import requests
from bs4 import BeautifulSoup
import operator
from configobj import ConfigObj
config = ConfigObj("config.ini")
my_mini_profile = config["my_mini_profile"]
HOMEPAGE_URL = config["HOMEPAGE_URL"]
LOGIN_URL = config["LOGIN_URL"]
username = config["username"]
password = config["password"]
client = requests.Session()
html = client.get(HOMEPAGE_URL).content
soup = BeautifulSoup(html, "html5lib")
csrf = soup.find(id="loginCsrfParam-login")['value']
login_information = {
'session_key': username,
'session_password': password,
'loginCsrfParam': csrf,
}
client.post(LOGIN_URL, data=login_information)
def getProfileIdentifiers(company, cutoff=20):
profile_identifiers = set()
def test_no_parent(tmpdir, specpath):
ini = tmpdir.join('config.ini')
ini.write('[[haha]]')
with pytest.raises(NestingError):
conf = ConfigObj(str(ini), configspec=specpath, file_error=True)
import os
import shutil
import sys
from configobj import ConfigObj
import json
from distutils.util import strtobool
#path_model = './'
#path_model = sys.argv[1]
#print (sys.argv)
#os.chdir(path_model)
startTime = datetime.now()
# get runtime params from config file
config = ConfigObj('runtime_params.ini')
parallel_mode = bool(strtobool(config['parallel_mode']))
model_mode = config['model_mode']
short_test = int(config['short_test'])
print_log = bool(strtobool(config['print_log']))
seed = int(config['seed'])
scenario_name = config[
'scenario_name'] #scenarios provide information on infrastructural plans
flow_input_type = config['flow_input_type']
flow_input_source = config['flow_input_source']
total_sensitivity_factors = int(config['total_sensitivity_factors'])
sensitivity_sample_file = config['sensitivity_sample_file']
output_list = config['output_list']
output_directory = config['output_directory']
clean_output = bool(strtobool(config['clean_output']))
save_full = bool(strtobool(config['save_full']))
def get_config(config_path=None):
"""reads the config file, validates it and return a config dict
:param config_path: path to a custom config file, if none is given the
default locations will be searched
:type config_path: str
:returns: configuration
:rtype: dict
"""
if config_path is None:
config_path = _find_configuration_file()
logger.debug('using the config file at {}'.format(config_path))
try:
user_config = ConfigObj(
config_path,
configspec=SPECPATH,
interpolation=False,
file_error=True,
)
except ConfigObjError as error:
logger.fatal('parsing the config file file with the following error: '
'{}'.format(error))
logger.fatal('if you recently updated khal, the config file format '
'might have changed, in that case please consult the '
'CHANGELOG or other documentation')
raise CannotParseConfigFileError()
fdict = {
'timezone': is_timezone,
'expand_path': expand_path,
'expand_db_path': expand_db_path,
'weeknumbers': weeknumber_option,
'color': is_color,
}
validator = Validator(fdict)
results = user_config.validate(validator, preserve_errors=True)
abort = False
for section, subsection, error in flatten_errors(user_config, results):
abort = True
if isinstance(error, Exception):
logger.fatal('config error:\n'
'in [{}] {}: {}'.format(section[0], subsection,
error))
else:
for key in error:
if isinstance(error[key], Exception):
logger.fatal('config error:\nin {} {}: {}'.format(
sectionize(section + [subsection]), key,
str(error[key])))
if abort or not results:
raise InvalidSettingsError()
config_checks(user_config)
extras = get_extra_values(user_config)
for section, value in extras:
if section == ():
logger.warn('unknown section "{}" in config file'.format(value))
else:
section = sectionize(section)
logger.warn('unknown key or subsection "{}" in '
'section "{}"'.format(value, section))
return user_config
def conf(inipath, specpath):
return ConfigObj(inipath, configspec=specpath)
def reloadConfig(self):
try:
self.config = ConfigObj("./config/mitmf.conf")
except Exception as e:
mitmf_logger.error("Error reloading config file: {}".format(e))
pass
from logHandler import logger
logging = logger.getChild('core.config')
import os
import confspecs
import paths
import application
from UserDict import UserDict
from configobj import ConfigObj, ParseError
from validate import Validator, VdtValueError
configFile = paths.data_path(application.name + ".ini")
confspec = ConfigObj(confspecs.defaults, list_values=False, encoding="UTF-8")
confspec.newlines = "\r\n"
conf = None
class ConfigurationResetException(Exception):
pass
class Configuration(UserDict):
def __init__(self, file=None, spec=None, *args, **kwargs):
self.file = file
self.spec = spec
self.validator = Validator()
self.setup_config(file=file, spec=spec)
self.validated = self.config.validate(self.validator, copy=True)
if self.validated:
self.write()
UserDict.__init__(self, self.config)
speechManager = boolean(default=false)
synthDriver = boolean(default=false)
nvwave = boolean(default=false)
annotations = boolean(default=false)
[uwpOcr]
language = string(default="")
[upgrade]
newLaptopKeyboardLayout = boolean(default=false)
[editableText]
caretMoveTimeoutMs = integer(min=0, max=2000, default=100)
[development]
enableScratchpadDir = boolean(default=false)
[featureFlag]
# 0:default, 1:yes, 2:no
cancelExpiredFocusSpeech = integer(0, 2, default=0)
# 0:Only in test versions, 1:yes
playErrorSound = integer(0, 1, default=0)
"""
#: The configuration specification
#: @type: ConfigObj
confspec = ConfigObj(StringIO(configSpecString),
list_values=False,
encoding="UTF-8")
confspec.newlines = "\r\n"
str(speck.ycentroid)))
ax2.axvline(speck.null_phase)
print speck.null_phase
plt.draw()
plt.pause(0.1)
plt.cla()
plt.close()
if __name__ == "__main__":
#configfilename = 'speckle_null_config.ini'
#config = ConfigObj(configfilename)
configfilename = 'speckle_null_config.ini'
hardwareconfigfile = 'speckle_instruments.ini'
configspecfile = 'speckle_null_config.spec'
config = ConfigObj(configfilename, configspec=configspecfile)
val = Validator()
check = config.validate(val)
pharo = hardware.PHARO_COM('PHARO',
configfile = hardwareconfigfile)
p3k = hardware.P3K_COM('P3K_COM', configfile = hardwareconfigfile)
im_params= config['IM_PARAMS']
null_params = config['NULLING']
abc = config['INTENSITY_CAL']['abc']
bgds = flh.setup_bgd_dict(config)
controlregion = pf.open(config['CONTROLREGION']['filename'])[0].data
#Notes==>scale exptime in snr
exp = config['INTENSITY_CAL']['exptime']
#Setup
initial_flatmap = p3k.grab_current_flatmap()
import logging
from bot.bot import OSMbot
from flask import Flask, request, current_app
from bot import Osmbot
from configobj import ConfigObj
import os
from raven.contrib.flask import Sentry
application = Flask(__name__)
application.debug = True
Osmbot(application, '')
config = ConfigObj('bot.conf')
token = config['token']
bot = OSMbot(token)
if 'sentry_dsn' in config:
application.config['sentry_dsn'] = config['sentry_dsn']
sentry = Sentry(application, dsn=config['sentry_dsn'])
sentry.captureMessage('OSMBot started', level=logging.INFO)
application.sentry = sentry
f = open('nginx.crt', 'r')
cert_data = f.read()
f.close()
webhook = os.path.join(config['webhook'], config['token'])
application.logger.debug('webhook:%s', config['webhook'])
response = bot.setWebhook(webhook, cert_data)
application.logger.debug('response:%s', response)
import subprocess
import glob
import shutil
import xml.etree.ElementTree as ET
from configobj import ConfigObj
# load config file
CONFIG_FILE = os.path.realpath( os.path.join( os.path.dirname( os.path.dirname( __file__) ), "TrovaWrapper_config.ini" ) )
if not os.path.exists( CONFIG_FILE ) :
msg = str('The TrovaWrapper config.ini file "' + CONFIG_FILE + '" is missing. Analysis cannot proceed...')
