def shib_register(request, RegisterForm=BaseRegisterForm, register_template_name='shibboleth/register.html'):
attr, error = parse_attributes(request.META)
# In some cases, user might have Shibboleth names set but no email
if attr[settings.SHIB_EMAIL] == None:
attr[settings.SHIB_EMAIL] = '*****@*****.**'
was_redirected = False
if request.REQUEST.has_key('next'):
was_redirected = True
redirect_url = request.REQUEST.get('next', settings.LOGIN_REDIRECT_URL)
context = {'shib_attrs': attr,
'was_redirected': was_redirected}
if error:
return render_to_response('shibboleth/attribute_error.html', context, context_instance=RequestContext(request))
try:
username = attr[settings.SHIB_USERNAME]
except:
return render_to_response('shibboleth/attribute_error.html', context, context_instance=RequestContext(request))
if not attr[settings.SHIB_USERNAME] or attr[settings.SHIB_USERNAME] == '':
return render_to_response('shibboleth/attribute_error.html', context, context_instance=RequestContext(request))
if request.method == 'POST':
form = RegisterForm(request.POST)
if form.is_valid():
user = form.save(attr)
try:
user = User.objects.get(username=attr[settings.SHIB_USERNAME])
except User.DoesNotExist:
form = RegisterForm()
context = {'form': form, 'next': redirect_url, 'shib_attrs': attr, 'was_redirected': was_redirected, }
return render_to_response(register_template_name, context, context_instance=RequestContext(request))
user.set_unusable_password()
try:
user.first_name = attr[settings.SHIB_FIRST_NAME]
user.last_name = attr[settings.SHIB_LAST_NAME]
user.email = attr[settings.SHIB_EMAIL]
except:
pass
user.save()
profile = user.get_profile()
if attr["student_id"] and attr["student_id"] != "":
# This is because a student might previously have had a student id. In that case, we don't want to erase it.
profile.student_id = attr["student_id"].split(':')[-1]
profile.save()
user.backend = 'django.contrib.auth.backends.ModelBackend'
login(request, user)
shib_logon_done.send(sender=shib_register, user=user, shib_attrs=attr)
if not redirect_url or '//' in redirect_url or ' ' in redirect_url:
redirect_url = settings.LOGIN_REDIRECT_URL
return HttpResponseRedirect(redirect_url)
def shib_register(request, RegisterForm=BaseRegisterForm, register_template_name='shibboleth/register.html'):
attr, error = parse_attributes(request.META)
was_redirected = False
if request.REQUEST.has_key('next'):
was_redirected = True
redirect_url = request.REQUEST.get('next', settings.LOGIN_REDIRECT_URL)
context = {'shib_attrs': attr,
'was_redirected': was_redirected}
if error:
return render_to_response('shibboleth/attribute_error.html', context, context_instance=RequestContext(request))
try:
username = attr[settings.SHIB_USERNAME]
except:
return render_to_response('shibboleth/attribute_error.html', context, context_instance=RequestContext(request))
if not attr[settings.SHIB_USERNAME] or attr[settings.SHIB_USERNAME] == '':
return render_to_response('shibboleth/attribute_error.html', context, context_instance=RequestContext(request))
if request.method == 'POST':
form = RegisterForm(request.POST)
if form.is_valid():
user = form.save(attr)
try:
user = User.objects.get(username=attr[settings.SHIB_USERNAME])
except User.DoesNotExist:
form = RegisterForm()
context = {'form': form, 'next': redirect_url, 'shib_attrs': attr, 'was_redirected': was_redirected, }
return render_to_response(register_template_name, context, context_instance=RequestContext(request))
user.set_unusable_password()
try:
user.first_name = attr[settings.SHIB_FIRST_NAME]
user.last_name = attr[settings.SHIB_LAST_NAME]
user.email = attr[settings.SHIB_EMAIL]
except:
pass
user.save()
user.backend = 'django.contrib.auth.backends.ModelBackend'
login(request, user)
shib_logon_done.send(sender=shib_register, user=user, shib_attrs=attr)
if not redirect_url or '//' in redirect_url or ' ' in redirect_url:
redirect_url = settings.LOGIN_REDIRECT_URL
return HttpResponseRedirect(redirect_url)
def process_data(self, data_source):
fp = utils.get_filepath(data_source, 'train')
data = arff.load(open(fp, 'rb'))
class_index, header, data_types = utils.parse_attributes(data)
self.data = []
self.class_sets = []
for row in data['data']:
self.data.append(row[:class_index])
label = reduce(lambda x,y:x+y, row[class_index:])
self.class_sets.append(utils.str_to_set(label))
self.num_data = len(self.class_sets)
self.num_classes = len(label)
self.data = np.array(self.data)
