#
np.random.seed(0)
# generate the data
(Xp, Xu, yu) = gendata(100, 100, 0.2)
# generate some lists
theta_list = np.linspace(0, 1, 30)
sigma_list = np.array([0.1, 0.5, 0.8, 1.0])
lambda_list = np.array([0.001, 0.1, 1, 10])
cr = 1
kfolds = 4
# calculate the class prior with cl1fast
fl1_theta, fl1_info = cl1fast(Xp, Xu)
# calculate the class prior
theta, l1_c2info = l1_cpe_cv(Xp, Xu, cr=2)
# plot the result
pyplt.plot(fl1_info['theta_list'], fl1_info['score'], label='fastL1')
pyplt.plot(l1_c2info['theta_list'], l1_c2info['score'], label='l1cr2')
pyplt.xlabel(r'$\theta$')
pyplt.ylabel(r'cl_1')
pyplt.legend(loc='upper center')
pyplt.axis([0, 1, 0, 2])
pyplt.show()
# plot the results
dataset = sys.argv[3]
nunlab = int(sys.argv[4])
npos = int(sys.argv[5])
theta = float(sys.argv[6])
# create the file name and check if simulation was already run (file exists)
datafname = '../results/{dataset}/{dataset}-{method}-theta-{theta}-nu-{nu}-np-{np}-{seed}.mat'.format(dataset=dataset, \
method=method, theta=theta,np=npos, nu=nunlab, seed=seed )
datafname = os.path.abspath(os.path.join(os.getcwd(), datafname))
if os.path.isfile(datafname):
print('Simulation already run for this seed: {0}'.format(datafname))
exit()
# set the simulation function
if method=='cl1':
simfun = lambda Xp, Xu: cl1fast(Xp, Xu)
elif method=='l1c1':
simfun = lambda Xp, Xu: l1_cpe_cv(Xp, Xu, cr=1)
# load the dataset
np.random.seed(seed)
(Xp, Xu, yu) = simdata.loaddataset(datapath, dataset, npos, nunlab, theta)
# time the execution
start_time = time.time()
# run simulation
if method=='cl1':
theta_est, info = cl1fast(Xp, Xu)
elif method=='l1c1':
theta_est, info = l1_cpe_cv(Xp, Xu,cr=1)
