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src/f/c/fcm-0.9.1/src/statistics/cluster.py   fcm(Download)
from scipy.cluster import vq
 
from dpmix import DPNormalMixture, BEM_DPNormalMixture, HDPNormalMixture
from fcm import FCMcollection
 
            seed(datetime.now().microsecond)
 
        self.hdp = HDPNormalMixture(standardized, ncomp=self.nclusts,
                                           gamma0=self.gamma0, m0=self.m0,
                                           nu0=self.nu0, Phi0=self.Phi0,

src/d/p/dpmix-HEAD/bench/bench_hdp.py   dpmix(Download)
import numpy as np
from time import time
from dpmix import HDPNormalMixture
 
# load data
 
    t1 = time()
    mcmc = HDPNormalMixture(data, ncomp=100, gpu=[0,1,2], 
                            parallel=True, verbose=100)
    mcmc.sample(1000, nburn=2000, tune_interval=50)
    imcmc = HDPNormalMixture(mcmc, verbose=100)
 
    t2 = time()
    mcmc = HDPNormalMixture(data, ncomp=100, gpu=[0], 
                            parallel=False, verbose=100)
    mcmc.sample(1000, nburn=2000, tune_interval=50)
    imcmc = HDPNormalMixture(mcmc, verbose=100)

src/d/p/dpmix-HEAD/tests/test_bounds.py   dpmix(Download)
import numpy.random as npr
from dpmix import HDPNormalMixture
 
 
if __name__ == '__main__':
            xs.append(npr.uniform(-5,5,(max_events, 5)))
        print
        mcmc = HDPNormalMixture(xs, ncomp=nclust, gpu=device, parallel=True, verbose=2)
        mcmc.sample(burnin, nburn=0, tune_interval=5)
        imcmc = HDPNormalMixture(mcmc, verbose=2)

src/d/p/dpmix-0.3/tests/test_bounds.py   dpmix(Download)
import numpy.random as npr
from dpmix import HDPNormalMixture
 
 
if __name__ == '__main__':
            xs.append(npr.uniform(-5,5,(max_events, 5)))
        print
        mcmc = HDPNormalMixture(xs, ncomp=nclust, gpu=device, parallel=True, verbose=2)
        mcmc.sample(burnin, nburn=0, tune_interval=5)
        imcmc = HDPNormalMixture(mcmc, verbose=2)