def halt(population, generation_count):
"""
Given a population of candidate solutions and generation count (the
number of epochs the algorithm has run) will return a boolean to
indicate if an acceptable solution has been found within the
referenced population.
"""
fittest = population[0]
max_fitness = MAX_REWARD
for i in range(len(fittest.chromosome)):
# Check for dissonances. Each dissonance should have incremented
# the fitness because it has been "placed" correctly.
cantus_firmus_note = cantus_firmus[i / 4]
melody_note = fittest.chromosome[i]
interval = melody_note - cantus_firmus_note
if interval in DISSONANCES:
max_fitness += REWARD_STEPWISE_MOTION
else:
if i > 0 and i < (len(fittest.chromosome) - 2):
if is_stepwise_motion(fittest.chromosome, i):
max_fitness += REWARD_STEPWISE_MOTION
return (fittest.fitness >= max_fitness or
generation_count > DEFAULT_MAX_GENERATION)
def halt(population, generation_count):
"""
Given a population of candidate solutions and generation count (the
number of epochs the algorithm has run) will return a boolean to
indicate if an acceptable solution has been found within the
referenced population.
"""
fittest = population[0]
max_fitness = MAX_REWARD
for i in range(len(fittest.chromosome)):
# Check for dissonances. Each dissonance should have incremented
# the fitness because it has been "placed" correctly.
cantus_firmus_note = cantus_firmus[i / 4]
melody_note = fittest.chromosome[i]
interval = melody_note - cantus_firmus_note
if interval in DISSONANCES:
max_fitness += REWARD_STEPWISE_MOTION
else:
if i > 0 and i < (len(fittest.chromosome) - 2):
if is_stepwise_motion(fittest.chromosome, i):
max_fitness += REWARD_STEPWISE_MOTION
return (fittest.fitness >= max_fitness
or generation_count > DEFAULT_MAX_GENERATION)
def fitness_function(genome):
"""
Given a candidate solution will return its fitness score assuming
the cantus_firmus in this closure. Caches the fitness score in the
genome.
"""
# Save some time!
if genome.fitness is not None:
return genome.fitness
# The fitness score to be returned.
fitness_score = 0.0
# Counts the number of repeated notes.
repeats = 0
# Counts the amount of parallel motion.
parallel_motion = 0
# Counts the number of jumps in the melodic contour.
jump_contour = 0
contrapunctus = genome.chromosome
# Make sure the solution starts correctly (at a 5th or octave).
first_interval = contrapunctus[0] - cantus_firmus[0]
if first_interval == 7 or first_interval == 4:
fitness_score += REWARD_FIRST
else:
fitness_score -= PUNISH_FIRST
# Make sure the solution finishes correctly (at an octave).
if contrapunctus[-1] - cantus_firmus[-1] == 7:
fitness_score += REWARD_LAST
else:
fitness_score -= PUNISH_LAST
# Ensure the penultimate note is step wise onto the final note.
if abs(contrapunctus[-1] - contrapunctus[-2]) == 1:
fitness_score += REWARD_LAST_STEP
else:
fitness_score -= PUNISH_LAST_STEP
# Reward contrary motion onto the final note.
cantus_firmus_motion = cantus_firmus[-1] - cantus_firmus[-2]
contrapunctus_motion = contrapunctus[-1] - contrapunctus[-2]
if ((cantus_firmus_motion < 0 and contrapunctus_motion > 0) or
(cantus_firmus_motion > 0 and contrapunctus_motion < 0)):
fitness_score += REWARD_LAST_MOTION
else:
fitness_score -= PUNISH_LAST_MOTION
# Make sure the penultimate note isn't a repeated note.
penultimate_preparation = abs(contrapunctus[-2] - contrapunctus[-3])
if penultimate_preparation == 0:
fitness_score -= PUNISH_REPEATED_PENULTIMATE
else:
# Make sure the movement to the penultimate note isn't from too
# far away (not greater than a third).
if penultimate_preparation < 2:
fitness_score += REWARD_PENULTIMATE_PREPARATION
else:
fitness_score -= PUNISH_PENULTIMATE_PREPARATION
# Check the fitness of the body of the solution.
last_notes = (contrapunctus[0], cantus_firmus[0])
last_interval = last_notes[0] - last_notes[1]
for i in range(1, len(contrapunctus) - 1):
contrapunctus_note = contrapunctus[i]
cantus_firmus_note = cantus_firmus[i / 4]
current_notes = (contrapunctus_note, cantus_firmus_note)
current_interval = contrapunctus_note - cantus_firmus_note
# Punish parallel fifths or octaves.
if ((current_interval == 4 or current_interval == 7) and
(last_interval == 4 or last_interval == 7)):
fitness_score -= PUNISH_PARALLEL_FIFTHS_OCTAVES
# Check for parallel motion.
if is_parallel(last_notes, current_notes):
parallel_motion += 1
# Check if the melody is a repeating note.
if contrapunctus_note == last_notes[0]:
repeats += 1
# Check the melodic contour.
contour_leap = abs(current_notes[0] - last_notes[0])
if contour_leap >= 2:
jump_contour += contour_leap - 2
# Ensure dissonances are part of a step-wise movement.
if i % 2 and current_interval in DISSONANCES:
