def credentials(save = None):
clientId = config.get('clientId')
clientSecret = config.get('clientSecret')
if not clientId:
clientId = DEFAULT_CLIENT_ID
clientSecret = DEFAULT_CLIENT_SECRET
refreshToken = config.get('refreshToken')
if refreshToken:
LOGGER.debug('Using stored refresh token...')
return oauth2client.client.OAuth2Credentials(None, clientId,
clientSecret, refreshToken, None,
oauth2client.GOOGLE_TOKEN_URI, None)
flow = oauth2client.client.OAuth2WebServerFlow(clientId, clientSecret,
OAUTH_SCOPE, REDIRECT_URI,
access_type = 'offline', approval_prompt = 'force')
url = flow.step1_get_authorize_url()
print 'Please open the following URL: '
print url
authorizationCode = raw_input('Copy and paste the authorization code: ').strip()
LOGGER.debug('Requesting new refresh token...')
credentials = flow.step2_exchange(authorizationCode)
refreshToken = credentials.refresh_token
print 'Refresh token: ' + refreshToken
if utils.firstNonNone(save, False):
config.set('refreshToken', refreshToken)
config.save()
return credentials
def save_to_conf(module, src):
def s(x):
try:
return src[module + "." + x][0]
except:
return None
typ = r.ui.progs[module]
conf = c.cfg[module]
for j in [*typ]:
if typ[j] == "label":
pass
if typ[j] == "action":
pass
if typ[j] == "multi":
conf[j] = src[module + "." + j]
elif typ[j] == "checkbox":
if s(j) is not None:
conf[j] = True
else:
conf[j] = False
elif typ[j] == "number" or typ[j] == "range":
try:
conf[j] = int(s(j))
except:
conf[j] = 1
else:
conf[j] = str(s(j))
config.save()
def onClose(self, evt): config.conf["upgrade"]["newLaptopKeyboardLayout"] = True try: config.save() except: pass self.EndModal(0)
def _append_data(analysis):
"""append source scores across subjects"""
try:
stcs, connectivity = load('score_source', subject='fsaverage',
analysis=analysis['name'])
except Exception:
stcs = list()
for meg_subject, subject in zip(range(1, 21), subjects_id):
if subject in bad_mri:
continue
# load
stc, _, _ = load('evoked_source', subject=meg_subject,
analysis=analysis['name'])
morph = load('morph', subject=meg_subject)
vertices_to = [np.arange(10242)] * 2
# fix angle error scale
if 'circAngle' in analysis['name']:
stc._data /= 2.
# apply morph
stc_morph = morph_data_precomputed(subject, 'fsaverage', stc,
vertices_to, morph)
stcs.append(stc_morph.data)
stcs = np.array(stcs)
save([stcs, connectivity], 'score_source', subject='fsaverage',
analysis=analysis['name'], overwrite=True, upload=True)
return stcs, connectivity
def _append_data(analysis):
"""append source scores across subjects"""
try:
stcs, connectivity = load('score_source',
subject='fsaverage',
analysis=analysis['name'])
except Exception:
stcs = list()
for meg_subject, subject in zip(range(1, 21), subjects_id):
if subject in bad_mri:
continue
# load
stc, _, _ = load('evoked_source',
subject=meg_subject,
analysis=analysis['name'])
morph = load('morph', subject=meg_subject)
vertices_to = [np.arange(10242)] * 2
# fix angle error scale
if 'circAngle' in analysis['name']:
stc._data /= 2.
# apply morph
stc_morph = morph_data_precomputed(subject, 'fsaverage', stc,
vertices_to, morph)
stcs.append(stc_morph.data)
stcs = np.array(stcs)
save([stcs, connectivity],
'score_source',
subject='fsaverage',
analysis=analysis['name'],
overwrite=True,
upload=True)
return stcs, connectivity
def save_scores(df):
# attributes to save
keep_cols = [
"datetime",
"season_week",
"team1",
"team2",
"result",
"pg_score1",
"pg_score2",
"elo_prob1",
"carm-elo_prob1",
"raptor_prob1",
]
# my models
keep_cols += [
c for c in df.columns
if c.startswith("result_") and c.endswith("prob1")
]
#
df_out = df[keep_cols].sort_values(["datetime", "team1"])
df_out.loc[df_out.datetime >= config.get("date", "today"), "result"] = ""
df_out = df_out.fillna("")
# View today's games
# df_out[df_out.datetime >= config.get('date', 'today')].head(20)
save(df_out,
dir="output",
filename="all_scores",
ext=".csv",
main=True,
date=False)
def register(ctx, ip):
"""Register an authorized user on your bridge."""
