def main():
"""Entry point of application."""
program_description = 'Harmonic oscillator'
parser = argparse.ArgumentParser(program_description)
parser.add_argument('--plot', help='plot best results', action='store_true')
app, args = application.default_console_app(Individual, AssessmentRunner, parser=parser)
app.run()
logger = logging.getLogger(__name__)
logger.info('\n')
logger.info('Hall of Fame:')
for individual in app.gp_runner.halloffame[:4]:
logger.info('{} {} = {}'.format(individual.fitness.values, repr(individual), str(individual)))
if not args.plot:
return
# Plot n best results.
import matplotlib.pyplot as plt
import seaborn
n = 4
seaborn.set_palette('husl', n + 2)
alpha = 0.75
label_size = 16
title_size = 20
assessment_runner = AssessmentRunner()
params, yinit = assessment_runner.params, assessment_runner.yinit
x, target = assessment_runner.x, assessment_runner.target
title = program_description + '\nparams={}, yinit={}'.format(params, yinit, fontsize=title_size)
ax0 = plt.subplot2grid((2, 2), (0, 0))
ax1 = plt.subplot2grid((2, 2), (1, 0))
ax2 = plt.subplot2grid((2, 2), (1, 1))
lines, labels = [], []
l, = ax0.plot(x, target, alpha=alpha)
labels.append('target')
lines.append(l)
for ind in reversed(app.gp_runner.halloffame[:n]):
label = 'with $a(y_0, y_1) = {}$'.format(str(ind))
label = label.replace('**', '^').replace('*', '\cdot ')
y = assessment_runner.trajectory(ind)
l, = ax0.plot(x, y[0, :], alpha=alpha)
ax1.plot(x, y[1, :], alpha=alpha, color=l.get_color())
ax2.plot(y[0, :], y[1, :], alpha=alpha, color=l.get_color())
labels.append(label)
lines.append(l)
ax0.set_ylabel('$y_0$', fontsize=label_size)
ax0.set_xlabel('time', fontsize=label_size)
ax1.set_ylabel('$y_1$', fontsize=label_size)
ax1.set_xlabel('time', fontsize=label_size)
ax2.set_xlabel('$y_0$', fontsize=label_size)
ax2.set_ylabel('$y_1$', fontsize=label_size)
ax2.set_title('Phase Portrait', fontsize=label_size)
plt.figlegend(lines, labels, loc='upper right', bbox_to_anchor=(0.9, 0.9), fontsize=label_size)
plt.suptitle(title, fontsize=title_size)
plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
plt.show()
def main():
"""Entry point of application."""
program_description = 'Lorenz system'
parser = argparse.ArgumentParser(program_description)
parser.add_argument(
'--params',
type=utils.argparse.ntuple(3, float),
default=(10, 28, 8 / 3),
help='parameters σ,r,b for the lorenz system (default: 10,28,8/3)')
parser.add_argument('--plot',
help='plot best results',
action='store_true')
app, args = application.default_console_app(Individual, AssessmentRunner,
parser)
app.assessment_runner.params['s'] = args.params[0]
app.assessment_runner.params['r'] = args.params[1]
app.assessment_runner.params['b'] = args.params[2]
app.run()
logger = logging.getLogger(__name__)
logger.info('\n')
logger.info('Hall of Fame:')
for individual in app.gp_runner.halloffame:
logger.info('{} {}'.format(individual.fitness.values,
str(individual)))
if not args.plot:
