def converter_isomap_modular(data_fname):
from modshogun import RealFeatures, CSVFile
from modshogun import Isomap
features = RealFeatures(CSVFile(data))
converter = Isomap()
converter.set_k(20)
converter.set_target_dim(1)
converter.apply(features)
return features
def converter_isomap_modular(data_fname):
try:
from modshogun import RealFeatures, Isomap, CSVFile
features = RealFeatures(CSVFile(data))
converter = Isomap()
converter.set_k(20)
converter.set_target_dim(1)
converter.apply(features)
return features
except ImportError:
print('No Eigen3 available')
def converter_isomap_modular (data_fname): from modshogun import RealFeatures, CSVFile from modshogun import Isomap features = RealFeatures(CSVFile(data)) converter = Isomap() converter.set_k(20) converter.set_target_dim(1) converter.apply(features) return features
def converter_isomap_modular (data_fname):
try:
from modshogun import RealFeatures, Isomap, CSVFile
features = RealFeatures(CSVFile(data))
converter = Isomap()
converter.set_k(20)
converter.set_target_dim(1)
converter.apply(features)
return features
except ImportError:
print('No Eigen3 available')
# Compute a second SPE embedding with local strategy
converter.set_strategy(SPE_LOCAL)
converter.set_k(12)
embedding = converter.embed(features)
X = embedding.get_feature_matrix()
fig.add_subplot(2, 2, 3)
pylab.plot(X[0, y1], X[1, y1], 'ro')
pylab.plot(X[0, y2], X[1, y2], 'go')
pylab.title('SPE with local strategy')
# Compute Isomap embedding (for comparison)
converter = Isomap()
converter.set_target_dim(2)
converter.set_k(6)
embedding = converter.embed(features)
X = embedding.get_feature_matrix()
fig.add_subplot(2, 2, 4)
pylab.plot(X[0, y1], X[1, y1], 'ro')
pylab.plot(X[0, y2], X[1, y2], 'go')
pylab.title('Isomap')
pylab.connect('key_press_event', util.quit)