conf_file = ctx.obj["conf_file"]
url = "http://%s/api" % ip
payload = {"devicetype": "hue-client.py"}
r = requests.post(url, json=payload)
if r.status_code != 200:
print("Could not communicate with %s. Check the IP, or run 'search'.")
return
else:
print("Please press the button on your Hue bridge...")
sys.stdout.write("Waiting...")
for i in range(0, 31):
sys.stdout.write(" %d" % (30 - i))
sys.stdout.flush()
r = requests.post(url, json=payload)
json = r.json()
if r.status_code == 200 and isinstance(json, list):
if "success" in json[0] and "username" in json[0]["success"]:
username = json[0]["success"]["username"]
config.save({"ip": ip, "username": username}, conf_file)
print(" Bingo!")
print("\nRegistered user %s." % username)
break
else:
sleep(1)
continue
def opt(self, cutoff, instates, prestates, C):
instates, prestates = int(instates), int(prestates)
config.lpcfg = LPCFG_Surrogate()
self.smooth(self.get_length(cutoff, instates, prestates), C)
config.save()
from parsing import parser
import multiprocessing as mp
try:
mp.set_start_method('fork')
except RuntimeError:
pass
parser.parse_devset(config.test_file)
import subprocess
subprocess.Popen(['cd', 'parsing'])
subprocess.Popen(['python3', 'parser.py'])
subprocess.Popen(['cd', '..'])
process = subprocess.Popen(['./evalb', '-p', 'new.prm', config.test_file, 'output/parse.txt'],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = process.communicate()
output = str(stdout)
i = output.find('FMeasure = ')
return float(output[i + 18:i + 23])
def process_data_files():
#TODO: fix bug
#new_config = get_new_new_config()
#config.load()
#config.config["modules"]["goagent"]["current_version"] = new_config["modules"]["goagent"]["current_version"]
#config.config["modules"]["launcher"]["current_version"] = new_config["modules"]["launcher"]["current_version"]
config.save()
def quit():
bulletmanager.shutdown()
scriptmanager.shutdown()
video.shutdown()
pygame.quit()
config.save("config.cfg")
sys.exit(0)
def _stats(analysis):
"""2nd order stats across subjects"""
# if already computed lets just load it
ana_name = 'stats_' + analysis['name'] + '_vhp'
if op.exists(paths('score', analysis=ana_name)):
return load('score', analysis=ana_name)
# gather scores across subjects
scores = list()
for subject in range(1, 21):
kwargs = dict(subject=subject, analysis=analysis['name'] + '_vhp')
fname = paths('score', **kwargs)
if op.exists(fname):
score, times = load(**kwargs)
else:
score, times = _decod(subject, analysis)
scores.append(score)
scores = np.array(scores)
# compute stats across subjects
p_values = stats(scores - analysis['chance'])
diag_offdiag = scores - np.tile([np.diag(sc) for sc in scores],
[len(times), 1, 1]).transpose(1, 0, 2)
p_values_off = stats(diag_offdiag)
# Save stats results
out = dict(scores=scores, p_values=p_values, p_values_off=p_values_off,
times=times, analysis=analysis)
save(out, 'score', analysis=ana_name)
return out
def process_data_files():
# TODO: fix bug
# new_config = get_new_new_config()
# config.load()
# config.config["modules"]["gae_proxy"]["current_version"] = new_config["modules"]["gae_proxy"]["current_version"]
# config.config["modules"]["launcher"]["current_version"] = new_config["modules"]["launcher"]["current_version"]
config.save()
def callback(self, event):
try:
if event.widget.cget("text") == "Browse":
if self.opt == "get_seq": self.browse_get_seq()
if self.opt == "lost": self.browse_get_seq()
if self.opt == "errors": self.browse_errors()
if self.opt == "graph": self.browse_graphics()
if self.opt == "select": self.browse_select()
if event.widget.cget("text") == "Execute":
cfgn.save(self)
qlibs.create_path(qlibs.get_datadir() + self.pop.get() + "/")
if self.opt == "get_seq": self.get_seq()
if self.opt == "lost": self.lost()
if self.opt == "reverse": self.reverse()
if self.opt == "quad_search": self.quad_search()
if self.opt == "errors": self.errors()
if self.opt == "dist": self.dist()
if self.opt == "graph": self.graphics()
if self.opt == "select": self.select()
if self.opt == "intersect": self.intersections()
messagebox.showinfo("Quad", "END!")