return
# Plot n best results.
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import seaborn
n = 2
seaborn.set_palette('husl', n + 2)
alpha = 0.7
label_size = 16
title_size = 20
params, yinit = app.assessment_runner.params, app.assessment_runner.yinit
x, target = app.assessment_runner.x, app.assessment_runner.target
title = program_description + '\nparams={}, yinit={}'.format(params, yinit)
ax0 = plt.subplot2grid((3, 2), (0, 0))
ax1 = plt.subplot2grid((3, 2), (1, 0))
ax2 = plt.subplot2grid((3, 2), (2, 0))
ax3 = plt.subplot2grid((3, 2), (1, 1), projection='3d', rowspan=2)
lines, labels = [], []
l, = ax0.plot(x, target, linestyle='dotted')
ax1.plot(x, target, linestyle='dotted')
ax2.plot(x, target, linestyle='dotted')
labels.append('target')
lines.append(l)
uncontrolled = Individual.from_string('Add(y_0, Neg(y_0))')
for ind in cons(uncontrolled, app.gp_runner.halloffame[:n]):
popt = getattr(ind, 'popt', np.zeros(len(ind.pset.constants)))
label = 'with $a({}) = {}$, $c={}$'.format(','.join(ind.pset.args),
str(ind), popt)
label = label.replace('**', '^').replace('*', '\cdot ')
y = app.assessment_runner.trajectory(ind, *popt)
l, = ax0.plot(x, y[0, :], alpha=alpha)
ax1.plot(x, y[1, :], alpha=alpha, color=l.get_color())
ax2.plot(x, y[2, :], alpha=alpha, color=l.get_color())
ax3.plot(y[0, :], y[1, :], y[2, :], alpha=alpha, color=l.get_color())
labels.append(label)
lines.append(l)
ax0.set_ylabel('$y_0$', fontsize=label_size)
ax0.set_xlabel('time', fontsize=label_size)
ax1.set_ylabel('$y_1$', fontsize=label_size)
ax1.set_xlabel('time', fontsize=label_size)
ax2.set_ylabel('$y_2$', fontsize=label_size)
ax2.set_xlabel('time', fontsize=label_size)
ax3.set_xlabel('$y_0$', fontsize=label_size)
ax3.set_ylabel('$y_1$', fontsize=label_size)
ax3.set_title('Phase Portrait', fontsize=label_size)
plt.figlegend(lines,
labels,
loc='upper right',
bbox_to_anchor=(0.9, 0.9),
fontsize=label_size)
plt.suptitle(title, fontsize=title_size)
plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
plt.show()
def main():
"""Entry point of application."""
program_description = "Damped oscillator d²y/dt² = -k*y - c*dy/dt"
parser = argparse.ArgumentParser(description=program_description)
parser.add_argument(
"--params",
type=utils.argparse.ntuple(2, float),
default=(3.0 / 8.0, 1.0),
help="parameters c,k for the damped oscillator (default: 3/8,1)",
)
parser.add_argument("--plot",
help="plot best results",
action="store_true")
app, args = application.default_console_app(Individual,
AssessmentRunner,
parser=parser)
app.assessment_runner.params["c"] = app.args.params[0]
app.assessment_runner.params["k"] = app.args.params[1]
app.run()
logger = logging.getLogger(__name__)
logger.info("\n")
logger.info("Hall of Fame:")
for individual in app.gp_runner.pareto_front:
popt = getattr(individual, "popt", ())
logger.info("{} {}, {} = {}".format(
individual.fitness.values,
str(individual),
individual.pset.constants,
popt,
))
if not args.plot:
return
# Plot n best results.
import matplotlib.pyplot as plt
import seaborn
n = 2
seaborn.set_palette("husl", n + 2)
alpha = 0.75
label_size = 16
title_size = 20
assessment_runner = AssessmentRunner()
params, yinit = assessment_runner.params, assessment_runner.yinit
x, ampl, omega = (
assessment_runner.x,
assessment_runner.ampl,
assessment_runner.omega,
)
title = program_description + "\nparams={}, yinit={}".format(
params, yinit, fontsize=title_size)
ax0 = plt.subplot2grid((2, 2), (0, 0))
ax1 = plt.subplot2grid((2, 2), (1, 0))
ax2 = plt.subplot2grid((2, 2), (1, 1))
lines, labels = [], []
target = (ampl * np.sin(omega * x), ampl * omega * np.cos(omega * x))
(l, ) = ax2.plot(target[0], target[1], linestyle="dotted", alpha=alpha)
ax0.plot(x,
target[0],
linestyle="dotted",
alpha=alpha,
color=l.get_color())
ax1.plot(x,
target[1],
linestyle="dotted",
alpha=alpha,
color=l.get_color())
labels.append("target")
lines.append(l)
uncontrolled = Individual.from_string("Add(y_0, Neg(y_0))")
