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import random
import numpy as np
from configurations.read_configuration import get_conf_n_sample, get_conf_sample_rate, get_conf_max_n_notes
def get_random_note_type_index(distribution):
"""A helper method that randomly chooses next note type based on a distribution
Parameters
----------
distribution: List[float]
Note type distribution.
Returns
-------
midi: int
Random type index.
"""
r = np.random.random()
for i in range(len(distribution)):
r = r - distribution[i]
if r < 0:
return i
return len(distribution) - 1
# Todo: rewrite this part
def to_onsets_in_seconds(bpm, notes):
"""A helper method that transform a list of note types into a list of note onsets (in seconds)
Parameters
----------
bpm: float
BPM
notes: List[int]
Returns
-------
midi: int
Random type index.
"""
full_note_length = 4 * 60 / bpm
onsets = [0]
for i in range(len(notes)):
onsets.append(onsets[i] + full_note_length * notes[i])
return onsets
class RandomRhythm:
"""First component in the random midi pipeline responsible for random rhythm (note onsets) generating"""
def __init__(self):
self.note_types = [0, 1, 3 / 4, 0.5, 3 / 8, 0.25, 1 / 8]
self.first_note_type_distribution = np.array([0, 0.2, 0.05, 0.25, 0.05, 0.3, 0.15])
self.rhythm_generation_matrix = np.array([
[0.1, 0.1, 0.25, 0.1, 0.25, 0.2],
[0.05, 0.25, 0.25, 0.05, 0.3, 0.1],
[0.1, 0.1, 0.3, 0.05, 0.35, 0.1],
[0.05, 0.05, 0.2, 0.2, 0.25, 0.25],
[0.1, 0.05, 0.1, 0.05, 0.4, 0.3],
[0.1, 0.05, 0.1, 0.1, 0.3, 0.35],
])
# self.bpm = bpm
self.rhythm_duration = np.array([0, 1, 3 / 4, 0.5, 3 / 8, 0.25])
self.audio_length = get_conf_n_sample() / get_conf_sample_rate()
self.bpm_range = [90, 100, 110, 120, 130, 140, 150, 160, 170]
self.max_n_notes = get_conf_max_n_notes()
def __call__(self, strategy: str, *args, **kwargs):
"""Choose required strategy to generate random rhythm (note onsets).
Parameters
----------
strategy: str
Strategy names for random rhythm (see Readme).
Returns
-------
onsets: List[float]
A list of floats referring to note onsets in seconds.
"""
if strategy == 'bpm_based_rhythm':
rhythm = self.get_bpm_based_rhythm()
elif strategy == 'free_rhythm':
rhythm = self.get_free_rhythm()
elif strategy == 'single_note_rhythm':
rhythm = self.get_single_note()
else:
rhythm = [0.0, 1, 2, 3, 4]
return rhythm[:self.max_n_notes]
def get_bpm_based_rhythm(self):
"""Uses "bpm_based_rhythm" strategy to generate random rhythm (see Readme)."""
# Todo: clean up this part
bpm = random.choice(self.bpm_range)
first_note = get_random_note_type_index(self.first_note_type_distribution)
note_type_indexes = [first_note]
current_note_type = first_note
while True:
current_note_type = get_random_note_type_index(self.rhythm_generation_matrix[current_note_type - 1]) + 1
note_type_indexes.append(current_note_type)
# Random early stop
if np.random.random() < 9 / bpm:
break
notes = [self.note_types[note_type_index] for note_type_index in note_type_indexes]
onsets = to_onsets_in_seconds(bpm, notes)
return onsets
def get_free_rhythm(self):
"""Uses "free_rhythm" strategy to generate random rhythm (see Readme)."""
n_notes = np.random.randint(int(self.max_n_notes * 0.6), self.max_n_notes)
# n_notes = np.random.randint(int(1), self.max_n_notes)
onsets = np.random.rand(n_notes)
onsets.sort()
# Avoid notes too close together
pre = onsets[0]
n_removed = 0
for i in range(len(onsets)-1):
index = i - n_removed + 1
if (onsets[index] - pre) < 0.05:
new_onsets = np.delete(onsets, index)
onsets = new_onsets
n_removed = n_removed + 1
else:
pre = onsets[index]
return ((onsets - onsets[0])*self.audio_length).tolist()
def get_single_note(self):
return [0.0]
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