#LogAndEmail( msg, 4)
logging.critical( msg )
sys.exit()
#print "CONFIG_FILE: " + CONFIG_FILE + "\n"
#Config = ConfigParser.ConfigParser()
Config = ConfigObj(CONFIG_FILE, raise_errors=True)
# load global section
#for key, value in Config.iteritems() :
# print "KEY: " + str(key) + " VALUE: " + str(value) + "\n"
# if 'global' in str(key):
globalOptions = Config['global']
UNIFLOW_URL = globalOptions['UNIFLOW_URL']
TROVAEMON_ID = globalOptions['TROVAEMON_ID']
TROVAEMON_PWD = globalOptions['TROVAEMON_PWD']
MAX_RETRY = globalOptions['MAX_RETRY']
''' Returns a list of paths to MiSeq repositories
'''
def Repositories() :
# get repo info
def save(self, dirname=""):
""" Saves the project as a directory named **dirname**.
If **dirname** is not provided, the **project_save_path** attribute
should already be set.
If **project_save_path** is not set, then it will be set to **dirname**.
"""
if dirname == "":
dirname = self.project_save_path
else:
self.project_save_path = dirname
# Do some error checking
if dirname == "":
raise IOError("Cannot save project to empty path.")
elif os.path.isfile(dirname):
raise IOError('Cannot save project to directory "%s"; '
'file exists.' % dirname)
logger.info('Starting save of project to "%s"' % dirname)
if not os.path.isdir(dirname):
logger.info(' Creating directory "%s"' % dirname)
os.mkdir(dirname)
# TODO: We should formalize this dependency at some point and move
# this import to the top level
from configobj import ConfigObj
config = ConfigObj()
config["Project"] = {}
exp = {}
for i, experiment in enumerate(self.experiments):
if experiment.name is not None and experiment.name != "":
safename = self._encode_name(experiment.name)
else:
safename = "Experiment_%d" % i
exp[safename] = experiment.save(basename=dirname, dirname=safename)
logger.info(' Saved experiment "%s" to subdir "%s"' % \
(experiment.name, safename))
config["Experiments"] = exp
if self.active_experiment is not None:
config["Project"]["active_experiment"] = self.active_experiment.name
contexts = {}
for i, ctx in enumerate(self.contexts):
if ctx.name is not None and ctx.name != "":
safename = self._encode_name(ctx.name)
else:
safename = "Context_%d" % i
filename = safename + ".pickle"
contexts[safename] = dict(name=ctx.name, file=filename)
ctx.save(join(dirname, filename))
logger.info(' Saved context "%s" to file "%s"' % \
(ctx.name, filename))
config["Contexts"] = contexts
config.filename = join(dirname, self.PROJECT_FILE_NAME)
logger.info(' Writing project to "%s"' % config.filename)
config.write()
logger.info('Finished saving project to "%s"' % dirname)
return
from flaskskeleton.model import *
# add your model's MetaData object here
# for 'autogenerate' support
# from myapp import mymodel
# target_metadata = mymodel.Base.metadata
from flaskskeleton.model import db
target_metadata = db.metadata
# other values from the config, defined by the needs of env.py,
# can be acquired:
# my_important_option = config.get_main_option("my_important_option")
# ... etc.
from configobj import ConfigObj
configobj = ConfigObj('config/dev.config', configspec='config/dev.configspec')
alembic_config = config.get_section(config.config_ini_section)
config.set_main_option('sqlalchemy.url', configobj['webapp']['database_uri'])
alembic_config['sqlalchemy.url'] = configobj['webapp']['database_uri']
def run_migrations_offline():
"""Run migrations in 'offline' mode.
This configures the context with just a URL
and not an Engine, though an Engine is acceptable
here as well. By skipping the Engine creation
we don't even need a DBAPI to be available.
Calls to context.execute() here emit the given string to the
def __init__(self, *args, **kwargs):
super(TestTimeseries, self).__init__(*args, **kwargs)
config_path = os.path.join(os.getcwd(), 'tests', 'test_configs',
'test_run_no_sta.cfg')
self.config = ConfigObj(config_path)
self.project_path = os.path.join(os.getcwd(), '..', 'testproject')
def parse_ini_races():
races = OrderedDict()
if (CFG_PATH / 'races.ini').isfile():
imported = ConfigObj(CFG_PATH / 'races.ini')
no_category = []
for name, data in imported.items():
for alias, value in data.items():
if alias.startswith('racealias_'):
_aliases[alias] = value
fixed_name = FIX_NAME.sub('', name.lower().replace(' ', '_'))
settings = races[fixed_name] = ImportedRace(fixed_name, ModuleType.ESS_INI)
settings.cmds['preloadcmd'] = data['preloadcmd']
settings.cmds['roundstartcmd'] = data['roundstartcmd']
settings.cmds['roundendcmd'] = data['roundendcmd']
settings.cmds['spawncmd'] = data['spawncmd']
settings.cmds['deathcmd'] = data['deathcmd']
settings.cmds['changeintocmd'] = None
settings.cmds['changefromcmd'] = data['onchange']
settings.config['required'] = int(data['required'])
settings.config['maximum'] = int(data['maximum'])
settings.config['restrictmap'] = data['restrictmap'].split('|') if data['restrictmap'] else []
settings.config['restrictitem'] = data['restrictitem'].split('|') if data['restrictitem'] else []
settings.config['restrictweapon'] = []
settings.config['restrictteam'] = int(data['restrictteam'])
settings.config['teamlimit'] = int(data.get('teamlimit', 0))
settings.config['author'] = data['author']
settings.config['allowonly'] = data['allowonly'].split('|') if data['allowonly'] else []
skillnames = data['skillnames'].split('|')
skilldescr = data['skilldescr'].split('|')
skillcfg = data['skillcfg'].split('|')
skillneeded = data['skillneeded'].split('|')
numberoflevels = map(int, data['numberoflevels'].split('|')) if '|' in data['numberoflevels'] else [int(data['numberoflevels'])] * len(skillnames)
skills = settings.config['skills'] = {}
for i, skill_name in enumerate(skillnames):
fixed_skill_name = FIX_NAME.sub('', skill_name.lower().replace(' ', '_'))
settings.strings[fixed_skill_name] = _LanguageString(skill_name)
settings.strings[f'{fixed_skill_name} description'] = _LanguageString(skilldescr[i].replace(r'\n', ''))
skill = skills[fixed_skill_name] = {}
skill['event'] = [skillcfg[i]]
skill['required'] = [int(skillneeded[i])] * numberoflevels[i]
if 'cooldown' in data[f'skill{i + 1}']:
skill['cooldown'] = list(map(lambda x: float(x) if '.' in x else int(x), data[f'skill{i + 1}']['cooldown'].split('|')))
if not len(skill['cooldown']) == numberoflevels[i]:
skill['cooldown'] = [skill['cooldown'][0]] * numberoflevels[i]
skill['variables'] = {}
skill['cmds'] = {}
skill['cmds']['setting'] = data[f'skill{i + 1}']['setting'].split('|')
if 'block' in data[f'skill{i + 1}']:
skill['cmds']['cmd'] = 'es_xdoblock ' + data[f'skill{i + 1}']['block']
else:
skill['cmds']['cmd'] = data[f'skill{i + 1}']['cmd']
skill['cmds']['sfx'] = data[f'skill{i + 1}']['sfx']
count = len(data[f'skill{i + 1}']['setting'].split('|'))
if count:
skill['maximum'] = count
else:
skill['maximum'] = numberoflevels[i]
for alias, value in data[f'skill{i + 1}'].items():
if alias.startswith('racealias_'):
_aliases[alias] = value
settings.strings['name'] = _LanguageString(name)
settings.strings['description'] = _LanguageString(data['desc'].replace(r'\n', ''))
categories = (data['category'].split('|') if data['category'] and not data['category'] == '0' else []) if 'category' in data else []
if categories:
for category in categories:
if category == '0':
no_category.append(settings)
continue
fixed_category = FIX_NAME.sub('', category.lower().replace(' ', '_'))
if fixed_category not in categories_strings:
categories_strings[fixed_category] = _LanguageString(category)
settings.add_to_category(fixed_category)
else:
no_category.append(settings)
for settings in no_category:
settings.add_to_category(None)
return races
sickbeard.FLATTEN_FOLDERS_DEFAULT = 0
sickbeard.NAMING_PATTERN = ''
sickbeard.NAMING_ABD_PATTERN = ''
sickbeard.NAMING_SPORTS_PATTERN = ''
sickbeard.NAMING_MULTI_EP = 1
sickbeard.PROVIDER_ORDER = ["sick_beard_index"]
sickbeard.newznabProviderList = providers.getNewznabProviderList("'Sick Beard Index|http://lolo.sickbeard.com/|0|5030,5040|0|eponly|0|0|0!!!NZBs.org|https://nzbs.org/||5030,5040,5060,5070,5090|0|eponly|0|0|0!!!Usenet-Crawler|https://www.usenet-crawler.com/||5030,5040,5060|0|eponly|0|0|0'")
sickbeard.providerList = providers.makeProviderList()
sickbeard.PROG_DIR = os.path.abspath(os.path.join(TESTDIR, '..'))