if event.widget.cget("text") == "Confirm":
cfgn.save(self)
except:
pass
return
def req_config_handler(self):
req = urlparse.urlparse(self.path).query
reqs = urlparse.parse_qs(req, keep_blank_values=True)
data = ''
if reqs['cmd'] == ['get_config']:
config.load()
data = '{ "check_update": "%d" }' % (
config.config["update"]["check_update"])
elif reqs['cmd'] == ['set_config']:
if reqs['check_update']:
check_update = int(reqs['check_update'][0])
if check_update != 0 and check_update != 1:
data = '{"res":"fail, check_update:%s"}' % check_update
else:
config.config["update"]["check_update"] = int(check_update)
config.save()
data = '{"res":"success"}'
else:
data = '{"res":"fail"}'
mimetype = 'text/plain'
self.wfile.write(
('HTTP/1.1 200\r\nContent-Type: %s\r\nContent-Length: %s\r\n\r\n' %
(mimetype, len(data))).encode())
self.wfile.write(data)
def _analyze_toi(analysis):
"""Subscore each analysis as a function of the reported visibility"""
ana_name = analysis['name'] + '-toi'
# don't recompute if not necessary
fname = paths('score', analysis=ana_name)
if os.path.exists(fname):
return load('score', analysis=ana_name)
# gather data
n_subject = 20
scores = dict(visibility=np.zeros((n_subject, len(tois), 4)),
contrast=np.zeros((n_subject, len(tois), 3)))
R = dict(visibility=np.zeros((n_subject, len(tois))),
contrast=np.zeros((n_subject, len(tois))),)
for s, subject in enumerate(subjects):
gat, _, events_sel, events = load('decod', subject=subject,
analysis=analysis['name'])
events = events.iloc[events_sel].reset_index()
for t, toi in enumerate(tois):
# Average predictions on single trials across time points
y_pred = _average_ypred_toi(gat, toi, analysis)
# visibility
for factor in ['visibility', 'contrast']:
# subscore per condition (e.g. each visibility rating)
scores[factor][s, t, :] = _subscore(y_pred, events,
analysis, factor)
# correlate residuals with factor
R[factor][s, t] = _subregress(y_pred, events,
analysis, factor, True)
save([scores, R], 'score', analysis=ana_name, overwrite=True, upload=True)
return [scores, R]
def set_template_config(request, collection_name, wiki_key):
new_config = json.loads(request.body)
conf_name = new_config["name"]
conf_type = new_config["type"]
collection = models.Collection.objects.get(name=collection_name)
wiki = models.Wiki.objects.get(wiki_key=wiki_key)
try:
config = models.Template.objects.get(
collection=collection,
wiki=wiki,
type=conf_type,
name=conf_name,
)
except models.Template.DoesNotExist:
# create if does not exist
config = models.Template(
collection=collection,
wiki=wiki,
type=conf_type,
name=conf_name,
# set as default if first template of this type
is_default=not models.Template.objects.filter(
collection__name=collection.name,
wiki=wiki,
type=conf_type,
).exists(),
)
config.template_file.save(f"{wiki_key}-{conf_name}",
ContentFile(new_config["template"]))
config.save()
return HttpResponse(status=200)
def train():
cleanup.cleanup()
c.save(c.work_dir)
data_loader = TextLoader(c.work_dir, c.batch_size, c.seq_length)
with open(os.path.join(c.work_dir, 'chars_vocab.pkl'), 'wb') as f:
cPickle.dump((data_loader.chars, data_loader.vocab), f)
model = Model(c.rnn_size, c.num_layers, len(data_loader.chars), c.grad_clip, c.batch_size, c.seq_length)
with tf.Session() as sess:
tf.initialize_all_variables().run()
saver = tf.train.Saver(tf.all_variables())
for e in range(c.num_epochs):
sess.run(tf.assign(model.lr, c.learning_rate * (c.decay_rate ** e)))
data_loader.reset_batch_pointer()
state = model.initial_state.eval()
for b in range(data_loader.num_batches):
start = time.time()
x, y = data_loader.next_batch()
feed = {model.input_data: x, model.targets: y, model.initial_state: state}
