def test_pdict():
a = iso.PDict({
"a": iso.PSequence([1, 2, 3], 1),
"b": 4,
"c": None
})
assert list(a) == [
{"a": 1, "b": 4, "c": None},
{"a": 2, "b": 4, "c": None},
{"a": 3, "b": 4, "c": None}
]
a = iso.PDict([{"a": 1}, {"a": 2, }, {"a": 3}])
b = a["a"].copy()
assert list(b) == [1, 2, 3]
assert list(a) == [{"a": 1}, {"a": 2}, {"a": 3}]
def pattern(v):
"""
Patternify a value, turning it into an object with a next() method
to obtain its next value.
Pattern subclasses remain untouched.
Scalars and other objects are turned into PConst objects. """
if isinstance(v, Pattern):
return v
elif isinstance(v, dict):
return isobar.PDict(v)
else:
return isobar.PConstant(v)
def test_io_midifile_pdict_save(dummy_timeline):
events = {
iso.EVENT_NOTE: iso.PSequence([60, 62, 64, 67], 1),
iso.EVENT_DURATION: iso.PSequence([0.5, 1.5, 1, 1], 1),
iso.EVENT_GATE: iso.PSequence([2, 0.5, 1, 1], 1),
iso.EVENT_AMPLITUDE: iso.PSequence([64, 32, 16, 8], 1)
}
pdict = iso.PDict(events)
pdict.save("output.mid")
d = MidiFileInputDevice("output.mid").read()
for key in events.keys():
assert isinstance(d[key], iso.PSequence)
assert list(d[key]) == list(events[key])
os.unlink("output.mid")
import argparse
import isobar as iso
from isobar.io.midifile.input import MidiFileInputDevice
import logging
logging.basicConfig(level=logging.DEBUG, format="[%(asctime)s] %(message)s")
parser = argparse.ArgumentParser(description="Read and play a .mid file")
parser.add_argument("filename", type=str, help="File to load (.mid)")
args = parser.parse_args()
#------------------------------------------------------------------------
# Quantize durations to the nearest 1/8th note.
#------------------------------------------------------------------------
pattern = MidiFileInputDevice(args.filename).read(quantize=1 / 8)
pattern = iso.PDict(pattern)
#------------------------------------------------------------------------
# Learn note, duration and amplitude series separately.
#------------------------------------------------------------------------
note_learner = iso.MarkovLearner()
note_learner.learn_pattern(pattern["note"])
dur_learner = iso.MarkovLearner()
dur_learner.learn_pattern(pattern["duration"])
#------------------------------------------------------------------------
# Quantize velocities to the nearest 10 to make chains easier to
# learn with a small sample set.
#------------------------------------------------------------------------
amp_learner = iso.MarkovLearner()
amp_learner.learn_pattern(