `interval` seconds, when `False` it will be called only once. If `True`, then the handler should return the next interval or `None` if it should not be called again. :Types: - `interval`: `float` - `recurring`: `bool` """ def decorator(func): """The decorator""" func._pyxmpp_timeout = interval func._pyxmpp_recurring = recurring return func return decorator
[ "Method", "decorator", "generator", "for", "decorating", "event", "handlers", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/mainloop/interfaces.py#L214-L234
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
MainLoop.delayed_call
Schedule function to be called from the main loop after `delay` seconds. :Parameters: - `delay`: seconds to wait :Types: - `delay`: `float`
pyxmpp2/mainloop/interfaces.py
def delayed_call(self, delay, function): """Schedule function to be called from the main loop after `delay` seconds. :Parameters: - `delay`: seconds to wait :Types: - `delay`: `float` """ main_loop = self handler = [] class DelayedCallHandler(TimeoutHandler): """Wrapper timeout handler class for the delayed call.""" # pylint: disable=R0903 @timeout_handler(delay, False) def callback(self): """Wrapper timeout handler method for the delayed call.""" try: function() finally: main_loop.remove_handler(handler[0]) handler.append(DelayedCallHandler()) self.add_handler(handler[0])
def delayed_call(self, delay, function): """Schedule function to be called from the main loop after `delay` seconds. :Parameters: - `delay`: seconds to wait :Types: - `delay`: `float` """ main_loop = self handler = [] class DelayedCallHandler(TimeoutHandler): """Wrapper timeout handler class for the delayed call.""" # pylint: disable=R0903 @timeout_handler(delay, False) def callback(self): """Wrapper timeout handler method for the delayed call.""" try: function() finally: main_loop.remove_handler(handler[0]) handler.append(DelayedCallHandler()) self.add_handler(handler[0])
[ "Schedule", "function", "to", "be", "called", "from", "the", "main", "loop", "after", "delay", "seconds", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/mainloop/interfaces.py#L264-L286
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
RosterItem.from_xml
Make a RosterItem from an XML element. :Parameters: - `element`: the XML element :Types: - `element`: :etree:`ElementTree.Element` :return: a freshly created roster item :returntype: `cls`
pyxmpp2/roster.py
def from_xml(cls, element): """Make a RosterItem from an XML element. :Parameters: - `element`: the XML element :Types: - `element`: :etree:`ElementTree.Element` :return: a freshly created roster item :returntype: `cls` """ if element.tag != ITEM_TAG: raise ValueError("{0!r} is not a roster item".format(element)) try: jid = JID(element.get("jid")) except ValueError: raise BadRequestProtocolError(u"Bad item JID") subscription = element.get("subscription") ask = element.get("ask") name = element.get("name") duplicate_group = False groups = set() for child in element: if child.tag != GROUP_TAG: continue group = child.text if group is None: group = u"" if group in groups: duplicate_group = True else: groups.add(group) approved = element.get("approved") if approved == "true": approved = True elif approved in ("false", None): approved = False else: logger.debug("RosterItem.from_xml: got unknown 'approved':" " {0!r}, changing to False".format(approved)) approved = False result = cls(jid, name, groups, subscription, ask, approved) result._duplicate_group = duplicate_group return result
def from_xml(cls, element): """Make a RosterItem from an XML element. :Parameters: - `element`: the XML element :Types: - `element`: :etree:`ElementTree.Element` :return: a freshly created roster item :returntype: `cls` """ if element.tag != ITEM_TAG: raise ValueError("{0!r} is not a roster item".format(element)) try: jid = JID(element.get("jid")) except ValueError: raise BadRequestProtocolError(u"Bad item JID") subscription = element.get("subscription") ask = element.get("ask") name = element.get("name") duplicate_group = False groups = set() for child in element: if child.tag != GROUP_TAG: continue group = child.text if group is None: group = u"" if group in groups: duplicate_group = True else: groups.add(group) approved = element.get("approved") if approved == "true": approved = True elif approved in ("false", None): approved = False else: logger.debug("RosterItem.from_xml: got unknown 'approved':" " {0!r}, changing to False".format(approved)) approved = False result = cls(jid, name, groups, subscription, ask, approved) result._duplicate_group = duplicate_group return result
