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RhythmicGenerators.py
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RhythmicGenerators.py
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from __future__ import annotations
from MusiStrata.Components import Bar, GenerateBarFromRhythmicPreset
from utils import ComputeCumulativeProbabilitiesFromDict
from random import random, choice
from math import ceil
from copy import deepcopy
from typing import List, Dict, Union, Tuple
class RhythmicGeneratorInterface(object):
def __str__(self):
return "<class 'RhythmicGeneratorInterface'>"
def __repr__(self):
return self.__str__()
@staticmethod
def GenerateBreak():
# Use this to get an empty bar, could serve as break in between generated segments
return Bar()
@staticmethod
def GeneratePattern(nbBars: int) -> Tuple[int, List[int]]:
# how many different bars? use square root of nb bars
nbSegments = ceil(nbBars ** 0.5)
return nbSegments, [choice(range(nbSegments)) for _ in range(nbBars)]
class RhythmicPreset(RhythmicGeneratorInterface):
"""
Expecting a Dict following this example:
{
"Name": "TestRhythmicPreset1",
"Tags": ["Test"],
"Beats": 4,
"MainPreset": [
{
"beat": 0.0,
"duration": 1.0
},
{
"beat": 2.0,
"duration": 1.0
},
{
"beat": 3.0,
"duration": 0.5
},
{
"beat": 3.5,
"duration": 0.5
}
],
"Variants": []
}
"""
NbBeats = 4
def __init__(self, parameters: Dict):
self.NbBeats = parameters["NbBeats"]
self.Presets = [parameters["MainPreset"]] + parameters["VariantsPreset"]
def __str__(self):
return "<class 'RhythmicPreset'>"
def __repr__(self):
return self.__str__()
# override generatepattern
def GeneratePattern(self, nbBars: int) -> List[int]:
return [choice(range(len(self.Presets))) for _ in range(nbBars)]
def __call__(self, nbBars: int, nbBeats: float = 4.0, pattern: List[int] = [], **kwargs):
if pattern == []:
pattern = self.GeneratePattern(nbBars)
return [
GenerateBarFromRhythmicPreset(
self.Presets[idPreset]
) for idPreset in pattern
]
class RhythmicModel(RhythmicGeneratorInterface):
"""
Expecting a Dict as input with fields:
- Name: str
- Tags: List[str]
- SilenceChance: float (0.0 <= value <= 1.0)
- Notes: Dict(str: float)
- Silences: Dict(str: float
Tags is not mandatory, will be used in DB queries when creating generator parameters
"""
# From Input Parameters
Name = ""
SilenceChance = 0.0
def __init__(self, parameters: Dict):
# Tracking Parameters
self.Name = parameters["Name"]
self.SilenceChance = parameters["SilenceChance"]
self.NotesDurations = []
self.NotesProbabilities = []
self.SilencesDurations = []
self.SilencesProbabilities = []
self.CheckAndSetProbabilities(parameters)
def __str__(self):
return "RhythmicModel({})".format(self.Name)
def __repr__(self):
return self.__str__()
def __call__(self, nbBars: int, nbBeats: float = 4.0, pattern: List[int] = [], **kwargs):
if pattern == []:
nbSegments, pattern = self.GeneratePattern(nbBars)
else:
nbSegments = max(pattern) + 1
generatedSegments = [
self.GenerateBar(nbBeats) for _ in range(nbSegments)
]
return [generatedSegments[idPattern] for idPattern in pattern]
def CheckAndSetProbabilities(self, parameters: Dict):
vals = []
for k in ["Notes", "Silences"]:
vals += ComputeCumulativeProbabilitiesFromDict(
parameters[k]
)
self.NotesDurations = vals[0]
self.NotesProbabilities = vals[1]
self.SilencesDurations = vals[2]
self.SilencesProbabilities = vals[3]
def GeneratePreset(self, nbBeats: int):
barPreset = []
sumDurations = 0.0
while sumDurations < nbBeats:
drewSilence = False
drawn = random()
if drawn <= self.SilenceChance:
drewSilence = True
currDurations = self.SilencesDurations
currProbabilities = self.SilencesProbabilities
else:
currDurations = self.NotesDurations
currProbabilities = self.NotesProbabilities
# adding insurance
nbTries = 0
while True:
selectedDuration = 0.0
drawn = random()
for idProba in range(len(currProbabilities)):
if drawn <= currProbabilities[idProba]:
selectedDuration = currDurations[idProba]
break
if sumDurations + selectedDuration <= nbBeats:
if not drewSilence:
barPreset.append(
{
"Beat": sumDurations,
"Duration": selectedDuration
}
)
sumDurations += selectedDuration
break
nbTries += 1
if nbTries >= 50:
print("Cannot find Solution. Switching between Silences and Notes")
if drewSilence:
currDurations = self.NotesDurations
currProbabilities = self.NotesProbabilities
drewSilence = False
else:
currDurations = self.SilencesDurations
currProbabilities = self.SilencesProbabilities
drewSilence = True
if nbTries >= 100:
print("Cannot fulfill exit conditions, mismatched Generator specs.")
print("Exiting generation loop, think about providing more granularity for model: {}".format(self))
print("Returning BarPreset generated until now")
print()
break
return barPreset
def GenerateBar(self, nbBeats: float) -> Bar:
return GenerateBarFromRhythmicPreset(
self.GeneratePreset(nbBeats)
)