def runTest(conf):
fiberPropotion, Size, trial, Rank, max_time, dir = conf
print(
"Running video trial with the following:\n\tProporion of Fibers = {}\n\tSize = {}\n\tRank = {}\n\tTrialNumber = {}\n\tMax Time = {}"
.format(fiberPropotion, Size, Rank, trial, maxtime))
numberOfFibers = Size**2
FibersSampled = max(int(numberOfFibers * fiberPropotion), 1)
# Create tensor
X = videoToTensor("600Test.mp4")
# init starting
A_init = initDecomposition(Size, Rank)
b0 = 0.25
error, _ = AdaCPDTime(X,
b0,
FibersSampled,
max_time,
A_init,
sample_interval=0.5,
eta=1)
saveAdaTimeTrial(X, fiberPropotion, Size, trial, Rank, b0, max_time, error,
dir)
def runTest(conf):
fiberPropotion, Size, trial, Rank, max_time, nu, eps, lamb = conf
print(
"Running trial with the following:\n\tProporion of Fibers = {}\n\tSize = {}\n\tRank = {}\n\tTrialNumber = {}\n\tMax Time = {}\n\tnu = {}\n\teps={}"
.format(fiberPropotion, Size, Rank, trial, maxtime, nu, eps))
# Create tensor
X = createTensor(Size, Rank)
# init starting
A_init = initDecomposition(Size, Rank)
# X, F, sketching_rates, lamb, eps, eta, Hinit, max_time ,sample_interval=.5
_, _, _, error, rates = CPDMWUTime(X,
Rank,
fiberPropotion,
lamb,
eps,
nu,
A_init,
max_time,
sample_interval=0.5)
return sum([error[x] for x in error.keys() if x > 5]) / len(
[error[x] for x in error.keys() if x > 5])
def runTest(conf):
print("running")
fiberPropotion, Size, trial, Rank, max_time, dir, c_eps, c_eta = conf
random.seed
eps = 1 / (c_eps * len(fiberPropotion))
eta = sqrt(2 * log(len(fiberPropotion)) / c_eta)
lamb = 0.001
if eps > 1:
print("eps")
return
# Create tensor
X = createTensor(Size, Rank)
# init starting
A_init = initDecomposition(Size, Rank)
b0 = 0.25
# X, F, sketching_rates, lamb, eps, eta, Hinit, max_time ,sample_interval=.5
print(
"Running trial with the following:\n\tProporion of Fibers = {}\n\tSize = {}\n\tRank = {}\n\tTrialNumber = {}\n\tMax Time = {}"
.format(fiberPropotion, Size, Rank, trial, maxtime))
print("\tc_eps = {}\n\teps={}\n\tc_eta={}\n\teta={}".format(
c_eps, eps, c_eta, eta))
_, _, _, error, rates = CPDMWUTime(X,
Rank,
fiberPropotion,
lamb,
eps,
eta,
A_init,
max_time,
sample_interval=0.5)
saveCPDTimeTrial(
X,
fiberPropotion,
lamb,
eps,
eta,
Size,
trial,
Rank,
max_time,
error,
rates,
c_eps,
c_eta,
dir,
)
def runTest(conf):
fiberPropotion, Size, trial, Rank, max_time,dir = conf
print("Running trial with the following:\n\tProporion of Fibers = {}\n\tSize = {}\n\tRank = {}\n\tTrialNumber = {}\n\tMax Time = {}".format(fiberPropotion, Size, Rank, trial, maxtime))
#Create tensor
X = videoToTensor('600Test.mp4')
#init starting
A_init = initDecomposition(Size,Rank)
#X, F, sketching_rates, lamb, eps, nu, Hinit, max_time ,sample_interval=.5
eps = 1/(1.2len(fiberPropotion))
nu = sqrt(2 * log(len(fiberPropotion))/50)
lamb = .001
A,B,C,error,rates = CPDMWUTime(X, Rank, fiberPropotion, lamb, eps, nu, A_init, max_time,sample_interval=.5)
saveCPDTimeTrial(X,A,B,C, fiberPropotion, lamb, eps, nu, Size, trial, Rank, max_time, error,rates,dir)
eta_ada = 1
iterations_total = 100
lamb = 0.01
proprtions = np.linspace(0.01, 1, num=10)
eps = 1 / (len(proprtions))
eta_cpd = sqrt(2 * log(len(proprtions)))
X = createTensor(Size, Rank)
# init starting
A_init = initDecomposition(Size, Rank)
A, B, C = A_init[0], A_init[1], A_init[2]
numberOfFibers = Size ** 2
FibersSampled = (numberOfFibers * proprtions).astype(int)
n_mb = 100 # 200*200//5#FibersSampled[5]
norm_x = linalg.norm(X)
errors = {0: ("init", error(X, [A, B, C], norm_x))}
start_time = time.time()
configurationada = collections.namedtuple(
"Configuration", "X b0 fibers A B C eta Gt norm_x iterations start_time errors"
)