sickbeard.DATA_DIR = TESTDIR
sickbeard.CONFIG_FILE = os.path.join(sickbeard.DATA_DIR, "config.ini")
sickbeard.CFG = ConfigObj(sickbeard.CONFIG_FILE)
sickbeard.BRANCG = sickbeard.config.check_setting_str(sickbeard.CFG, 'General', 'branch', '')
sickbeard.CUR_COMMIT_HASH = sickbeard.config.check_setting_str(sickbeard.CFG, 'General', 'cur_commit_hash', '')
sickbeard.GIT_USERNAME = sickbeard.config.check_setting_str(sickbeard.CFG, 'General', 'git_username', '')
sickbeard.GIT_PASSWORD = sickbeard.config.check_setting_str(sickbeard.CFG, 'General', 'git_password', '', censor_log=True)
sickbeard.LOG_DIR = os.path.join(TESTDIR, 'Logs')
sickbeard.logger.logFile = os.path.join(sickbeard.LOG_DIR, 'test_sickbeard.log')
createTestLogFolder()
sickbeard.CACHE_DIR = os.path.join(TESTDIR, 'cache')
createTestCacheFolder()
sickbeard.logger.initLogging(False, True)
sgroup = parser.add_argument_group("%s" % p.name, p.desc)
sgroup.add_argument("--%s" % p.optname,
action="store_true",
help="Load plugin %s" % p.name)
if p.has_opts:
p.add_options(sgroup)
except NotImplementedError:
sys.exit("[-] %s plugin claimed option support, but didn't have it." %
p.name)
args = parser.parse_args()
try:
configfile = ConfigObj(args.configfile)
except Exception, e:
sys.exit("[-] Error parsing config file: " + str(e))
config_args = configfile['MITMf']['args']
if config_args:
print "[*] Loading arguments from config file"
for arg in config_args.split(' '):
sys.argv.append(arg)
args = parser.parse_args()
####################################################################################################
# Here we check for some variables that are very commonly used, and pass them down to the plugins
try:
args.ip_address = get_if_addr(args.interface)
# Minimal tests
RUN_SLOW_TESTS = False
# quick n dirty method to see if internet is on
try:
_ = urlopen('http://www.google.com', timeout=1)
HAS_INTERNET = True
except URLError:
HAS_INTERNET = False
# check if there is a credentials file (should be added to .gitignore)
cred_path = os.path.abspath(os.path.join(__file__, "../../..", '.credentials'))
if os.path.exists(cred_path):
HAS_CREDENTIALS = True
try:
cred = ConfigObj(cred_path)
except ConfigObjError:
raise
else:
HAS_CREDENTIALS = False
cred = None
def requires_internet(test):
# Test decorator
msg = 'requires internet'
return test if HAS_INTERNET else unittest.skip(msg)(test)
def requires_py3(test):
# Test decorator
def write_conf(conf_dict, conf_file):
config = ConfigObj()
config.filename = conf_file
for k, v in conf_dict.items():
config[k] = v
config.write()
#!/usr/bin/env python3
'''Tämä on asiakas-esimerkki joka ottaa yhteyttä flaskin socket-palvelimelle'''
import subprocess, json, time, datetime, threading, websocket
from configobj import ConfigObj
config = ConfigObj('/boot/asetukset.txt')
def lokita(data, flush=True):
with open("/home/pi/batloki", "a") as kirj:
aika = str(datetime.datetime.now())
kirj.write(aika + " " + data + "\n")
print(aika + " " + data, flush=flush)
def kyseleNaapurit(
): #kyselee batmanin näkemät naapurilaitteet # [('00:c0:ca:98:8f:9f', ' 0.500', ' 7.8'), ('00:c0:ca:98:8e:ed', ' 0.190', '35.6')]
tamaLaiteMAC = subprocess.getoutput(
'sudo batctl n|grep -o "MAC:.*"|cut -d "/" -f2|cut -d " " -f1')
tamaLaiteIP = subprocess.getoutput(
'ifconfig |grep bat0 -A1|tail -n 1|grep -o "inet.*" | cut -d " " -f 2'
) #vittu mitä paskaa, fiksaa tää :D
naapuritraaka = subprocess.getoutput('sudo batctl n -H').split("\n")
jrivi = '{"laite": "' + config.get(
"mesh_name"
) + '", "mac": "' + tamaLaiteMAC + '", "ip": "' + tamaLaiteIP + '", "data": ['
for n in naapuritraaka:
nmac = n[0:17]
nviive = n[19:26]
nteho = n[36:40]
if len(nmac) > 0:
jrivi += '{"mac": "' + nmac + '", "viive": "' + nviive + '", "teho": "' + nteho + '"},'
def test_configfile(self):
from configobj import ConfigObj
config = ConfigObj('config/mitmf.conf')
def _get_default_config():
'''Create the default configuration object.'''
