partitura.utils

partitura.utils.compute_pianoroll(note_info, time_unit='auto', time_div='auto', onset_only=False, note_separation=False, pitch_margin=-1, time_margin=0, return_idxs=False, piano_range=False, remove_drums=True, remove_silence=True, end_time=None)

Computes a piano roll from a structured note array (as generated by the note_array methods in partitura.score.Part and partitura.performance.PerformedPart instances).

Parameters

• note_info (structured array, Part, PartGroup, PerformedPart) – Note information

• time_unit (('auto', 'beat', 'quarter', 'div', 'second')) –

• time_div (int, optional) – How many sub-divisions for each time unit (beats for a score or seconds for a performance. See is_performance below).

• onset_only (bool, optional) – If True, code only the onsets of the notes, otherwise code onset and duration.

• pitch_margin (int, optional) – If pitch_margin > -1, the resulting array will have pitch_margin empty rows above and below the highest and lowest pitches, respectively; if pitch_margin == -1, the resulting pianoroll will have span the fixed pitch range between (and including) 1 and 127.

• time_margin (int, optional) – The resulting array will have time_margin * time_div empty columns before and after the piano roll

• return_idxs (bool, optional) – If True, return the indices (i.e., the coordinates) of each note in the piano roll.

• piano_range (bool, optional) – If True, the pitch axis of the piano roll is in piano keys instead of MIDI note numbers (and there are only 88 pitches). This is equivalent as slicing piano_range_pianoroll = pianoroll[21:109, :].

• remove_drums (bool, optional) – If True, removes the drum track (i.e., channel 9) from the notes to be considered in the piano roll. This option is only relevant for piano rolls generated from a PerformedPart. Default is True.

• remove_silence (bool, optional) – If True, the first frame of the pianoroll starts at the onset of the first note, not at time 0 of the timeline.

• end_time (int, optional) – The time corresponding to the ending of the last pianoroll frame (in time_unit). If None this is set to the last note offset.

Returns

• pianoroll (scipy.sparse.csr_matrix) – A sparse int matrix of size representing the pianoroll; The first dimension is pitch, the second is time; The sizes of the dimensions vary with the parameters pitch_margin, time_margin, time_div, remove silence, and end_time.

• pr_idx (ndarray) – Indices of the onsets and offsets of the notes in the piano roll (in the same order as the input note_array). This is only returned if return_idxs is True.

Examples

>>> import numpy as np
>>> from partitura.utils import compute_pianoroll
>>> note_array = np.array([(60, 0, 1)],                          dtype=[('pitch', 'i4'),                                 ('onset_beat', 'f4'),                                 ('duration_beat', 'f4')])
>>> pr = compute_pianoroll(note_array, pitch_margin=2, time_div=2)
>>> pr.toarray()
array([[0, 0],
       [0, 0],
       [1, 1],
       [0, 0],
       [0, 0]])

Notes

The default values in this function assume that the input note_array represents a score.

partitura.utils.ensure_notearray(notearray_or_part, *args, **kwargs)

Ensures to get a structured note array from the input.

Parameters

• notearray_or_part (structured ndarray, Score, Part, PerformedPart) – Input score information

• kwargs (dict) – Additional arguments to be passed to partitura.utils.note_array_from_part().

Returns

Structured array containing score information.

Return type

structured ndarray

partitura.utils.ensure_rest_array(restarray_or_part, *args, **kwargs)

Ensures to get a structured note array from the input.

Parameters

restarray_or_part (structured ndarray, Part or PerformedPart) – Input score information

Returns

Structured array containing score information.

Return type

structured ndarray

partitura.utils.fifths_mode_to_key_name(fifths, mode=None)

Return the key signature name corresponding to a number of sharps or flats and a mode. A negative value for fifths denotes the number of flats (i.e. -3 means three flats), and a positive number the number of sharps. The mode is specified as ‘major’ or ‘minor’. If mode is None, the key is assumed to be major.

Parameters

• fifths (int) – Number of fifths

• mode ({'major', 'minor', None, -1, 1}) – Mode of the key signature

Returns

The name of the key signature, e.g. ‘Am’

Return type

str

Examples

>>> fifths_mode_to_key_name(0, 'minor')
'Am'
>>> fifths_mode_to_key_name(0, 'major')
'C'
>>> fifths_mode_to_key_name(3, 'major')
'A'
>>> fifths_mode_to_key_name(-1, 1)
'F'

partitura.utils.key_mode_to_int(mode)

Return the mode of a key as an integer (1 for major and -1 for minor).

Parameters

mode ({'major', 'minor', None, 1, -1}) – Mode of the key

Returns

Integer representation of the mode.

Return type

int

partitura.utils.key_name_to_fifths_mode(key_name)

Return the number of sharps or flats and the mode of a key signature name. A negative number denotes the number of flats (i.e. -3 means three flats), and a positive number the number of sharps. The mode is specified as ‘major’ or ‘minor’.

Parameters

name (str) – Name of the key signature, i.e. Am, E#, etc

Returns

Tuple containing the number of fifths and the mode

Return type

(int, str)

Examples

>>> key_name_to_fifths_mode('Am')
(0, 'minor')
>>> key_name_to_fifths_mode('C')
(0, 'major')
>>> key_name_to_fifths_mode('A')
(3, 'major')

partitura.utils.pianoroll_to_notearray(pianoroll, time_div=8, time_unit='sec')

Extract a structured note array from a piano roll.

For now, the structured note array is considered a “performance”.

Parameters

• pianoroll (array-like) – 2D array containing a piano roll. The first dimension is pitch, and the second is time. The value of each “pixel” in the piano roll is considered to be the MIDI velocity, and it is supposed to be between 0 and 127.

• time_div (int) – How many sub-divisions for each time unit (see notearray_to_pianoroll).

• time_unit ({'beat', 'quarter', 'div', 'sec'}) – time unit of the output note array.

Returns

Structured array with pitch, onset, duration, velocity and note id fields.

Return type

np.ndarray

Notes

Please note that all non-zero pixels will contribute to a note. For the case of piano rolls with continuous values between 0 and 1 (as might be the case of those piano rolls produced using probabilistic/generative models), we recomend to either 1) hard- threshold the piano roll to have only 0s (note-off) or 1s (note- on) or, 2) soft-threshold the notes (values below a certain threshold are considered as not active and scale the active notes to lie between 1 and 127).

partitura.utils.show_diff(a, b)

Show the difference between two strings, using the difflib package. The difference is printed to stdout.

Parameters

• a (str) – First string

• b (str) – Second string

partitura.utils.slice_notearray_by_time(note_array, start_time, end_time, time_unit='auto', clip_onset_duration=True)

Get a slice of a structured note array by time

Parameters

• note_array (structured array) – Structured array with score information.

• start_time (float) – Starting time

• end_time (float) – End time

• time_unit ({'auto', 'beat', 'quarter', 'second', 'div'} optional) – Time unit. If ‘auto’, the default time unit will be inferred from the note_array.

• clip_onset_duration (bool optional) – Clip duration of the notes in the array to fit within the specified window

Returns

note_array_slice – Structured array with only the score information between start_time and end_time.

Return type

stuctured array