def __illustrate__(self, scale=None, target_timespan=None, **kwargs):
target_timespan = target_timespan or abjad.Timespan(0, 16)
assert isinstance(target_timespan, abjad.Timespan)
assert 0 < target_timespan.duration
scale = scale or 1.5
music_specifiers = abjad.OrderedDict([
('A', 'A music'),
('B', 'B music'),
('C', 'C music'),
('D', 'D music'),
('E', 'E music'),
('F', 'F music'),
('G', 'G music'),
('H', 'H music'),
('I', 'I music'),
('J', 'J music'),
])
timespan_list = self(
layer=0,
music_specifiers=music_specifiers,
target_timespan=target_timespan,
)
ti_lilypond_file = timespan_list.__illustrate__(
key='voice_name',
range_=target_timespan,
scale=scale,
)
ti_markup = ti_lilypond_file.items[-1]
offset_counter = abjad.OffsetCounter(timespan_list)
oc_lilypond_file = offset_counter.__illustrate__(
range_=target_timespan,
scale=scale,
)
oc_markup = oc_lilypond_file.items[-1]
lilypond_file = abjad.LilyPondFile.new(
default_paper_size=['tabloid', 'landscape'],
date_time_token=False,
)
lilypond_file.items.extend([
abjad.String.normalize('''
% Backport for pre 2.19.20 versions of LilyPond
#(define-markup-command (overlay layout props args)
(markup-list?)
(apply ly:stencil-add (interpret-markup-list layout props args)))
'''),
ti_markup,
abjad.Markup.null().pad_around(2),
oc_markup,
])
lilypond_file.header_block.tagline = False
return lilypond_file
def __illustrate__(self, scale=None, target_timespan=None, **kwargs):
target_timespan = target_timespan or abjad.Timespan(0, 16)
assert isinstance(target_timespan, abjad.Timespan)
assert 0 < target_timespan.duration
scale = scale or 1.5
music_specifiers = dict([
("A", "A music"),
("B", "B music"),
("C", "C music"),
("D", "D music"),
("E", "E music"),
("F", "F music"),
("G", "G music"),
("H", "H music"),
("I", "I music"),
("J", "J music"),
])
timespan_list = self(
layer=0,
music_specifiers=music_specifiers,
target_timespan=target_timespan,
)
ti_lilypond_file = timespan_list.__illustrate__(
key="voice_name",
range_=target_timespan,
scale=scale,
)
ti_markup = ti_lilypond_file.items[-1]
offset_counter = abjad.OffsetCounter(timespan_list)
oc_lilypond_file = offset_counter.__illustrate__(
range_=target_timespan,
scale=scale,
)
oc_markup = oc_lilypond_file.items[-1]
lilypond_file = abjad.LilyPondFile.new(
default_paper_size=["tabloid", "landscape"],
date_time_token=False,
)
lilypond_file.items.extend([
abjad.String.normalize("""
% Backport for pre 2.19.20 versions of LilyPond
#(define-markup-command (overlay layout props args)
(markup-list?)
(apply ly:stencil-add (interpret-markup-list layout props args)))
"""),
ti_markup,
abjad.Markup.null().pad_around(2),
oc_markup,
])
lilypond_file.header_block.tagline = False
return lilypond_file
import pathlib
import abjad
from chalk_line.materials.timespans.segment_01.make_timespans import (
rhythm_timespan_list, )
offset_counter = abjad.OffsetCounter(rhythm_timespan_list)
counter_path = f"""{pathlib.Path(__file__).parent}/segment_01_offset_counter.pdf"""
persisted_counter = abjad.persist.as_pdf(offset_counter,
counter_path,
scale=0.70)
permitted_meters = abjad.MeterList([
(5, 4),
(9, 8),
(4, 4),
(7, 8),
(3, 4),
(5, 8),
(2, 4),
(3, 8),
(5, 16),
(1, 4),
# (3, 16),
# (1, 8),
])
fitted_meters = abjad.Meter.fit_meters(argument=offset_counter,
meters=permitted_meters,
final_list.append(new_ts)
meters.append(abjad.Meter(new_ts.duration))
permitted_meters = [
# (7, 4),
(5, 4),
(4, 4),
(3, 4),
(3, 8),
(11, 16),
# (3, 16),
]
# remove repeated
coincident_offsets = list(dict.fromkeys(coincident_offsets))
# print(coincident_offsets)
offset_counter = abjad.OffsetCounter(coincident_offsets)
fitted_meters = abjad.Meter.fit_meters(
argument=offset_counter,
meters=permitted_meters, # maximum_run_length=1
)
time_signatures = [_.implied_time_signature for _ in fitted_meters]
for i in time_signatures:
print("Time Signature:", i)
if __name__ == "__main__":
# abjad.show(final_list, scale=0.8, key="annotation")
pass
1,
2,
3,
2,
), # smashes timespans together without intermittent silence
silence_talea=rmakers.Talea(counts=(2, 1, 1), denominator=4),
# fuse_groups=False, #turns groups from multiple timespans into one large timespan
)
timespan_list = timespan_maker(music_specifiers=music_specifiers,
target_timespan=target_timespan)
# abjad.show(timespan_list, scale=0.7, key='voice_name')
timespan_list
#
offset_counter = abjad.OffsetCounter(timespan_list)
# abjad.show(offset_counter, scale=0.7)
####
permitted_meters = abjad.MeterList([(3, 4), (4, 4), (5, 16), (7, 8)])
# abjad.show(permitted_meters, scale=0.7)
#
fitted_meters = abjad.Meter.fit_meters(argument=offset_counter,
meters=permitted_meters,
maximum_run_length=1)
# abjad.show(fitted_meters, scale=0.7)
# groups = [timespan.voice_name for timespan in timespan_list]
# input = [(span, group) for span, group in zip(timespan_list, groups)]
