def _plot_result(fANOVA, configspace, directory, yrange=None):
vis = Visualizer(fANOVA, configspace)
try:
os.makedirs(directory)
except FileExistsError:
pass
for hp in configspace.get_hyperparameters():
plt.close('all')
plt.clf()
param = hp.name
outfile_name = os.path.join(directory,
param.replace(os.sep, "_") + ".pdf")
if isinstance(hp, (CategoricalHyperparameter)):
vis.plot_categorical_marginal(
configspace.get_idx_by_hyperparameter_name(param),
show=False,
ylabel='Predictive Accuracy')
else:
vis.plot_marginal(
configspace.get_idx_by_hyperparameter_name(param),
resolution=100,
show=False,
ylabel='Predictive Accuracy')
x1, x2, _, _ = plt.axis()
if yrange:
plt.axis((x1, x2, yrange[0], yrange[1]))
plt.savefig(outfile_name)
pass
def plot_result(self, name='fANOVA', show=True):
if not os.path.exists(name):
os.mkdir(name)
vis = Visualizer(self.evaluator,
self.cs,
directory=name,
y_label=self._get_label(self.scenario.run_obj))
self.logger.info('Getting Marginals!')
pbar = tqdm(range(self.to_evaluate),
ascii=True,
disable=not self.verbose)
for i in pbar:
plt.close('all')
plt.clf()
param = list(self.evaluated_parameter_importance.keys())[i]
# Plot once in log, once linear
for mode in [(True, '_log'), (False, '')]:
outfile_name = os.path.join(
name,
param.replace(os.sep, "_") + mode[1] + ".png")
# The try/except clause is only for back-compatibility with fanova <= 2.0.11
try:
vis.plot_marginal(
self.cs.get_idx_by_hyperparameter_name(param),
log_scale=mode[0],
show=False,
incumbents=self.incumbents)
except TypeError:
self.logger.debug(
"Plotting incumbents not supported by fanova < 2.0.12")
vis.plot_marginal(
self.cs.get_idx_by_hyperparameter_name(param),
log_scale=mode[0],
show=False)
fig = plt.gcf()
fig.savefig(outfile_name)
plt.close('all')
plt.clf()
if show:
plt.show()
pbar.set_description('Creating fANOVA plot: {: <.30s}'.format(
outfile_name.split(os.path.sep)[-1]))
if self.pairwise:
self.logger.info('Plotting Pairwise-Marginals!')
most_important_ones = list(
self.evaluated_parameter_importance.keys(
))[:min(self.num_single, self.n_most_imp_pairs)]
vis.create_most_important_pairwise_marginal_plots(
most_important_ones)
try:
vis.create_most_important_pairwise_marginal_plots(
most_important_ones)
except TypeError as err:
self.logger.debug(err, exc_info=1)
self.logger.warning('Could not create pairwise plots!')
plt.close('all')
def plot_result(self, name='fANOVA', show=True):
if not os.path.exists(name):
os.mkdir(name)
if self.scenario.run_obj == 'runtime':
label = 'runtime [sec]'
elif self.scenario.run_obj == 'quality':
label = 'cost'
else:
label = '%s' % self.scenario.run_obj
vis = Visualizer(self.evaluator,
self.cs,
directory=name,
y_label=label)
self.logger.info('Getting Marginals!')
pbar = tqdm(range(self.to_evaluate),
ascii=True,
disable=not self.verbose)
for i in pbar:
plt.close('all')
plt.clf()
param = list(self.evaluated_parameter_importance.keys())[i]
outfile_name = os.path.join(name,
param.replace(os.sep, "_") + ".png")
vis.plot_marginal(self.cs.get_idx_by_hyperparameter_name(param),
log_scale=False,
show=False)
fig = plt.gcf()
fig.savefig(outfile_name)
plt.close('all')
plt.clf()
outfile_name = os.path.join(
name,
param.replace(os.sep, "_") + "_log.png")
vis.plot_marginal(self.cs.get_idx_by_hyperparameter_name(param),
log_scale=True,
show=False)
fig = plt.gcf()
fig.savefig(outfile_name)
plt.close('all')
plt.clf()
if show:
plt.show()
pbar.set_description('Creating fANOVA plot: {: <.30s}'.format(
outfile_name.split(os.path.sep)[-1]))
if self.pairwise:
self.logger.info('Plotting Pairwise-Marginals!')
most_important_ones = list(
self.evaluated_parameter_importance.keys(
))[:min(self.num_single, self.n_most_imp_pairs)]
try:
vis.create_most_important_pairwise_marginal_plots(
most_important_ones)
except TypeError:
self.logger.warning('Could not create pairwise plots!')
plt.close('all')
def _plot_result(fANOVA, configspace, directory, yrange=None):
os.makedirs(directory, exist_ok=True)
vis = Visualizer(fANOVA, configspace, directory, y_label='Predictive Accuracy')
for hp1 in configspace.get_hyperparameters():
plt.close('all')
plt.clf()
param = hp1.name
outfile_name = os.path.join(directory, param.replace(os.sep, "_") + ".pdf")
vis.plot_marginal(configspace.get_idx_by_hyperparameter_name(param), show=False)
x1, x2, _, _ = plt.axis()
if yrange:
plt.axis((x1, x2, yrange[0], yrange[1]))
plt.savefig(outfile_name)
pass
def plot_result(self, name='fANOVA', show=True):
if not os.path.exists(name):
os.mkdir(name)
vis = Visualizer(self.evaluator, self.cs, directory=name)
self.logger.info('Getting Marginals!')
for i in range(self.to_evaluate):
plt.close('all')
plt.clf()
param = list(self.evaluated_parameter_importance.keys())[i]
outfile_name = os.path.join(name,
param.replace(os.sep, "_") + ".png")
vis.plot_marginal(self.cs.get_idx_by_hyperparameter_name(param),
show=False)
fig = plt.gcf()
fig.savefig(outfile_name)
if show:
plt.show()
self.logger.info('Creating fANOVA plot: %s' % outfile_name)
self.logger.info('Plotting Pairwise-Marginals!')
most_important_ones = list(self.evaluated_parameter_importance.keys(
))[:min(self.num_single, self.n_most_imp_pairs)]
vis.create_most_important_pairwise_marginal_plots(most_important_ones)
plt.close('all')
def plot_result(self, name='fANOVA'):
vis = Visualizer(self.evaluator, self.cs)
if not os.path.exists(name):
os.mkdir(name)
self.logger.info('Getting Marginals!')
for i in range(self.to_evaluate):
plt.close('all')
plt.clf()
param = list(self.evaluated_parameter_importance.keys())[i]
outfile_name = os.path.join(name,
param.replace(os.sep, "_") + ".png")
if isinstance(self.cs.get_hyperparameter(param),
(CategoricalHyperparameter)):
vis.plot_categorical_marginal(
self.cs.get_idx_by_hyperparameter_name(param), show=False)
else:
vis.plot_marginal(
self.cs.get_idx_by_hyperparameter_name(param), show=False)
plt.savefig(outfile_name)
self.logger.info('Creating fANOVA plot: %s' % outfile_name)
self.logger.info('Getting Pairwise-Marginals!')
self.logger.info('This will take some time!')
vis.create_most_important_pairwise_marginal_plots(
name, self.to_evaluate)