#______________________________________________
timestr = '2021-03-29'
record_path = '../Records/EXP_03_NMNIST/'
print('classic HOTS and homeoHOTS')
for name in ['hots', 'homhots']:
score_s1 = np.zeros([nb_trials, len(var_jit_s)])
score_t1 = np.zeros([nb_trials, len(std_jit_t)])
score_s12 = np.zeros([nb_trials, len(var_jit_s)])
score_t12 = np.zeros([nb_trials, len(std_jit_t)])
f_name = f'{record_path}{timestr}_results_jitter_{nb_test}_histo_{name}_std.pkl'
print(f'{name} clustering...')
hotshom, homeotest = netparam(name, filt, tau, nbclust, sigma, homeinv,
jitter, timestr, dataset, R)
print(f'{name} training...')
trainhistomap = hotshom.running(homeotest=homeotest,
nb_digit=nb_train,
outstyle='histo')
print(f'{name} testing...')
for trial in [5]: #range(nb_trials):
hotshom.date = '2021-03-29_' + str(trial)
for id_jit, jit_s in enumerate(var_jit_s):
jit_s = round(jit_s, 2)
jitonic = [None, jit_s]
if jit_s == 0:
jitonic = [None, None]
testhistomap = hotshom.running(homeotest=homeotest,
train=False,
#______________________________________________
#_______________NB_OF_DIGITS___________________
dataset = 'nmnist'
nb_test = 10000
nb_train = 60000
ds = 10
nb_test = nb_test//ds
nb_train = nb_train//ds
print(f'training set size: {nb_train} - testing set: {nb_test}')
#______________________________________________
timestr = '2021-03-29'
record_path = '../Records/EXP_03_NMNIST/'
print('classic HOTS and homeoHOTS')
for nbclust in [[8,16],[4,8,16],[8,8,16],[16,8,16],[8,16,32],[16,32,64]]:
print(f'architecture: {nbclust}')
for name in ['homhots', 'hots']:
print('clustering...')
hotshom, homeotest = netparam(name, filt, tau, nbclust, sigma, homeinv, jitter, timestr, dataset, R, subset_size = nb_train)
print('training...')
#trainhistomap = hotshom.running(homeotest=homeotest, nb_digit = nb_train, outstyle='LR')
trainhistomap = hotshom.running(homeotest=homeotest, nb_digit = nb_train, outstyle='histo', subset_size = nb_train)
print('testing...')
testhistomap = hotshom.running(homeotest = homeotest, train=False, nb_digit=nb_test, jitonic=jitonic, subset_size = nb_test)
#trainhistomap = hotshom.running(homeotest=homeotest, nb_digit = nb_train, outstyle='histo')
#JS_score = histoscore(trainhistomap,testhistomap, verbose = True)
#trainhistomap = hotshom.running(homeotest=homeotest, nb_digit = nb_train, outstyle='histav')
#JS_score = histoscore_lagorce(trainhistomap,testhistomap, verbose = True)