train_loss, state, _ = sess.run([model.cost, model.final_state, model.train_op], feed)
end = time.time()
print("{}/{} (epoch {}), train_loss = {:.3f}, time/batch = {:.3f}"
.format(e * data_loader.num_batches + b,
c.num_epochs * data_loader.num_batches,
e, train_loss, end - start))
if (e * data_loader.num_batches + b) % c.save_every == 0:
checkpoint_path = os.path.join(c.work_dir, 'model.ckpt')
saver.save(sess, checkpoint_path, global_step=e * data_loader.num_batches + b)
print("model saved to {}".format(checkpoint_path))
def _analyze_continuous(analysis):
"""Regress prediction error as a function of visibility and contrast for
each time point"""
ana_name = analysis['name'] + '-continuous'
# don't recompute if not necessary
fname = paths('score', analysis=ana_name)
if os.path.exists(fname):
return load('score', analysis=ana_name)
# gather data
n_subject = 20
n_time = 151
scores = dict(visibility=np.zeros((n_subject, n_time, 4)),
contrast=np.zeros((n_subject, n_time, 3)))
R = dict(visibility=np.zeros((n_subject, n_time)),
contrast=np.zeros((n_subject, n_time)),)
for s, subject in enumerate(subjects):
gat, _, events_sel, events = load('decod', subject=subject,
analysis=analysis['name'])
events = events.iloc[events_sel].reset_index()
y_pred = np.transpose(get_diagonal_ypred(gat), [1, 0, 2])[..., 0]
for factor in ['visibility', 'contrast']:
# subscore per condition (e.g. each visibility rating)
scores[factor][s, :, :] = _subscore(y_pred, events,
analysis, factor)
# correlate residuals with factor
R[factor][s, :] = _subregress(y_pred, events,
analysis, factor, True)
times = gat.train_times_['times']
save([scores, R, times], 'score', analysis=ana_name,
overwrite=True, upload=True)
return [scores, R, times]
def _stats(analysis):
"""2nd order stats across subjects"""
# if already computed lets just load it
ana_name = 'stats_' + analysis['name'] + '_vhp'
if op.exists(paths('score', analysis=ana_name)):
return load('score', analysis=ana_name)
# gather scores across subjects
scores = list()
for subject in range(1, 21):
kwargs = dict(subject=subject, analysis=analysis['name'] + '_vhp')
fname = paths('score', **kwargs)
if op.exists(fname):
score, times = load(**kwargs)
else:
score, times = _decod(subject, analysis)
scores.append(score)
scores = np.array(scores)
# compute stats across subjects
p_values = stats(scores - analysis['chance'])
diag_offdiag = scores - np.tile([np.diag(sc) for sc in scores],
[len(times), 1, 1]).transpose(1, 0, 2)
p_values_off = stats(diag_offdiag)
# Save stats results
out = dict(scores=scores,
p_values=p_values,
p_values_off=p_values_off,
times=times,
analysis=analysis)
save(out, 'score', analysis=ana_name)
return out
def main():
res = packitems(os.getcwd())
res["HOST_MACHINE"] = socket.gethostname()
import config
config.save(res)
return res
def choose(chat, message, args, sender):
if len(args) == 1:
if args[0].lower() == '--listen':
listeners.append(chat.Name)
conf = config.config()
config_operators = conf.get('mc_listens', [])
if chat.Name in config_operators:
chat.SendMessage("This chat is already listening to Minecraft service statuses.")
return
config_operators.append(chat.Name)
conf['mc_listens'] = config_operators
config.save(conf)
return
elif args[0].lower() == '--unlisten':
conf = config.config()
config_operators = conf.get('mc_listens', [])
if chat.Name not in config_operators:
chat.SendMessage("This chat is not currently listening to Minecraft service statuses.")
return
config_operators.remove(chat.Name)
conf['mc_listens'] = config_operators
config.save(conf)
return
else:
service = args[0]
if service in get_statuses():
chat.SendMessage(format_status(service))
return
else:
chat.SendMessage("Service not found.")
