#encoding:latin-1

from py_nnma import *

param = dict(alpha=.1, tau=2, regul=1e-1, sparse_par=1e-1, psi=1e-3)

nc = 10
B = np.random.rand(100,nc)
C = np.random.rand(nc,20)
A = np.dot(B, C)

import sys, time

def run(name, routine):
    print "run %12s" % name,
    sys.stdout.flush()
    start = time.time()
    _,_,obj,count,converged = routine(A, 10, eps=5e-5, verbose= 0, 
                                      maxcount=1000, **param) 
    print "obj = %E  count=%5d  converged=%d  TIME=%.2f secs" % \
                 (obj,count, converged, time.time()-start)

print
print "TEST WITH DENSE MATRIX\n"

run("FNMAI_SPARSE", FNMAI_SPARSE)
run("NNSC", NNSC)
run("FNMAI", FNMAI)
run("GDCLS_L1", GDCLS_L1)
run("GDCLS", GDCLS)
run("ALS", ALS)
run("NMFKL", NMFKL)
run("NMF", NMF)
run("RRI", RRI)
run("FastHALS", FastHALS)
run("SNMF", SNMF)


print
print "TEST WITH SPARSE MATRIX\n"
A = sp.csc_matrix(A)

run("NNSC", NNSC)
run("FNMAI_SPARSE", FNMAI_SPARSE)
run("FNMAI", FNMAI)
run("GDCLS_L1", GDCLS_L1)
run("GDCLS", GDCLS)
run("ALS", ALS)
run("NMFKL", NMFKL)
run("NMF", NMF)
run("RRI", RRI)
run("FastHALS", FastHALS)
run("SNMF", SNMF)