_default_config = ConfigObj()
_default_config.merge({
'scale_factor': 1.,
'iter_list': ['g_AMPA_total', 'g_GABA_total'],
'output_dir': 'panels/',
'grids_data_root': 'simulation_data/main_network/grids',
'bump_data_root': 'simulation_data/main_network/gamma_bump',
'vel_data_root': 'simulation_data/main_network/velocity',
'const_pos_data_root': 'simulation_data/main_network/const_position',
'singleDataRoot': 'simulation_data/main_network/single_neuron',
'connection_data_root': 'simulation_data/main_network/connections',
'even_shape': (31, 31),
'noise_sigmas': [0, 150, 300],
# Sections
'mpl': {
'font.size':
11,
'pdf.fonttype':
42,
'mathtext.default':
'regular',
'font.sans-serif':
['Helvetica', 'Avant Garde', 'Computer Modern Sans serif'],
'xtick.major.size':
tick_len,
'xtick.major.width':
tick_width,
'xtick.minor.size':
tick_len / 2.,
'xtick.minor.width':
tick_width,
'xtick.direction':
'out',
'ytick.major.size':
tick_len,
'ytick.major.width':
tick_width,
'ytick.minor.size':
tick_len / 2.,
'ytick.minor.width':
tick_width,
'ytick.direction':
'out',
},
'sweeps': {
'fig_size': (3.7, 2.6), # inches
'bbox': (0.08, 0.2, .72, .65), # l, b, w, h
'transparent': True,
'grid_contours': [.5],
'contours_kwargs': {
'hold': True,
'colors': 'k',
'linewidths': [1.5]
},
},
'grids': {
'example_rc': ((5, 15), (15, 5)),
'example_idx': [(5, 15), (5, 15), (5, 15)], # (row, col)
'ntrials': 3,
},
'gamma': {
'example_rc': ((5, 15), (15, 5)),
},
'bumps': {
'n_trials': 5,
},
'p_bumps': {
'frac_total_text': 'P(bumps)'
},
'bump_sigma': {
'sigma_bump_text': '$\sigma_{bump}^{-1}\ (neurons^{-1})$',
},
'seizures': {
'thetaT': 125., # ms
'sig_dt': .5 # ms
},
'vel_rasters': {
'tLimits': [2e3, 3e3], # ms
'trialNum': 0,
'ylabelPos': -0.22,
},
})
##############################################################################
GridSweepsPlotter_config = {
'cbar': [0, 0, 1],
'cbar_kw': {
'label': 'Gridness score',
'location': 'right',
'shrink': 0.8,
'pad': -0.05,
'ticks': ti.MultipleLocator(0.5),
'rasterized': True
},
'sigma_title':
True,
'vmin':
-0.5,
'vmax':
1.111,
'xlabel': [None, None, None],
'xticks': [True, True, True],
'ylabel': [None, '', ''],
'yticks': [True, False, False],
'ann': [
dict(txt='b',
rc=_default_config['grids']['example_rc'][0],
xytext_offset=(1.5, 1),
color='black'),
dict(txt='a',
rc=_default_config['grids']['example_rc'][1],
xytext_offset=(0.5, 1.5),
color='black')
],
'plot_contours': [0, 0, 0],
}
_default_config['GridSweepsPlotter'] = GridSweepsPlotter_config
##############################################################################
GridExamplesPlotter_config = {
'fig_size': (1, 1.2),
'ax_box': (0.01, 0.01, 0.99, 0.85), # l, b, r, t
'transparent': True,
'population_type': 'E',
}
_default_config['GridExamplesPlotter'] = GridExamplesPlotter_config
##############################################################################
GridExampleRectPlotter_config = {
'cbar_kw': {
'label': 'Gridness score',
'location': 'right',
'shrink': 0.8,
'pad': -0.05,
'ticks': ti.MultipleLocator(0.5),
'rasterized': True
},
'vmin': -0.505,
'vmax': 1.111,
'fig_saver': PdfOutputSaver(None, 'pdf')
}
_default_config['GridExampleRectPlotter'] = GridExampleRectPlotter_config
##########################################################################
SpatialInfoPlotter_config = {
'cbar': [0, 0, 0],
'cbar_kw': {
'label': 'Information (bits/spike)',
'location': 'right',
'shrink': 0.8,
'pad': -0.15,
'ticks': ti.MultipleLocator(0.5),
'rasterized': True
},
'sigma_title': True,
'vmin': 0.14,
'vmax': 2.66,
'xlabel': ['', '', ''],
'xticks': [False, False, False],
'ylabel': [None, '', ''],
'yticks': [True, False, False],
'plot_contours': [1, 1, 1],
}
_default_config['SpatialInfoPlotter'] = SpatialInfoPlotter_config
##########################################################################
SpatialSparsityPlotter_config = {
'cbar': [0, 0, 0],
'cbar_kw': {
'label': 'Sparsity',
'location': 'right',
'shrink': 0.8,
'pad': -0.15,
'ticks': ti.MultipleLocator(0.2),
'rasterized': True
},
'sigma_title': True,
'vmin': 0.12,
'vmax': 0.89,
'xlabel': ['', '', ''],
'xticks': [False, False, False],
'ylabel': [None, '', ''],
'yticks': [True, False, False],
'plot_contours': [1, 1, 1],
}
_default_config['SpatialSparsityPlotter'] = SpatialSparsityPlotter_config
##############################################################################
GridnessCorrelationPlotter_config = {
'fig_size': (3.5, 1.5),
'bbox_rect': (0.2, 0.35, 0.95, .95),
}
_default_config[
'GridnessCorrelationPlotter'] = GridnessCorrelationPlotter_config
##############################################################################
GridsDiffSweep_config = {
'cbar_kw':
dict(label='$\Delta_{150 - 0}$(Gridness score)',
location='right',
shrink=0.8,
pad=-0.05,
ticks=ti.MultipleLocator(0.5),
rasterized=True)
}
_default_config['GridsDiffSweep'] = GridsDiffSweep_config
##############################################################################
GridDetailedNoisePlotter_config = {
'legend': ['a', 'b'],
'legend_kwargs':
dict(
loc=(0.8, 1),
fontsize='small',
frameon=False,
numpoints=1,
handletextpad=0.05,
)
}
_default_config[
'GridDetailedNoisePlotter'] = GridDetailedNoisePlotter_config
##############################################################################
GridDetailedNoisePlotter_config = {
'legend': ['a', 'b'],
'legend_kwargs':
dict(
loc=(0.8, 1),
fontsize='small',
frameon=False,
numpoints=1,
handletextpad=0.05,
)
}
_default_config[
'GridDetailedNoisePlotter'] = GridDetailedNoisePlotter_config
##############################################################################
GammaDetailedNoisePlotter_config = {
'legend': ['a', 'b'],
'legend_kwargs':
dict(
loc=(0.85, 0.7),
fontsize='small',
frameon=False,
numpoints=1,
handletextpad=0.05,
)
}
_default_config[
'GammaDetailedNoisePlotter'] = GammaDetailedNoisePlotter_config
##############################################################################
VmExamplesPlotter_config = {
'fig_size': (2.5, 1.25),
'ax_rect': (0.01, 0.01, 0.999, 0.6), # l, b, r, t
}
_default_config['VmExamplesPlotter'] = VmExamplesPlotter_config
##############################################################################
ConnectionFunctionPlotter_config = {
'fig_size': (3, 1.5),
'bbox_rect': (.2, .25, .95, .75),
'uniform_random':
False,
'leg1_kwargs':
dict(loc=(.6, .9), frameon=False, fontsize='x-small', ncol=1),
'leg2_kwargs':
dict(loc=(0.45, 1.03), frameon=False, fontsize='x-small'),
}
_default_config[
'ConnectionFunctionPlotter'] = ConnectionFunctionPlotter_config
##############################################################################
GammaSweepsPlotter_config = {
'scale_factor':
.9,
'cbar': [1, 0, 0],
'cbar_kw':
{ # This has to match cbar_kw-s below
'location': 'left',
},
'AC_cbar_kw':
dict(
location='left',
ticks=ti.MultipleLocator(0.3),
fraction=0.25,
shrink=0.8,
pad=.2,
labelpad=8,
label='$1^{st}$ autocorrelation\npeak',
rasterized=True,
),
'AC_xticks': [False] * 3,
'AC_yticks': [1, 0, 0],
'AC_sigma_title':
True,
'AC_vmin':
-0.09,
'AC_vmax':
0.675,
'F_cbar_kw':
dict(location='left',