return
chat.SendMessage(format_status())
def save_state(start_num, tag_index):
config = model.Config.select().where(model.Config.name == "continue").limit(1).first()
if config is None:
model.Config.create(name="continue", value=json.dumps({ "start_num": start_num, "tag_index": tag_index }))
else:
config.value = json.dumps({ "start_num": start_num, "tag_index": tag_index })
config.save()
def main():
df = df_with_538()
df_scored = score_df(df)
# Each of these functions is updating df
df_scored2, df_acc = benchmark_model_accuracy(df_scored)
# pandas groupby means
_ = week_accuracies(df_scored2)
df_records = all_records(df_scored2, freq=True)
# Save out
save_scores(df_scored)
save(df_acc,
dir="output",
filename="acc_overall",
ext=".csv",
main=True,
date=False)
save(df_records,
dir="output",
filename="records",
ext=".csv",
main=True,
date=False)
def registerPress():
addr: str = app.getEntry("Server Address")
token: str = app.getEntry("Device-Token")
uname = platform.uname()
if addr != "" and token != "":
if "http" not in addr:
addr = "http://" + addr
app.setLabel("info", "Trying to contact cmm server")
registerRequest = req.post(addr + "/api/devices/register",
json={
"loginsecret": token,
"name": uname.node,
"os": uname.system,
"osshort": uname.system[0:3],
"arch": uname.machine,
"mac": "Na"
},
verify=False)
responseCode = registerRequest.status_code
if responseCode <= 200 or responseCode >= 300:
app.setLabel(
"info",
"Something went wrong, token probably invalid\nStatus code: " +
str(responseCode))
else:
jsonData = json.loads(registerRequest.text)
config.config["endpointURL"] = addr
config.config["secret"] = jsonData["clientSecret"]
config.config["uuid"] = jsonData["uuid"]
config.save(config.config)
app.setLabel("info", "Successfully registered device")
app.hideSubWindow("Register this device")
else:
app.setLabel("info", "You have to specify everything")
def testConfig(self):
logger.debug('-'*26 + '\n')
logger.info('Running simple configuration test...')
import config
config.check()
config.reload()
configdata = str(config.get_config())
config.set('testval', 1337)
if not config.get('testval', None) is 1337:
self.assertTrue(False)
config.set('testval')
if not config.get('testval', None) is None:
self.assertTrue(False)
config.save()
config.reload()
if not str(config.get_config()) == configdata:
self.assertTrue(False)
self.assertTrue(True)
def on_main_window_delete_event(self, _widget, _event):
self.conf.set('GUI', 'show_private_groups', str(self.show_private_groups))
self.conf.set('GUI', 'show_system_groups', str(self.show_system_groups))
visible_cols = [col.get_title() for col in self.users_tree.get_columns() if col.get_visible()]
self.conf.set('GUI', 'visible_user_columns', ','.join(visible_cols))
config.save()
exit()
def connect2ap(ssid=None, pw=None):
""" If pw is None get the password from the config file
If pw is not None, write ssid,pw to the config file
If ip is None in config file choose dhcp config
else get ip.
If gw is None it is assumed as 192.168.2.254,
If dns is None it is assumed as 192.168.2.254,
Deactivate the wlan, wait 1 second and activate with given ssid and pw
"""
log.info("Connecting to ap %s", ssid)
if not ssid:
ssid = config.get("ssid", "xxxx")
else:
config.put("ssid", ssid)
if not pw:
pw = config.get(ssid, "geheim")
else:
config.put(ssid, pw)
ip = config.get("wlan_ip")
gw = config.get("wlan_gw", "192.168.2.254")
dns = config.get("wlan_dns", "192.168.2.254")
config.save()
wlan.active(False)
wlan.active(True)
if ip:
wconf = (ip, '255.255.255.0', gw, dns)
wlan.ifconfig(wconf)
wlan.connect(ssid, pw)
def setup_config():
if not os.path.exists(config._configfile):
# this is the default config, it will be overwritten if a config file already exists. Else, it saves it
conf_data = readstatic.read_static('default_config.json', ret_bin=False)
config.set_config(json.loads(conf_data))
config.save()
config.reload()
settings = 0b000
if config.get('log.console.color', True):
settings = settings | USE_ANSI
if config.get('log.console.output', True):
settings = settings | OUTPUT_TO_CONSOLE
if config.get('log.file.output', True):
settings = settings | OUTPUT_TO_FILE
set_settings(settings)
verbosity = str(config.get('log.verbosity', 'default')).lower().strip()
if not verbosity in ['default', 'null', 'none', 'nil']:
map = {
str(LEVEL_DEBUG) : LEVEL_DEBUG,
'verbose' : LEVEL_DEBUG,
'debug' : LEVEL_DEBUG,
str(LEVEL_INFO) : LEVEL_INFO,
'info' : LEVEL_INFO,
'information' : LEVEL_INFO,
str(LEVEL_WARN) : LEVEL_WARN,
'warn' : LEVEL_WARN,
'warning' : LEVEL_WARN,
'warnings' : LEVEL_WARN,
str(LEVEL_ERROR) : LEVEL_ERROR,
'err' : LEVEL_ERROR,
'error' : LEVEL_ERROR,
'errors' : LEVEL_ERROR,
str(LEVEL_FATAL) : LEVEL_FATAL,
'fatal' : LEVEL_FATAL,
str(LEVEL_IMPORTANT) : LEVEL_IMPORTANT,
'silent' : LEVEL_IMPORTANT,
'quiet' : LEVEL_IMPORTANT,
'important' : LEVEL_IMPORTANT
}
if verbosity in map:
set_level(map[verbosity])
else:
logger.warn('Verbosity level %s is not valid, using default verbosity.' % verbosity)
if type(config.get('client.webpassword')) is type(None):
config.set('client.webpassword', base64.b16encode(os.urandom(32)).decode('utf-8'), savefile=True)
if type(config.get('client.client.port')) is type(None):
randomPort = netcontroller.get_open_port()
config.set('client.client.port', randomPort, savefile=True)
if type(config.get('client.public.port')) is type(None):
randomPort = netcontroller.get_open_port()
config.set('client.public.port', randomPort, savefile=True)
if type(config.get('client.api_version')) is type(None):
config.set('client.api_version', onionrvalues.API_VERSION, savefile=True)
def action_ok(self, event):
if confirm_dialog(self):
selected = []
for element in self.selected_list_model.elements():
selected.append(element)
c.set_default('PLUGIN_LIST', selected)
c.save()
self.dispose()
def restart_pi():
logger.info('Sending restart command to Raspberry Pi...')