[ "Make", "a", "RosterItem", "from", "an", "XML", "element", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/roster.py#L192-L235
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
RosterItem.as_xml
Make an XML element from self. :Parameters: - `parent`: Parent element :Types: - `parent`: :etree:`ElementTree.Element`
pyxmpp2/roster.py
def as_xml(self, parent = None): """Make an XML element from self. :Parameters: - `parent`: Parent element :Types: - `parent`: :etree:`ElementTree.Element` """ if parent is not None: element = ElementTree.SubElement(parent, ITEM_TAG) else: element = ElementTree.Element(ITEM_TAG) element.set("jid", unicode(self.jid)) if self.name is not None: element.set("name", self.name) if self.subscription is not None: element.set("subscription", self.subscription) if self.ask: element.set("ask", self.ask) if self.approved: element.set("approved", "true") for group in self.groups: ElementTree.SubElement(element, GROUP_TAG).text = group return element
def as_xml(self, parent = None): """Make an XML element from self. :Parameters: - `parent`: Parent element :Types: - `parent`: :etree:`ElementTree.Element` """ if parent is not None: element = ElementTree.SubElement(parent, ITEM_TAG) else: element = ElementTree.Element(ITEM_TAG) element.set("jid", unicode(self.jid)) if self.name is not None: element.set("name", self.name) if self.subscription is not None: element.set("subscription", self.subscription) if self.ask: element.set("ask", self.ask) if self.approved: element.set("approved", "true") for group in self.groups: ElementTree.SubElement(element, GROUP_TAG).text = group return element
[ "Make", "an", "XML", "element", "from", "self", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/roster.py#L237-L260
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
RosterItem._verify
Check if `self` is valid roster item. Valid item must have proper `subscription` and valid value for 'ask'. :Parameters: - `valid_subscriptions`: sequence of valid subscription values - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid.
pyxmpp2/roster.py
def _verify(self, valid_subscriptions, fix): """Check if `self` is valid roster item. Valid item must have proper `subscription` and valid value for 'ask'. :Parameters: - `valid_subscriptions`: sequence of valid subscription values - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid. """ if self.subscription not in valid_subscriptions: if fix: logger.debug("RosterItem.from_xml: got unknown 'subscription':" " {0!r}, changing to None".format(self.subscription)) self.subscription = None else: raise ValueError("Bad 'subscription'") if self.ask not in (None, u"subscribe"): if fix: logger.debug("RosterItem.from_xml: got unknown 'ask':" " {0!r}, changing to None".format(self.ask)) self.ask = None else: raise ValueError("Bad 'ask'")
def _verify(self, valid_subscriptions, fix): """Check if `self` is valid roster item. Valid item must have proper `subscription` and valid value for 'ask'. :Parameters: - `valid_subscriptions`: sequence of valid subscription values - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid. """ if self.subscription not in valid_subscriptions: if fix: logger.debug("RosterItem.from_xml: got unknown 'subscription':" " {0!r}, changing to None".format(self.subscription)) self.subscription = None else: raise ValueError("Bad 'subscription'") if self.ask not in (None, u"subscribe"): if fix: logger.debug("RosterItem.from_xml: got unknown 'ask':" " {0!r}, changing to None".format(self.ask)) self.ask = None else: raise ValueError("Bad 'ask'")
[ "Check", "if", "self", "is", "valid", "roster", "item", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/roster.py#L262-L289
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
RosterItem.verify_roster_result
Check if `self` is valid roster item. Valid item must have proper `subscription` value other than 'remove' and valid value for 'ask'. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid.