ticks=ti.MultipleLocator(30),
fraction=0.25,
shrink=0.8,
pad=.2,
labelpad=8,
label='Oscillation\nfrequency (Hz)',
extend='max',
extendfrac=0.1,
rasterized=True),
'F_xticks': [True] * 3,
'F_yticks': [1, 0, 0],
'F_sigma_title':
False,
'F_vmin':
30,
'F_vmax':
120,
'ann': [
dict(
txt='b',
rc=None,
xytext_offset=(1.5, 0),
color='white',
),
dict(
txt='a',
rc=None,
xytext_offset=(-.5, 2.),
color='white',
),
],
'plot_grid_contours': [0, 1, 0],
}
_default_config['GammaSweepsPlotter'] = GammaSweepsPlotter_config
tmp = GammaSweepsPlotter_config
_default_config['GammaSweepsPlotter']['ann'][0]['rc'] = \
_default_config['gamma']['example_rc'][0]
_default_config['GammaSweepsPlotter']['ann'][1]['rc'] = \
_default_config['gamma']['example_rc'][1]
_default_config['GammaSweepsPlotter'].update({
'annF': deepcopy(tmp['ann']),
})
##############################################################################
GammaExamplePlotter_config = {
# index0: noise_sigma
# index1: example index
'xscales': [
[0, 0, 0],
[0, 0, 1],
],
'sigma_titles': [
[0, 0, 0],
[1, 1, 1],
],
'xscale_kw':
dict(scaleLen=50, x=0.75, y=-0.07, size='x-small'),
'yscale_kw': [[
dict(scaleLen=5, unitsText='nA', x=.5, y=.1, size='x-small'),
dict(scaleLen=0.5, unitsText='nA', x=.5, y=.05, size='x-small'),
dict(scaleLen=0.5, unitsText='nA', x=.5, y=.05, size='x-small')
],
[
dict(scaleLen=5,
unitsText='nA',
x=.5,
y=.1,
size='x-small'),
dict(scaleLen=0.5,
unitsText='nA',
x=.5,
y=.05,
size='x-small'),
dict(scaleLen=0.5,
unitsText='nA',
x=.55,
y=0,
size='x-small')
]],
}
_default_config['GammaExamplePlotter'] = GammaExamplePlotter_config
##############################################################################
GammaScatterAllPlotter_config = {
'fig_size': (4.2, 2),
'dot_size':
6,
'legend_kwargs':
dict(loc=(0.9, 0.4),
fontsize='small',
frameon=False,
numpoints=1,
title='$\sigma$ (pA)'),
'bbox_rect': (.1, .35, .95, .85),
'ylabel':
'',
}
_default_config['GammaScatterAllPlotter'] = GammaScatterAllPlotter_config
##############################################################################
GammaFreqGridsScatterAllPlotter_config = {
'fig_size': (4.2, 2),
'dot_size':
6,
'legend_kwargs':
dict(loc=(0.8, 0.4),
fontsize='small',
frameon=False,
numpoints=1,
title='$\sigma$ (pA)'),
'bbox_rect': (.1, .35, .95, .85),
'ylabel':
'',
'yticks':
True,
}
_default_config[
'GammaFreqGridsScatterAllPlotter'] = GammaFreqGridsScatterAllPlotter_config
##############################################################################
GammaScatterPBumpsAllPlotter_config = {
'fig_size': (4.5, 2.6),
'bbox_rect': (0.3, 0.22, 0.82, 0.95),
'xlabel':
'',
'legend_kwargs':
dict(loc=(1.05, 0.5),
fontsize='small',
frameon=False,
title='$\sigma$ (pA)'),
}
_default_config[
'GammaScatterPBumpsAllPlotter'] = GammaScatterPBumpsAllPlotter_config
##############################################################################
GammaPBumpsProbabilityPlotter_config = {
'fig_size': (2.7, 2.7), # inches
'bbox_rect': (0.25, 0.2, 0.95, 0.9),
}
_default_config[
'GammaPBumpsProbabilityPlotter'] = GammaPBumpsProbabilityPlotter_config
##############################################################################
GammaFreqPBumpsProbabilityPlotter_config = {
'fig_size': (2.7, 2.7), # inches
'bbox_rect': (0.25, 0.2, 0.95, 0.9),
}
_default_config[
'GammaFreqPBumpsProbabilityPlotter'] = GammaFreqPBumpsProbabilityPlotter_config
##############################################################################
GammaGridsProbabilityPlotter_config = {
'fig_size': (2.7, 2.7), # inches
'bbox_rect': (0.25, 0.2, 0.95, 0.9),
'title_size': 'medium',
}
_default_config[
'GammaGridsProbabilityPlotter'] = GammaGridsProbabilityPlotter_config
##############################################################################
GammaFreqGridsProbabilityPlotter_config = {
'fig_size': (2.7, 2.7), # inches
'bbox_rect': (0.25, 0.2, 0.95, 0.9),
'title_size': 'x-small',
}
_default_config[
'GammaFreqGridsProbabilityPlotter'] = GammaFreqGridsProbabilityPlotter_config
##############################################################################
fracTotalText = _default_config['p_bumps']['frac_total_text']
FracTotalSweepAnnPlotter_config = {
'scale_factor':
.8,
'cbar': (1, 0, 0),
'cbar_kw':
dict(label=fracTotalText,
location='left',
shrink=0.8,
pad=0.25,
ticks=ti.MultipleLocator(0.5),
rasterized=True)
}
_default_config[
'FracTotalSweepAnnPlotter'] = FracTotalSweepAnnPlotter_config
##############################################################################
MainBumpFormationPlotter_config = {
'scale_factor':
1.,
'cbar': [0, 0, 1],
'cbar_kw':
dict(label="P(bumps)",
location='right',
shrink=0.8,
pad=-.05,
ticks=ti.MultipleLocator(0.5),
rasterized=True),
'xticks': [True] * 3,
'plot_grid_contours': [1, 1, 1],
}
_default_config[
'MainBumpFormationPlotter'] = MainBumpFormationPlotter_config
##############################################################################
_default_config['MainIsBumpPlotter'] = FracTotalSweepAnnPlotter_config
##############################################################################
_default_config['IsBumpPlotter'] = FracTotalSweepAnnPlotter_config
##############################################################################
IsBumpExamplePlotter_config = {
'bumpQualityX': -.9,
'rateColors': ['k', 'k', 'k', 'k', 'k', 'k', 'k', 'k', 'k', 'k'],
#'rateColors': ['k', 'yellow', 'yellow', 'yellow', 'yellow', 'yellow',
# 'yellow', 'yellow', 'yellow', 'yellow'],
'cbar_fig_size': (0.6, 0.6),
}
_default_config['IsBumpExamplePlotter'] = IsBumpExamplePlotter_config
##############################################################################
MainScatterGridsBumpsPlotter_config = {
'fig_size': (4.5, 2.6),
'bbox_rect': (0.3, 0.22, 0.82, 0.95),
'xlabel':
'',
'legend':
False,
'legend_kwargs':
dict(loc=(1.05, 0.5),
fontsize='small',
frameon=False,
handletextpad=0,
title='$\sigma$ (pA)'),
}
_default_config[
'MainScatterGridsBumpsPlotter'] = MainScatterGridsBumpsPlotter_config
##############################################################################
BumpDriftAtTimePlotter_config = {
'scale_factor':
.8,
'cbar_kw':
dict(label='Average bump drift\n(neurons)',
location='right',
shrink=0.8,
pad=-0.05,
ticks=ti.MultipleLocator(10),
rasterized=True),
'plot_grid_contours': [1, 1, 1],
}
_default_config['BumpDriftAtTimePlotter'] = BumpDriftAtTimePlotter_config
##############################################################################
BumpDiffAtInitPlotter_config = {
'cbar_kw':
dict(label='Distance from init\nposition (neurons)',
location='right',
shrink=0.8,
pad=-0.05,
ticks=ti.MultipleLocator(10),
rasterized=True)
}
_default_config['BumpDiffAtInitPlotter'] = BumpDiffAtInitPlotter_config
##############################################################################
BumpDiffResetPlotter_config = {
'scale_factor':
.8,
'cbar_kw':
dict(label='Distance from reset\nposition (neurons)',
location='right',
shrink=0.8,
pad=-0.05,
ticks=ti.MultipleLocator(5),
rasterized=True),
'plot_grid_contours': [1, 1, 1],
}
_default_config['BumpDiffResetPlotter'] = BumpDiffResetPlotter_config