config.save()
command = "/usr/bin/sudo /sbin/shutdown -r now"
process = subprocess.Popen(command.split(), stdout=subprocess.PIPE)
output = process.communicate()[0]
print output
def onOk(self, evt): config.conf["keyboard"]["useCapsLockAsNVDAModifierKey"] = self.capsAsNVDAModifierCheckBox.IsChecked() config.conf["general"]["showWelcomeDialogAtStartup"] = self.showWelcomeDialogAtStartupCheckBox.IsChecked() try: config.save() except: pass self.Close()
def generate_new_uuid():
node_id = uuid.getnode()
xx_net_uuid = str(uuid.uuid4())
config.config["update"]["node_id"] = node_id
config.config["update"]["uuid"] = xx_net_uuid
logging.info("generate node_id:%s", node_id)
logging.info("generate uuid:%s", xx_net_uuid)
config.save()
def save(self):
if self._config.last_saved is None:
return self.saveAs()
else:
config.save(self._config.last_saved, self.values)
self.undo.undo() # unstack last change
self.handleChanges(dirty=False) # will stack current values
return True
def set_rotation(self, rotation):
platform = self.bookshelf.platform
if platform.hasProperty('DISABLE_ROTATION') and platform.getProperty('DISABLE_ROTATION') == 'true':
self.menu_item_rotation_0.selected = 1
else:
c.set_default('SCREEN_ROTATION', rotation)
c.save()
self.reconfigure()
def create_project(project_name, branch_base, branch_merge):
config.main['projects'][project_name] = {
'branches': {
'base': branch_base or 'master',
'merge': branch_merge or 'master'
}
}
config.save()
def save(self):
config.setValue("wine_paths", self._winePaths())
config.setValue("default_wine_path", str(self.defaultWinePath.itemData(self.defaultWinePath.currentIndex()).toString()))
config.setValue("allow_menu_entry_creation", self.allowMenuEntryCreation.isChecked())
config.setValue("auto_import_shortcuts", self.autoImportShortcuts.isChecked())
config.setValue("debug_line", str(self.debugLine.text()))
config.setValue("architecture", str(self.architecture.currentText()))
config.save()
def save():
previous_mods = config.mods
config.config_mods = ",".join(mods)
config.mods = config.config_mods
config.save()
if config.mods != previous_mods:
reload_all()
return END_LOOP
def unhide_plugin(self, id):
""" Unhide plugin with given id. This will unhide the plugin so queries
return it again, and write this change to the config
"""
self.__hidden_plugins.remove(id)
config.set('plugin.hiddenplugins', list(self.__hidden_plugins))
config.save()
self.__hidden_changed()
async def lexicon(self, ctx, word):
if ctx.author.name == ctx.channel.name or ctx.author.is_mod:
config.channels[ctx.channel.name]["lexicon"] = word.lower()
cf.save(config)
msg = f'Lexicon changed to {word.lower()}'
else:
msg = f'Command can only be used by {ctx.channel.name} or moderators'
await ctx.send(msg)
def finish_table_calib():
# We've already picked the bound points for each image
global depth
boundpts = np.load('%s/config/boundpts.npy' % newest_folder)
depth = np.load('%s/config/depth.npy' % newest_folder)
config.bg = find_plane(depth, boundpts)
config.save(newest_folder)
def finish_table_calib():
# We've already picked the bound points for each image
global depth
boundpts = np.load('%s/config/boundpts.npy' % newest_folder)
depth = np.load('%s/config/depth.npy' % newest_folder)
config.bg = find_plane(depth, boundpts)
config.save(newest_folder)
def add_operator(new_op):
conf = config.config()
config_operators = conf.get('operators', [])
if new_op in config_operators:
return False
config_operators.append(new_op)
conf['operators'] = config_operators
config.save(conf)
return True
def onSaveConfigurationCommand(self,evt):
if globalVars.appArgs.secure:
queueHandler.queueFunction(queueHandler.eventQueue,ui.message,_("Cannot save configuration - NVDA in secure mode"))