pyxmpp2/roster.py
def verify_roster_result(self, fix = False): """Check if `self` is valid roster item. Valid item must have proper `subscription` value other than 'remove' and valid value for 'ask'. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid. """ self._verify((None, u"from", u"to", u"both"), fix)
def verify_roster_result(self, fix = False): """Check if `self` is valid roster item. Valid item must have proper `subscription` value other than 'remove' and valid value for 'ask'. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid. """ self._verify((None, u"from", u"to", u"both"), fix)
[ "Check", "if", "self", "is", "valid", "roster", "item", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/roster.py#L291-L305
[ "def", "verify_roster_result", "(", "self", ",", "fix", "=", "False", ")", ":", "self", ".", "_verify", "(", "(", "None", ",", "u\"from\"", ",", "u\"to\"", ",", "u\"both\"", ")", ",", "fix", ")" ]
14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
RosterItem.verify_roster_push
Check if `self` is valid roster push item. Valid item must have proper `subscription` value other and valid value for 'ask'. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid.
pyxmpp2/roster.py
def verify_roster_push(self, fix = False): """Check if `self` is valid roster push item. Valid item must have proper `subscription` value other and valid value for 'ask'. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid. """ self._verify((None, u"from", u"to", u"both", u"remove"), fix)
def verify_roster_push(self, fix = False): """Check if `self` is valid roster push item. Valid item must have proper `subscription` value other and valid value for 'ask'. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with the defaults :Types: - `fix`: `bool` :Raise: `ValueError` if the item is invalid. """ self._verify((None, u"from", u"to", u"both", u"remove"), fix)
[ "Check", "if", "self", "is", "valid", "roster", "push", "item", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/roster.py#L307-L321
[ "def", "verify_roster_push", "(", "self", ",", "fix", "=", "False", ")", ":", "self", ".", "_verify", "(", "(", "None", ",", "u\"from\"", ",", "u\"to\"", ",", "u\"both\"", ",", "u\"remove\"", ")", ",", "fix", ")" ]
14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
RosterItem.verify_roster_set
Check if `self` is valid roster set item. For use on server to validate incoming roster sets. Valid item must have proper `subscription` value other and valid value for 'ask'. The lengths of name and group names must fit the configured limits. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with right defaults - `settings`: settings object providing the name limits :Types: - `fix`: `bool` - `settings`: `XMPPSettings` :Raise: `BadRequestProtocolError` if the item is invalid.
pyxmpp2/roster.py
def verify_roster_set(self, fix = False, settings = None): """Check if `self` is valid roster set item. For use on server to validate incoming roster sets. Valid item must have proper `subscription` value other and valid value for 'ask'. The lengths of name and group names must fit the configured limits. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with right defaults - `settings`: settings object providing the name limits :Types: - `fix`: `bool` - `settings`: `XMPPSettings` :Raise: `BadRequestProtocolError` if the item is invalid. """ # pylint: disable=R0912 try: self._verify((None, u"remove"), fix) except ValueError, err: raise BadRequestProtocolError(unicode(err)) if self.ask: if fix: self.ask = None else: raise BadRequestProtocolError("'ask' in roster set") if self.approved: if fix: self.approved = False else: raise BadRequestProtocolError("'approved' in roster set") if settings is None: settings = XMPPSettings() name_length_limit = settings["roster_name_length_limit"] if self.name and len(self.name) > name_length_limit: raise NotAcceptableProtocolError(u"Roster item name too long") group_length_limit = settings["roster_group_name_length_limit"] for group in self.groups: if not group: raise NotAcceptableProtocolError(u"Roster group name empty") if len(group) > group_length_limit: raise NotAcceptableProtocolError(u"Roster group name too long") if self._duplicate_group: raise BadRequestProtocolError(u"Item group duplicated")