fp = utils.get_filepath(data_source, 'test')
test_data = arff.load(open(fp, 'rb'))
self.test_data = []
self.test_class_sets = []
for row in test_data['data']:
self.test_data.append(row[:class_index])
label = reduce(lambda x,y:x+y, row[class_index:])
self.test_class_sets.append(utils.str_to_set(label))
self.test_num_data = len(self.test_class_sets)
self.test_data = np.array(self.test_data)
new_topk_d = {'emotions': 2, 'scene': 2, 'yeast': 2}
new_topk_loops = {'emotions': 10, 'scene': 10, 'yeast': 10}
# ================================================================
# ADAPTIVE ALGORITHM
ada_topk_best = {'emotions': 0.2427, 'scene': 0.1216}
ada_topk_N = {'emotions': 70, 'scene': 50}
# all other parameters, we'll inherit from optimal hyperparameters
# In[3]:
data_source = 'yeast'
fp = utils.get_filepath(data_source, 'train')
data = arff.load(open(fp, 'rb'))
class_index, header, data_types = utils.parse_attributes(data)
train_rows = data['data']
fp = utils.get_filepath(data_source, 'test')
data = arff.load(open(fp, 'rb'))
test_rows = data['data']
if data_source == 'mediamill_reduced':
train_rows = train_rows[0:400]
test_rows = test_rows[0:100]
loss = 'logistic'
num_wls = 5
num_covs = 20
gamma = 0.3
M = 100
k = 3
def shib_register(request,
RegisterForm=BaseRegisterForm,
register_template_name='shibboleth/register.html'):
attr, error = parse_attributes(request.META)
was_redirected = False
if request.REQUEST.has_key('next'):
was_redirected = True
redirect_url = request.REQUEST.get('next', settings.LOGIN_REDIRECT_URL)
context = {'shib_attrs': attr, 'was_redirected': was_redirected}
if error:
return render_to_response('shibboleth/attribute_error.html',
context,
context_instance=RequestContext(request))
try:
username = attr[settings.SHIB_USERNAME]
except:
return render_to_response('shibboleth/attribute_error.html',
context,
context_instance=RequestContext(request))
if not attr[settings.SHIB_USERNAME] or attr[settings.SHIB_USERNAME] == '':
return render_to_response('shibboleth/attribute_error.html',
context,
context_instance=RequestContext(request))
if request.method == 'POST':
form = RegisterForm(request.POST)
if form.is_valid():
user = form.save(attr)
try:
user = User.objects.get(username=attr[settings.SHIB_USERNAME])
except User.DoesNotExist:
form = RegisterForm()
context = {
'form': form,
'next': redirect_url,
'shib_attrs': attr,
'was_redirected': was_redirected,
}
return render_to_response(register_template_name,
context,
context_instance=RequestContext(request))
user.set_unusable_password()
try:
user.first_name = attr[settings.SHIB_FIRST_NAME]
user.last_name = attr[settings.SHIB_LAST_NAME]
user.email = attr[settings.SHIB_EMAIL]
except:
pass
user.save()
user.backend = 'django.contrib.auth.backends.ModelBackend'
login(request, user)
shib_logon_done.send(sender=shib_register, user=user, shib_attrs=attr)
if not redirect_url or '//' in redirect_url or ' ' in redirect_url:
redirect_url = settings.LOGIN_REDIRECT_URL
return HttpResponseRedirect(redirect_url)
def main():
seed = np.random.randint(1, 999)
# Read params.csv file and parse the options
params = utils.read_params()
loss = params['loss']
data_source = params['data_source']
num_wls = int(params['num_wls'])
num_covs = int(params['num_covs'])
M = int(params['M'])
gamma = params['gamma']
# Load the train data
fp = utils.get_filepath(data_source, 'train')
data = arff.load(open(fp, 'rb'))
class_index, _, _ = utils.parse_attributes(data)
train_rows = data['data']
# Load the test data
fp = utils.get_filepath(data_source, 'test')
data = arff.load(open(fp, 'rb'))
test_rows = data['data']
start = time.time()
model = AdaOLMR(data_source, loss=loss, num_covs=num_covs, gamma=gamma)
model.M = M
model.gen_weaklearners(num_wls,
min_grace=5,
max_grace=20,
min_tie=0.01,
max_tie=0.9,
min_conf=0.01,
max_conf=0.9,
min_weight=3,
max_weight=10,
seed=seed)
for i, row in enumerate(train_rows):
X = row[:class_index]
Y = row[class_index:]
pred = model.predict(X)
model.update(Y)
cum_error = 0
for i, row in enumerate(test_rows):
X = row[:class_index]
Y = row[class_index:]
pred = model.predict(X)
model.update(Y)
cum_error += utils.rank_loss(pred, model.Y)
end = time.time()
runtime = round(end - start, 2)
avg_loss = round(cum_error / float(len(test_rows)), 4)
print 'data_source', data_source
print 'loss', loss
print 'gamma', gamma
print 'num_wls', num_wls
print 'num_covs', num_covs
print 'M', M
print 'seed', seed
print 'runtime', runtime
print 'avg_loss', avg_loss