##############################################################################
MaxPopulationFRSweepsPlotter_config = {
'cbar': [1, 0, 0],
'cbar_kw':
dict(label="$E-rate_{max}$ (Hz)",
location='left',
shrink=0.8,
pad=0.25,
ticks=ti.MultipleLocator(100),
rasterized=True),
'plot_grid_contours': [1, 1, 1],
'grid_contours': [.5],
}
_default_config[
'MaxPopulationFRSweepsPlotter'] = MaxPopulationFRSweepsPlotter_config
##############################################################################
BumpSigmaSweepPlotter_config = {
'cbar': [0, 0, 1],
'cbar_kw':
dict(label=_default_config['bump_sigma']['sigma_bump_text'],
location='right',
shrink=0.8,
pad=-0.05,
ticks=ti.MultipleLocator(0.2),
rasterized=True)
}
_default_config['BumpSigmaSweepPlotter'] = BumpSigmaSweepPlotter_config
##############################################################################
BumpExamplePlotter_config = {
'bbox': (0.01, 0.01, 0.99, 0.82),
}
_default_config['BumpExamplePlotter'] = BumpExamplePlotter_config
##############################################################################
EIRasterPlotter_config = {
'fig_size': (3, 1.9),
'fig_ext': 'pdf',
'yticks': [1, 0, 0],
'ylabelPos': -0.35,
'scaleBar': [None, None, 25],
'scaleX': .85,
'scaleY': -.1,
}
_default_config['EIRasterPlotter'] = EIRasterPlotter_config
##############################################################################
EIRatePlotter_config = {
'fig_size': (3, .65),
'rateTop': .9,
'ylabelPos': -0.35,
}
_default_config['EIRatePlotter'] = EIRatePlotter_config
##############################################################################
MaxMeanThetaFRSweepPlotter_config = {
'cbar_kw':
dict(
label="max(E rate)/$\\theta$ cycle (Hz)",
location='left',
shrink=0.8,
pad=0.25,
ticks=ti.MultipleLocator(100),
#ticks = ti.LogLocator(base=4),
#format = ti.LogFormatter(4),
rasterized=True)
}
_default_config[
'MaxMeanThetaFRSweepPlotter'] = MaxMeanThetaFRSweepPlotter_config
##############################################################################
PSeizureSweepPlotter_config = {
'FRThreshold': 300,
'plot_grid_contours': [1, 1, 1],
'grid_contours': [.5],
}
PSeizureSweepPlotter_config.update({
'cbar_kw':
dict(label="P($E-rate_{{max}}$ > {0})".format(
PSeizureSweepPlotter_config['FRThreshold']),
location='left',
shrink=0.8,
pad=0.25,
ticks=ti.MultipleLocator(0.5),
rasterized=True)
})
_default_config['PSeizureSweepPlotter'] = PSeizureSweepPlotter_config
##############################################################################
MaxFRGridsProbabilityPlotter_config = {
'fig_size': (2.7, 2.7), # inches
'scale_factor': .85,
'bbox_rect': (0.3, 0.22, 0.92, 0.9),
}
_default_config[
'MaxFRGridsProbabilityPlotter'] = MaxFRGridsProbabilityPlotter_config
##############################################################################
PSeizureGridsProbabilityPlotter_config = {
'FRThreshold': 300,
'fig_size': (2.7, 2.7), # inches
'scale_factor': .85,
'bbox_rect': (0.3, 0.22, 0.92, 0.9),
}
_default_config[
'PSeizureGridsProbabilityPlotter'] = PSeizureGridsProbabilityPlotter_config
##############################################################################
PSeizureGridsScatterAllPlotter_config = {
'FRThreshold':
300,
'fig_size': (2.5, 2.2), # inches
'bbox_rect': (0.3, 0.23, 0.92, 0.9),
'tight_layout_kwargs': {
'pad': .2,
},
'legend_kwargs':
dict(loc=(0.5, 0.6),
fontsize='small',
frameon=False,
numpoints=1,
title='$\sigma$ (pA)'),
}
_default_config[
'PSeizureGridsScatterAllPlotter'] = PSeizureGridsScatterAllPlotter_config
##############################################################################
MaxFRGridsScatterAllPlotter_config = {
'fig_size': (2.5, 2.2), # inches
'bbox_rect': (0.3, 0.23, 0.92, 0.9),
'tight_layout_kwargs': {
'pad': .2,
},
'plot_legend':
False,
'legend_kwargs':
dict(loc=(0.6, 0.5),
fontsize='small',
frameon=False,
numpoints=1,
title='$\sigma$ (pA)'),
}
_default_config[
'MaxFRGridsScatterAllPlotter'] = MaxFRGridsScatterAllPlotter_config
##############################################################################
MaxStdThetaFRSweepPlotter_config = {
'cbar_kw':
dict(label="max(E rate)/$\\theta$ cycle (Hz)",
location='left',
shrink=0.8,
pad=0.25,
ticks=ti.MaxNLocator(4),
rasterized=True)
}
_default_config[
'MaxStdThetaFRSweepPlotter'] = MaxStdThetaFRSweepPlotter_config
##############################################################################
_default_config[
'MaxMedianThetaFRSweepPlotter'] = MaxStdThetaFRSweepPlotter_config
##############################################################################
VelSlopeSweepPlotter_config = {
'scale_factor':
.8,
'vmin':
-.472,
'vmax':
1.353,
'cbar': [0, 0, 1],
'cbar_kw':
dict(
location='right',
shrink=0.8,
pad=-0.1,
label='Slope\n(neurons/s/pA)',
ticks=ti.MultipleLocator(0.4),
),
'plot_contours': [1, 1, 1],
}
_default_config['VelSlopeSweepPlotter'] = VelSlopeSweepPlotter_config
##############################################################################
VelFitErrSweepPlotter_config = {
'scale_factor':
.8,
'cbar': [0, 0, 1],
'cbar_kw':
dict(label='Fit error (neurons/s)',
location='right',
shrink=0.8,
pad=-0.1,
ticks=ti.MultipleLocator(2),
rasterized=True),
'ylabel': [None, '', ''],
'yticks': [1, 0, 0],
'plot_contours': [1, 1, 1],
'vmin':
0,
'vmax':
11.2,
}
_default_config['VelFitErrSweepPlotter'] = VelFitErrSweepPlotter_config
##############################################################################
VelLinesPlotter_config = {
'scale_factor': .8,
'fig_size': (3., 2),
'bbox_rect': (0.4, 0.35, 0.95, 0.65),
'positions': ((5, 15), (5, 15), (5, 15)),
'ivel_range': 11,
'g_ann': False,
}
_default_config['VelLinesPlotter'] = VelLinesPlotter_config
##############################################################################
VelFitStdSweepPlotter_config = {
'scale_factor':
.7,
'cbar_kw':
dict(location='right',
label='Mean $\sigma_{spd}$ (neurons/s)',
shrink=0.8,
pad=0.05,
ticks=ti.MultipleLocator(5),
extend='max',
extendfrac=0.1)
}
_default_config['VelFitStdSweepPlotter'] = VelFitStdSweepPlotter_config
##############################################################################
VelocityRasterPlotter_config = {
'fig_size': (3.75, 2.2),
'transparent': True,
'bbox': (0.2, 0.2, 0.99, 0.8)
}
_default_config['VelocityRasterPlotter'] = VelocityRasterPlotter_config
##############################################################################
VelocityRatePlotter_config = {
'fig_size': (3.75, 1),
'bbox': (.2, .2, .99, 0.70),
'transparent': True,
}
_default_config['VelocityRatePlotter'] = VelocityRatePlotter_config
##############################################################################
VelocityRasterZoomPlotter_config = {
'fig_size': (3.75 * .75, 1.2),
'ylabelPos': -0.22,
'bbox': (0.2, 0.25, 0.99, 0.95),
'transparent': True,
}
_default_config[
'VelocityRasterZoomPlotter'] = VelocityRasterZoomPlotter_config
##############################################################################
ThetaSignalPlotter_config = {
'fig_size': (3, .5),
'T': .5e3, # ms
'bbox': (0, .05, 1., .95), # l, b, r, t
'color': (0, 0, 0, .3),