def verify_roster_set(self, fix = False, settings = None): """Check if `self` is valid roster set item. For use on server to validate incoming roster sets. Valid item must have proper `subscription` value other and valid value for 'ask'. The lengths of name and group names must fit the configured limits. :Parameters: - `fix`: if `True` than replace invalid 'subscription' and 'ask' values with right defaults - `settings`: settings object providing the name limits :Types: - `fix`: `bool` - `settings`: `XMPPSettings` :Raise: `BadRequestProtocolError` if the item is invalid. """ # pylint: disable=R0912 try: self._verify((None, u"remove"), fix) except ValueError, err: raise BadRequestProtocolError(unicode(err)) if self.ask: if fix: self.ask = None else: raise BadRequestProtocolError("'ask' in roster set") if self.approved: if fix: self.approved = False else: raise BadRequestProtocolError("'approved' in roster set") if settings is None: settings = XMPPSettings() name_length_limit = settings["roster_name_length_limit"] if self.name and len(self.name) > name_length_limit: raise NotAcceptableProtocolError(u"Roster item name too long") group_length_limit = settings["roster_group_name_length_limit"] for group in self.groups: if not group: raise NotAcceptableProtocolError(u"Roster group name empty") if len(group) > group_length_limit: raise NotAcceptableProtocolError(u"Roster group name too long") if self._duplicate_group: raise BadRequestProtocolError(u"Item group duplicated")
[ "Check", "if", "self", "is", "valid", "roster", "set", "item", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/roster.py#L323-L369
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14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
Roster.groups
Set of groups defined in the roster. :Return: the groups :ReturnType: `set` of `unicode`
pyxmpp2/roster.py
def groups(self): """Set of groups defined in the roster. :Return: the groups :ReturnType: `set` of `unicode` """ groups = set() for item in self._items: groups |= item.groups return groups
def groups(self): """Set of groups defined in the roster. :Return: the groups :ReturnType: `set` of `unicode` """ groups = set() for item in self._items: groups |= item.groups return groups
[ "Set", "of", "groups", "defined", "in", "the", "roster", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/roster.py#L539-L548
[ "def", "groups", "(", "self", ")", ":", "groups", "=", "set", "(", ")", "for", "item", "in", "self", ".", "_items", ":", "groups", "|=", "item", ".", "groups", "return", "groups" ]
14a40a3950910a9cd008b55f0d8905aa0186ce18
valid
Roster.get_items_by_name
Return a list of items with given name. :Parameters: - `name`: name to look-up - `case_sensitive`: if `False` the matching will be case insensitive. :Types: - `name`: `unicode` - `case_sensitive`: `bool` :Returntype: `list` of `RosterItem`
pyxmpp2/roster.py
def get_items_by_name(self, name, case_sensitive = True): """ Return a list of items with given name. :Parameters: - `name`: name to look-up - `case_sensitive`: if `False` the matching will be case insensitive. :Types: - `name`: `unicode` - `case_sensitive`: `bool` :Returntype: `list` of `RosterItem` """ if not case_sensitive and name: name = name.lower() result = [] for item in self._items: if item.name == name: result.append(item) elif item.name is None: continue elif not case_sensitive and item.name.lower() == name: result.append(item) return result
def get_items_by_name(self, name, case_sensitive = True): """ Return a list of items with given name. :Parameters: - `name`: name to look-up - `case_sensitive`: if `False` the matching will be case insensitive. :Types: - `name`: `unicode` - `case_sensitive`: `bool` :Returntype: `list` of `RosterItem` """ if not case_sensitive and name: name = name.lower() result = [] for item in self._items: if item.name == name: result.append(item) elif item.name is None: continue elif not case_sensitive and item.name.lower() == name: result.append(item) return result
[ "Return", "a", "list", "of", "items", "with", "given", "name", "." ]
Jajcus/pyxmpp2
python
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/roster.py#L550-L574
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14a40a3950910a9cd008b55f0d8905aa0186ce18