return
try:
config.save()
queueHandler.queueFunction(queueHandler.eventQueue,ui.message,_("Configuration saved"))
except:
messageBox(_("Could not save configuration - probably read only file system"),_("Error"),wx.OK | wx.ICON_ERROR)
def _run(epochs, events, analysis):
"""Runs temporal generalization for a given subject and analysis"""
print(subject, analysis['name'])
# subselect the trials (e.g. exclude absent trials) with a
# dataframe query defined in conditions.py
query, condition = analysis['query'], analysis['condition']
sel = range(len(events)) if query is None \
else events.query(query).index
sel = [ii for ii in sel if ~np.isnan(events[condition][sel][ii])]
# The to-be-predicted value, for each trial:
y = np.array(events[condition], dtype=np.float32)
print analysis['name'], np.unique(y[sel]), len(sel)
# Abort if there is no trial
if len(sel) == 0:
return
# Apply analysis
gat = GeneralizationAcrossTime(clf=analysis['clf'],
cv=analysis['cv'],
scorer=analysis['scorer'],
n_jobs=-1)
print(subject, analysis['name'], 'fit')
gat.fit(epochs[sel], y=y[sel])
print(subject, analysis['name'], 'score')
score = gat.score(epochs[sel], y=y[sel])
print(subject, analysis['name'], 'save')
# save space
if analysis['name'] not in ['probe_phase', 'target_circAngle']:
# we'll need the estimator trained on the probe_phase and to generalize
# to the target phase and prove that there is a significant signal.
gat.estimators_ = None
if analysis['name'] not in [
'target_present', 'target_circAngle', 'probe_circAngle'
]:
# We need these individual prediction to control for the correlation
# between target and probe angle.
gat.y_pred_ = None
# Save analysis
save([gat, analysis, sel, events],
'decod',
subject=subject,
analysis=analysis['name'],
overwrite=True,
upload=True)
save([score, epochs.times],
'score',
subject=subject,
analysis=analysis['name'],
overwrite=True,
upload=True)
return
def add_show(self):
dlg = AddShowDialog(self)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
show = dlg.show_name
if show in self.shows: return
self.shows.append(show)
self.updateListWidget()
config.save(self.shows)
def save():
global current_config, current_render_distance, current_username, current_features, current_hide_launcher
current_config['general']['render-distance'] = current_render_distance.get()
current_config['general']['username'] = current_username.get()
current_config['general']['custom-features'] = current_features.copy()
current_config['general']['hide-launcher'] = bool(current_hide_launcher.get())
current_config['server']['ip'] = current_ip.get()
current_config['server']['port'] = current_port.get()
config.save(current_config)
def put(self, key):
CONFIG = config.load()
if key in CONFIG:
print(request.form['data'])
CONFIG[key] = json.loads(request.form['data'])
config.save(CONFIG)
return {"result": "ok"}, 201
else:
return {"result": "key " + key + " not found"}, 404
def remove_operator(remove_op):
conf = config.config()
config_operators = conf.get('operators', [])
if remove_op not in config_operators:
return False
config_operators.remove(remove_op)
conf['operators'] = config_operators
config.save(conf)
return True
def on_continue_clicked(self, _widget):
self.dlg.hide()
config.PARSER.set('GUI', 'requests_checked_groups',
','.join([r[1] for r in self.groups_list if r[0]]))
config.PARSER.set('GUI', 'requests_checked_roles',
','.join([r[1] for r in self.roles_list if r[0]]))
config.save()
start_server(self.system, self.get_selected_groups(),
self.get_selected_roles())
def hide_plugin(self, id):
""" Hide plugin with given id. This will hide the plugin so queries do
not return it anymore, and write this change to the config.