}
_default_config['ThetaSignalPlotter'] = ThetaSignalPlotter_config
##############################################################################
PACExamplePlotter_config = {
'fig_size': (5, 3.5),
'bbox': (0, .05, 1., .95), # l, b, r, t
'letter_xy': (0, 1.),
'theta_color': 'k',
'gamma_color': 'b',
}
_default_config['PACExamplePlotter'] = PACExamplePlotter_config
##############################################################################
RasterExamplePlotter_config = {
'fig_size': (6.2, 8.3),
'sweep_rect': (.12, .73, .45, .95),
'cbar_kw':
dict(label="Mean $E-rate_{max}^{\\theta}$ (Hz)",
location='right',
shrink=0.8,
pad=.05,
ticks=ti.MultipleLocator(250),
rasterized=True),
'FRThreshold':
300.,
'ylabelPos':
-0.1,
'markersize':
1.5,
'plot_ann_txt':
True,
'theta_color': (0, 0, 0, .3),
'fig_saver':
SeparateMultipageSaver(None, 'pdf')
}
_default_config['RasterExamplePlotter'] = RasterExamplePlotter_config
##############################################################################
ScatterGammaGridsSeparatePlotter_config = {
'fig_size': (5., 6.7),
#'bbox_rect': (0.12, 0.17, 0.98, 0.92),
}
_default_config[
'ScatterGammaGridsSeparatePlotter'] = ScatterGammaGridsSeparatePlotter_config
##############################################################################
ScatterGammaFGridsSeparatePlotter_config = {
'fig_size': (5., 6.7),
#'bbox_rect': (0.12, 0.17, 0.98, 0.92),
}
_default_config[
'ScatterGammaFGridsSeparatePlotter'] = ScatterGammaFGridsSeparatePlotter_config
##############################################################################
GridsPBumpsProbabilityPlotter_config = {
'fig_size': (2.7, 2.7), # inches
'bbox_rect': (0.25, 0.2, 0.95, 0.9),
'title_size': 'medium',
}
_default_config[
'GridsPBumpsProbabilityPlotter'] = GridsPBumpsProbabilityPlotter_config
##############################################################################
GridBumpScatterPlotter_config = {
'fig_size': (8.27, 11.69),
'color_box_width': .165
}
GridBumpScatterPlotter_config.update({
'color_box_coords': {
'left': 0.14, # w = 0.165
'bottom': .85,
'right': .14 + GridBumpScatterPlotter_config['color_box_width'],
'top': .95
}
#'bbox_rect': (0.12, 0.17, 0.98, 0.92),
})
_default_config['GridBumpScatterPlotter'] = GridBumpScatterPlotter_config
##############################################################################
GridSimpleExamplePlotter_config = {
'fig_size': (5.4, 2.5),
'transparent': True,
'ns_idx': 0,
'rc': (25, 2),
'trial_no': 0,
}
_default_config[
'GridSimpleExamplePlotter'] = GridSimpleExamplePlotter_config
##############################################################################
Burak2009ConnectionPlotter_config = {
'fig_size': (2, 2),
}
_default_config[
'Burak2009ConnectionPlotter'] = Burak2009ConnectionPlotter_config
##############################################################################
FRSweepPlotter_config = {
'scale_factor': .8,
'cbar_kw': {
'location': 'right', # This has to match cbar_kw_e and cbar_kw_i
},
'plot_grid_contours': [1, 1, 1],
'cbar_kw_e': {
'label': 'Mean E Firing rate (Hz)',
'location': 'right',
'shrink': 0.8,
'pad': -0.05,
'ticks': ti.LogLocator(subs=[1, 2, 4, 6, 8]),
'rasterized': True,
},
'cbar_kw_i': {
'label': 'Mean I Firing rate (Hz)',
'location': 'right',
'shrink': 0.8,
'pad': -0.05,
'ticks': ti.LogLocator(subs=[1, 2, 4, 6, 8]),
'rasterized': True,
},
}
_default_config['FRSweepPlotter'] = FRSweepPlotter_config
##############################################################################
ScatterGridsFRAllPlotter_config = {
'fig_size': (4.2, 3),
'dot_size':
6,
'legend_kwargs':
dict(loc=(0.4, 0.6),
fontsize='small',
frameon=False,
numpoints=1,
title='$\sigma$ (pA)'),
'bbox_rect': (.2, .2, .95, .95),
'ylabel':
'Gridness score',
'yticks':
True,
}
_default_config[
'ScatterGridsFRAllPlotter'] = ScatterGridsFRAllPlotter_config
###########################################################################
GridsVelFitErrProbabilityPlotter_config = {
'fig_size': (2.7, 2.7), # inches
'bbox_rect': (0.25, 0.2, 0.95, 0.9),
'title_size': 'medium',
'data_range': [[0, 11.2], [-.5, 1.2]],
}
_default_config[
'GridsVelFitErrProbabilityPlotter'] = GridsVelFitErrProbabilityPlotter_config
###########################################################################
_default_config.update({
'WeightOutE2IPlotter': {
'fig_size': (1.75, 1.75),
'g_idx': 15,
'neuron_idx': 527,
'use_title': False,
},
'WeightOutI2EPlotter': {
'fig_size': (1.75, 1.75),
'g_idx': 15,
'neuron_idx': 527,
'use_title': False,
},
'WeightInE2IPlotter': {
'fig_size': (1.75, 1.75),
'g_idx': 15,
'neuron_idx': 527,
'use_title': False,
},
'WeightInI2EPlotter': {
'fig_size': (1.75, 1.75),
'g_idx': 15,
'neuron_idx': 527,
'use_title': False,
},
})
_default_config['WeightGridPlotter'] = {
'fig_size': (3, 3),
'cbar_fig_size': (1, 0.5),
'bbox_rect': (.1, .1, .9, .9),
'g_idx': 15,
'neuron_idx': 527,
}
_default_config['GridExampleColorbarPlotter'] = {
'fig_size': (0.6, 0.8),
}
_default_config['BumpExampleColorbarPlotter'] = {
'fig_size': (0.6, 0.6),
}
###########################################################################
_default_config['HighGridScoreFraction'] = {
'threshold': .5,
}
##############################################################################
return _default_config
def test_init_config(self):
from configobj import ConfigObj
config = ConfigObj('test/bot.conf')
def base_config(config_path: Path, config=None):
global_params = dict(
regions='force_list(default=list())',
webhook_target='string(default="")',
webhook_header='header(default="", url=webhook_target)',
webhook_image='boolean(default=yes)',
webhook_image_type='option("vehicle", "original", default="vehicle")',
max_prediction_delay='float(default=6)',
memory_decay='float(default=300)',
image_format=
'string(default="$(camera)_screenshots/%y-%m-%d/%H-%M-%S.%f.jpg")',
sample='integer(default=2)',
total='integer(default=-1)',
mmc='boolean(default=no)',
csv_file='string(default="")',
jsonlines_file='string(default="")',
)
camera = dict(
url='string',
name='string',
active='boolean(default=yes)',
# Overridable
regions='force_list(default=None)',
webhook_target='string(default=None)',
webhook_header='header(default=None, url=webhook_target)',
webhook_image='boolean(default=None)',
webhook_image_type='option("vehicle", "original", default=None)',
max_prediction_delay='float(default=None)',
memory_decay='float(default=None)',
image_format='string(default=None)',
sample='integer(default=None)',
total='integer(default=None)',
mmc='boolean(default=None)',
csv_file='string(default=None)',
jsonlines_file='string(default=None)',
)
def webhook_header_check(value, *args, **kwargs):
token = value.split('Token ')[-1]
if not token:
return None
url = 'https://app.parkpow.com/api/v1/parking-list'
headers = {'Authorization': f'Token {token}'}
try:
response = requests.get(url, headers=headers, timeout=10)
except (requests.Timeout, requests.ConnectionError):
raise ValidateError('Please check your internet connection.')
if response.status_code != 200:
raise ValidateError('Wrong token.')