# The current_note is a dissonance on the third beat of a bar.
# Check that both the adjacent notes are only a step away.
if is_stepwise_motion(contrapunctus, i):
fitness_score += REWARD_STEPWISE_MOTION
else:
fitness_score -= PUNISH_STEPWISE_MOTION
else:
if is_stepwise_motion(contrapunctus, i):
fitness_score += REWARD_STEPWISE_MOTION
last_notes = current_notes
last_interval = current_interval
# Punish too many (> 1/3) repeated notes.
if repeats > repeat_threshold:
fitness_score -= PUNISH_REPEATS
# Punish too many (> 1/3) parallel movements.
if parallel_motion > repeat_threshold:
fitness_score -= PUNISH_PARALLEL
# Punish too many large leaps in the melody.
if jump_contour > jump_threshold:
fitness_score -= PUNISH_LEAPS
genome.fitness = fitness_score
return fitness_score
def fitness_function(genome):
"""
Given a candidate solution will return its fitness score assuming
the cantus_firmus in this closure. Caches the fitness score in the
genome.
"""
# Save some time!
if genome.fitness is not None:
return genome.fitness
# The fitness score to be returned.
fitness_score = 0.0
# Counts the number of repeated notes.
repeats = 0
# Counts the amount of parallel motion.
parallel_motion = 0
# Counts the number of jumps in the melodic contour.
jump_contour = 0
contrapunctus = genome.chromosome
# Make sure the solution starts correctly (at a 5th or octave).
first_interval = contrapunctus[0] - cantus_firmus[0]
if first_interval == 7 or first_interval == 4:
fitness_score += REWARD_FIRST
else:
fitness_score -= PUNISH_FIRST
# Make sure the solution finishes correctly (at an octave).
if contrapunctus[-1] - cantus_firmus[-1] == 7:
fitness_score += REWARD_LAST
else:
fitness_score -= PUNISH_LAST
# Ensure the penultimate note is step wise onto the final note.
if abs(contrapunctus[-1] - contrapunctus[-2]) == 1:
fitness_score += REWARD_LAST_STEP
else:
fitness_score -= PUNISH_LAST_STEP
# Reward contrary motion onto the final note.
cantus_firmus_motion = cantus_firmus[-1] - cantus_firmus[-2]
contrapunctus_motion = contrapunctus[-1] - contrapunctus[-2]
if ((cantus_firmus_motion < 0 and contrapunctus_motion > 0)
or (cantus_firmus_motion > 0 and contrapunctus_motion < 0)):
fitness_score += REWARD_LAST_MOTION
else:
fitness_score -= PUNISH_LAST_MOTION
# Make sure the penultimate note isn't a repeated note.
penultimate_preparation = abs(contrapunctus[-2] - contrapunctus[-3])
if penultimate_preparation == 0:
fitness_score -= PUNISH_REPEATED_PENULTIMATE
else:
# Make sure the movement to the penultimate note isn't from too
# far away (not greater than a third).
if penultimate_preparation < 2:
fitness_score += REWARD_PENULTIMATE_PREPARATION
else:
fitness_score -= PUNISH_PENULTIMATE_PREPARATION
# Check the fitness of the body of the solution.
last_notes = (contrapunctus[0], cantus_firmus[0])
last_interval = last_notes[0] - last_notes[1]
for i in range(1, len(contrapunctus) - 1):
contrapunctus_note = contrapunctus[i]
cantus_firmus_note = cantus_firmus[i / 4]
current_notes = (contrapunctus_note, cantus_firmus_note)
current_interval = contrapunctus_note - cantus_firmus_note
# Punish parallel fifths or octaves.
if ((current_interval == 4 or current_interval == 7)
and (last_interval == 4 or last_interval == 7)):
fitness_score -= PUNISH_PARALLEL_FIFTHS_OCTAVES
# Check for parallel motion.
if is_parallel(last_notes, current_notes):
parallel_motion += 1
# Check if the melody is a repeating note.
if contrapunctus_note == last_notes[0]:
repeats += 1
# Check the melodic contour.
contour_leap = abs(current_notes[0] - last_notes[0])
if contour_leap >= 2:
jump_contour += contour_leap - 2
# Ensure dissonances are part of a step-wise movement.
if i % 2 and current_interval in DISSONANCES:
# The current_note is a dissonance on the third beat of a bar.
# Check that both the adjacent notes are only a step away.
if is_stepwise_motion(contrapunctus, i):
fitness_score += REWARD_STEPWISE_MOTION
else:
fitness_score -= PUNISH_STEPWISE_MOTION
else:
if is_stepwise_motion(contrapunctus, i):
fitness_score += REWARD_STEPWISE_MOTION
last_notes = current_notes
last_interval = current_interval
# Punish too many (> 1/3) repeated notes.
if repeats > repeat_threshold:
fitness_score -= PUNISH_REPEATS
# Punish too many (> 1/3) parallel movements.
if parallel_motion > repeat_threshold:
fitness_score -= PUNISH_PARALLEL
# Punish too many large leaps in the melody.
if jump_contour > jump_threshold:
fitness_score -= PUNISH_LEAPS
genome.fitness = fitness_score
return fitness_score