for ind in cons(uncontrolled, reversed(app.gp_runner.pareto_front[:n])):
popt = getattr(ind, "popt", np.zeros(len(ind.pset.constants)))
label = "with $a(y_0, y_1) = {}$, $c={}$".format(str(ind), popt)
label = label.replace("**", "^").replace("*", "\cdot ")
y = assessment_runner.trajectory(ind, *popt)
(l, ) = ax0.plot(x, y[0, :], alpha=alpha)
ax1.plot(x, y[1, :], alpha=alpha, color=l.get_color())
ax2.plot(y[0, :], y[1, :], alpha=alpha, color=l.get_color())
labels.append(label)
lines.append(l)
ax0.set_ylabel("$y_0$", fontsize=label_size)
ax0.set_xlabel("time", fontsize=label_size)
ax1.set_ylabel("$y_1$", fontsize=label_size)
ax1.set_xlabel("time", fontsize=label_size)
ax2.set_xlabel("$y_0$", fontsize=label_size)
ax2.set_ylabel("$y_1$", fontsize=label_size)
ax2.set_title("Phase Portrait", fontsize=label_size)
plt.figlegend(lines,
labels,
loc="upper right",
bbox_to_anchor=(0.9, 0.9),
fontsize=label_size)
plt.suptitle(title, fontsize=title_size)
plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
plt.show()
def main():
"""Entry point of application."""
program_description = 'Damped oscillator d²y/dt² = -k*y - c*dy/dt'
parser = argparse.ArgumentParser(description=program_description)
parser.add_argument(
'--params',
type=utils.argparse.ntuple(2, float),
default=(3.0 / 8.0, 1.0),
help='parameters c,k for the damped oscillator (default: 3/8,1)')
parser.add_argument('--plot',
help='plot best results',
action='store_true')
app, args = application.default_console_app(Individual,
AssessmentRunner,
parser=parser)
app.assessment_runner.params['c'] = app.args.params[0]
app.assessment_runner.params['k'] = app.args.params[1]
app.run()
logger = logging.getLogger(__name__)
logger.info('\n')
logger.info('Hall of Fame:')
for individual in app.gp_runner.halloffame:
popt = getattr(individual, 'popt', ())
logger.info('{} {}, {} = {}'.format(individual.fitness.values,
str(individual),
individual.pset.constants, popt))
if not args.plot:
return
# Plot n best results.
import matplotlib.pyplot as plt
import seaborn
n = 2
seaborn.set_palette('husl', n + 2)
alpha = 0.75
label_size = 16
title_size = 20
assessment_runner = AssessmentRunner()
params, yinit = assessment_runner.params, assessment_runner.yinit
x, ampl, omega = assessment_runner.x, assessment_runner.ampl, assessment_runner.omega
title = program_description + '\nparams={}, yinit={}'.format(
params, yinit, fontsize=title_size)
ax0 = plt.subplot2grid((2, 2), (0, 0))
ax1 = plt.subplot2grid((2, 2), (1, 0))
ax2 = plt.subplot2grid((2, 2), (1, 1))
lines, labels = [], []
target = (ampl * np.sin(omega * x), ampl * omega * np.cos(omega * x))
l, = ax2.plot(target[0], target[1], linestyle='dotted', alpha=alpha)
ax0.plot(x,
target[0],
linestyle='dotted',
alpha=alpha,
color=l.get_color())
ax1.plot(x,
target[1],
linestyle='dotted',
alpha=alpha,
color=l.get_color())
labels.append('target')
lines.append(l)
uncontrolled = Individual.from_string('Add(y_0, Neg(y_0))')
for ind in cons(uncontrolled, reversed(app.gp_runner.halloffame[:n])):
popt = getattr(ind, 'popt', np.zeros(len(ind.pset.constants)))
label = 'with $a(y_0, y_1) = {}$, $c={}$'.format(str(ind), popt)
label = label.replace('**', '^').replace('*', '\cdot ')
y = assessment_runner.trajectory(ind, *popt)
l, = ax0.plot(x, y[0, :], alpha=alpha)
ax1.plot(x, y[1, :], alpha=alpha, color=l.get_color())
ax2.plot(y[0, :], y[1, :], alpha=alpha, color=l.get_color())
labels.append(label)
lines.append(l)
ax0.set_ylabel('$y_0$', fontsize=label_size)
ax0.set_xlabel('time', fontsize=label_size)
ax1.set_ylabel('$y_1$', fontsize=label_size)
ax1.set_xlabel('time', fontsize=label_size)
ax2.set_xlabel('$y_0$', fontsize=label_size)
ax2.set_ylabel('$y_1$', fontsize=label_size)
ax2.set_title('Phase Portrait', fontsize=label_size)
plt.figlegend(lines,
labels,
loc='upper right',
bbox_to_anchor=(0.9, 0.9),
fontsize=label_size)
plt.suptitle(title, fontsize=title_size)
plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
plt.show()
def main():
"""Entry point of application."""
