def clusterize_r_em(*args):
""" Clustering and plotting with EM GMM"""
try:
from rpy2.robjects import r
import rpy2.robjects.numpy2ri
rpy2.robjects.numpy2ri.activate()
except:
print "You need rpy2"
sys.exit(-1)
r.library("mclust")
for arg in args:
model = r.Mclust(arg)
print model
print r.summary(model)
r.quartz("plot")
r.plot(model, arg)
print raw_input("any key to pass")
def clusterize_r_em(*args):
""" Clustering and plotting with EM GMM"""
try:
from rpy2.robjects import r
import rpy2.robjects.numpy2ri
rpy2.robjects.numpy2ri.activate()
except:
print "You need rpy2"
sys.exit(-1)
r.library("mclust")
for arg in args:
model = r.Mclust(arg)
print model
print r.summary(model)
r.quartz("plot")
r.plot(model, arg)
print raw_input("any key to pass")
def clusterize_r_em(*args, **kwargs):
""" Clustering and plotting with EM GMM"""
try:
from rpy2.robjects import r
import rpy2.robjects.numpy2ri
rpy2.robjects.numpy2ri.activate()
from sklearn.decomposition import PCA
except:
print "You need rpy2"
sys.exit(-1)
r.library("mclust")
for arg in args:
if kwargs.get('clf_on_pca', False):
pca = PCA(2)
arg = pca.fit(arg).transform(arg)
model = r.Mclust(arg)
print model
print r.summary(model)
r.quartz("plot")
r.plot(model, arg)
print raw_input("press any key to pass")