Note that config will then emit a signal
"""
self.__hidden_plugins.add(id)
config.set('plugin.hiddenplugins', list(self.__hidden_plugins))
config.save()
self.__hidden_changed()
def on_close(self, event):
"""Try and stop the reactor."""
functions.output('Goodbye', process = False)
try:
application.log_object.flush()
config.save()
reactor.stop()
except Exception as e:
logger.exception(e)
event.Skip()
def action_ok(self, event):
language = self.language.get_selection()
encoding = self.encoding.get_selection()
para_start = self.para_start.get_selection()
if confirm_dialog_no_restart(self):
c.set_default('DEFAULT_TEXT_LANGUAGE', language)
c.set_default('DEFAULT_TEXT_ENCODING', encoding)
c.set_default('DEFAULT_PARAGRAPH_START', para_start)
c.save()
self.dispose()
def action_ok(self, event):
make_folder = self.make_folder.selected
if confirm_dialog(self):
c.set_default('MAKE_FOLDER', make_folder)
c.set_default('DEFAULT_OPEN_DIRECTORY', self.open_file_dir)
c.set_default('DEFAULT_SAVE_DIRECTORY', self.save_file_dir)
c.set_default('LOCALE', self.language.get_selection())
c.set_default('MIDLET_LOCALE', self.midlet_language.get_selection())
c.save()
self.dispose()
def _epoch_raw(subject, block, overwrite=False):
"""high pass filter raw data, make consistent channels and epoch."""
# Checks if preprocessing has already been done
epo_fname = paths('epo_block', subject=subject, block=block)
if op.exists(epo_fname) and not overwrite:
return
print(subject, block)
# Load raw data
raw = load('sss', subject=subject, block=block, preload=True)
# Explicit picking of channel to ensure same channels across subjects
picks = ['STI101', 'EEG060', 'EOG061', 'EOG062', 'ECG063', 'EEG064',
'MISC004']
# Potentially add forgotten channels
ch_type = dict(STI='stim', EEG='eeg', EOG='eog', ECG='ecg',
MIS='misc')
missing_chans = list()
for channel in picks:
if channel not in raw.ch_names:
missing_chans.append(channel)
if missing_chans:
info = create_info(missing_chans, raw.info['sfreq'],
[ch_type[ch[:3]] for ch in missing_chans])
raw.add_channels([RawArray(
np.zeros((len(missing_chans), raw.n_times)), info,
raw.first_samp)], force_update_info=True)
# Select same channels order across subjects
picks = [np.where(np.array(raw.ch_names) == ch)[0][0] for ch in picks]
picks = np.r_[np.arange(306), picks]
# high pass filtering
raw.filter(.1, None, l_trans_bandwidth=.05, filter_length='30s',
n_jobs=1)
# Ensure same sampling rate
if raw.info['sfreq'] != 1000.0:
raw.resample(1000.0)
# Select events
events = find_events(raw, stim_channel='STI101', shortest_event=1)
sel = np.where(events[:, 2] <= 255)[0]
events = events[sel, :]
# Compensate for delay (as measured manually with photodiod
events[1, :] += .050 * raw.info['sfreq']
# Epoch continuous data
epochs = Epochs(raw, events, reject=None, tmin=-.600, tmax=1.8,
picks=picks, baseline=None)
save(epochs, 'epo_block', subject=subject, block=block, overwrite=True,
upload=False)
def modify_login(self):
login = input_string([4235, 4236], "^[a-zA-Z0-9]$") # type your new
# login ; use alphanumeric characters
if login == None:
voice.alert([4238]) # current login kept
elif (len(login) < 1) or (len(login) > 20):
voice.alert([4237, 4238]) # incorrect login ; current login kept
else:
voice.alert([4239, login]) # new login:
config.login = login
config.save()
def modify_login():
login = input_string(mp.ENTER_NEW_LOGIN + mp.USE_LETTERS_AND_NUMBERS_ONLY,
"^[a-zA-Z0-9]$")
if login == None:
voice.alert(mp.CURRENT_LOGIN_KEPT)
elif (len(login) < 1) or (len(login) > 20):
voice.alert(mp.BAD_LOGIN + mp.CURRENT_LOGIN_KEPT)
else:
voice.alert(mp.NEW_LOGIN + [login])
config.login = login
config.save()
def reconfigure(self):
self.bookshelf.configure()
if self.bookshelf.platform.hasProperty('DISABLE_ROTATION') and self.bookshelf.platform.getProperty('DISABLE_ROTATION') == 'true':
c.set_default('SCREEN_ROTATION', 0)
c.save()
self.bookshelf.configure()
self.set_title()
for i in range(self.tabbed_pane.tabCount):
bookView = self.tabbed_pane.getComponentAt(i)
# re-render every loaded book
bookView.action_preview(None)