program_description = "Lorenz system"
parser = argparse.ArgumentParser(program_description)
parser.add_argument(
"--params",
type=utils.argparse.ntuple(3, float),
default=(10, 28, 8 / 3),
help="parameters σ,r,b for the lorenz system (default: 10,28,8/3)",
)
parser.add_argument("--plot",
help="plot best results",
action="store_true")
app, args = application.default_console_app(Individual, AssessmentRunner,
parser)
app.assessment_runner.params["s"] = args.params[0]
app.assessment_runner.params["r"] = args.params[1]
app.assessment_runner.params["b"] = args.params[2]
app.run()
logger = logging.getLogger(__name__)
logger.info("\n")
logger.info("Hall of Fame:")
for individual in app.gp_runner.pareto_front:
logger.info("{} {}".format(individual.fitness.values,
str(individual)))
if not args.plot:
return
# Plot n best results.
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import seaborn
n = 2
seaborn.set_palette("husl", n + 2)
alpha = 0.7
label_size = 16
title_size = 20
params, yinit = app.assessment_runner.params, app.assessment_runner.yinit
x, target = app.assessment_runner.x, app.assessment_runner.target
title = program_description + "\nparams={}, yinit={}".format(params, yinit)
ax0 = plt.subplot2grid((3, 2), (0, 0))
ax1 = plt.subplot2grid((3, 2), (1, 0))
ax2 = plt.subplot2grid((3, 2), (2, 0))
ax3 = plt.subplot2grid((3, 2), (1, 1), projection="3d", rowspan=2)
lines, labels = [], []
(l, ) = ax0.plot(x, target, linestyle="dotted")
ax1.plot(x, target, linestyle="dotted")
ax2.plot(x, target, linestyle="dotted")
labels.append("target")
lines.append(l)
uncontrolled = Individual.from_string("Add(y_0, Neg(y_0))")
for ind in cons(uncontrolled, app.gp_runner.pareto_front[:n]):
popt = getattr(ind, "popt", np.zeros(len(ind.pset.constants)))
label = "with $a({}) = {}$, $c={}$".format(",".join(ind.pset.args),
str(ind), popt)
label = label.replace("**", "^").replace("*", "\cdot ")
y = app.assessment_runner.trajectory(ind, *popt)
(l, ) = ax0.plot(x, y[0, :], alpha=alpha)
ax1.plot(x, y[1, :], alpha=alpha, color=l.get_color())
ax2.plot(x, y[2, :], alpha=alpha, color=l.get_color())
ax3.plot(y[0, :], y[1, :], y[2, :], alpha=alpha, color=l.get_color())
labels.append(label)
lines.append(l)
ax0.set_ylabel("$y_0$", fontsize=label_size)
ax0.set_xlabel("time", fontsize=label_size)
ax1.set_ylabel("$y_1$", fontsize=label_size)
ax1.set_xlabel("time", fontsize=label_size)
ax2.set_ylabel("$y_2$", fontsize=label_size)
ax2.set_xlabel("time", fontsize=label_size)
ax3.set_xlabel("$y_0$", fontsize=label_size)
ax3.set_ylabel("$y_1$", fontsize=label_size)
ax3.set_title("Phase Portrait", fontsize=label_size)
plt.figlegend(lines,
labels,
loc="upper right",
bbox_to_anchor=(0.9, 0.9),
fontsize=label_size)
plt.suptitle(title, fontsize=title_size)
plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.05)
plt.show()