return value
spec = ConfigObj()
spec['timezone'] = 'string(default="UTC")'
spec['version'] = 'integer(default=2)'
spec['cameras'] = dict(__many__=camera, **global_params)
if not config_path.exists():
with open(config_path, 'w') as fp:
fp.write(DEFAULT_CONFIG.replace('\n', '\r\n'))
try:
config = ConfigObj(config.split('\n') if config else str(config_path),
configspec=spec,
raise_errors=True,
indent_type=' ')
config.newlines = '\r\n' # For Windows
except Exception as e:
logging.error(e)
return None, str(e)
validator = Validator({'header': webhook_header_check})
result = config.validate(validator, preserve_errors=True)
errors = flatten_errors(config, result)
if errors:
error_message = 'Config errors:'
for section_list, key, error in errors:
if error is False:
error = 'key %s is missing.' % key
elif key is not None:
section_list.append(key)
section_string = '/'.join(section_list)
logging.error('%s: %s', section_string, error)
error = f'{section_string}, param: {key}, message: {error}'
error_message += f'\n{error}'
return None, error_message
return config, None
def test_invalid_lines_with_percents(tmpdir, specpath):
ini = tmpdir.join('config.ini')
ini.write('extra: %H:%M\n')
with pytest.raises(ParseError):
conf = ConfigObj(str(ini), configspec=specpath, file_error=True)
def initialize(file=None, logging_level='INFO'):
"""Read the configuration file containing the run's parameters.
This should be the first call of most (all?) OGGM simulations.
Parameters
----------
file : str
path to the configuration file (default: OGGM params.cfg)
logging_level : str
set a logging level. See :func:`set_logging_config` for options.
"""
global IS_INITIALIZED
global PARAMS
global PATHS
set_logging_config(logging_level=logging_level)
if file is None:
file = os.path.join(os.path.abspath(os.path.dirname(__file__)),
'params.cfg')
try:
cp = ConfigObj(file, file_error=True)
except (ConfigObjError, IOError) as e:
log.critical('Config file could not be parsed (%s): %s', file, e)
sys.exit()
log.workflow('Using configuration file: %s', file)
# Paths
oggm_static_paths()
PATHS['working_dir'] = cp['working_dir']
PATHS['dem_file'] = cp['dem_file']
PATHS['climate_file'] = cp['climate_file']
# Multiprocessing pool
PARAMS['use_multiprocessing'] = cp.as_bool('use_multiprocessing')
PARAMS['mp_processes'] = cp.as_int('mp_processes')
# Some non-trivial params
PARAMS['continue_on_error'] = cp.as_bool('continue_on_error')
PARAMS['grid_dx_method'] = cp['grid_dx_method']
PARAMS['topo_interp'] = cp['topo_interp']
PARAMS['use_intersects'] = cp.as_bool('use_intersects')
PARAMS['use_compression'] = cp.as_bool('use_compression')
PARAMS['mpi_recv_buf_size'] = cp.as_int('mpi_recv_buf_size')
PARAMS['use_multiple_flowlines'] = cp.as_bool('use_multiple_flowlines')
PARAMS['filter_min_slope'] = cp.as_bool('filter_min_slope')
PARAMS['auto_skip_task'] = cp.as_bool('auto_skip_task')
PARAMS['correct_for_neg_flux'] = cp.as_bool('correct_for_neg_flux')
PARAMS['filter_for_neg_flux'] = cp.as_bool('filter_for_neg_flux')
PARAMS['run_mb_calibration'] = cp.as_bool('run_mb_calibration')
PARAMS['rgi_version'] = cp['rgi_version']
PARAMS['use_rgi_area'] = cp.as_bool('use_rgi_area')
PARAMS['compress_climate_netcdf'] = cp.as_bool('compress_climate_netcdf')
PARAMS['use_tar_shapefiles'] = cp.as_bool('use_tar_shapefiles')
PARAMS['clip_mu_star'] = cp.as_bool('clip_mu_star')
# Climate
PARAMS['baseline_climate'] = cp['baseline_climate'].strip().upper()
PARAMS['baseline_y0'] = cp.as_int('baseline_y0')
PARAMS['baseline_y1'] = cp.as_int('baseline_y1')
PARAMS['hydro_month_nh'] = cp.as_int('hydro_month_nh')
PARAMS['hydro_month_sh'] = cp.as_int('hydro_month_sh')
PARAMS['temp_use_local_gradient'] = cp.as_bool('temp_use_local_gradient')
PARAMS['tstar_search_glacierwide'] = cp.as_bool('tstar_search_glacierwide')
k = 'temp_local_gradient_bounds'
PARAMS[k] = [float(vk) for vk in cp.as_list(k)]
k = 'tstar_search_window'
PARAMS[k] = [int(vk) for vk in cp.as_list(k)]
PARAMS['use_bias_for_run'] = cp.as_bool('use_bias_for_run')
# Inversion
k = 'use_shape_factor_for_inversion'
PARAMS[k] = cp[k]
# Flowline model
k = 'use_shape_factor_for_fluxbasedmodel'
PARAMS[k] = cp[k]
# Make sure we have a proper cache dir
from oggm.utils import download_oggm_files, get_demo_file
download_oggm_files()
# Delete non-floats
ltr = [
'working_dir', 'dem_file', 'climate_file', 'use_tar_shapefiles',
'grid_dx_method', 'run_mb_calibration', 'compress_climate_netcdf',
'mp_processes', 'use_multiprocessing', 'baseline_y0', 'baseline_y1',
'temp_use_local_gradient', 'temp_local_gradient_bounds', 'topo_interp',
'use_compression', 'bed_shape', 'continue_on_error',
'use_multiple_flowlines', 'tstar_search_glacierwide',
'mpi_recv_buf_size', 'hydro_month_nh', 'clip_mu_star',
'tstar_search_window', 'use_bias_for_run', 'hydro_month_sh',
'use_intersects', 'filter_min_slope', 'auto_skip_task',
'correct_for_neg_flux', 'filter_for_neg_flux', 'rgi_version',
'use_shape_factor_for_inversion', 'use_rgi_area',
'use_shape_factor_for_fluxbasedmodel', 'baseline_climate'
]
for k in ltr:
cp.pop(k, None)
# Other params are floats
for k in cp:
PARAMS[k] = cp.as_float(k)
# Read-in the reference t* data - maybe it will be used, maybe not
fns = [
'ref_tstars_rgi5_cru4', 'ref_tstars_rgi6_cru4',
'ref_tstars_rgi5_histalp', 'ref_tstars_rgi6_histalp'
]
for fn in fns:
PARAMS[fn] = pd.read_csv(get_demo_file('oggm_' + fn + '.csv'))
fpath = get_demo_file('oggm_' + fn + '_calib_params.json')
with open(fpath, 'r') as fp:
mbpar = json.load(fp)
PARAMS[fn + '_calib_params'] = mbpar
# Empty defaults
set_intersects_db()
IS_INITIALIZED = True
# Pre extract cru cl to avoid problems by multiproc
from oggm.utils import get_cru_cl_file
get_cru_cl_file()
def __get_value_from_settings(prop_label):
config = ConfigObj('misc/settings.ini')
return config[prop_label]
def oggm_static_paths():
"""Initialise the OGGM paths from the config file."""
global PATHS, PARAMS
# See if the file is there, if not create it
if not os.path.exists(CONFIG_FILE):
dldir = os.path.join(os.path.expanduser('~'), 'OGGM')
config = ConfigObj()
config['dl_cache_dir'] = os.path.join(dldir, 'download_cache')
config['dl_cache_readonly'] = False
config['tmp_dir'] = os.path.join(dldir, 'tmp')
config['cru_dir'] = os.path.join(dldir, 'cru')
config['rgi_dir'] = os.path.join(dldir, 'rgi')
config['test_dir'] = os.path.join(dldir, 'tests')
config['has_internet'] = True
config.filename = CONFIG_FILE
config.write()
# OK, read in the file
try:
config = ConfigObj(CONFIG_FILE, file_error=True)
except (ConfigObjError, IOError) as e:
log.critical('Config file could not be parsed (%s): %s', CONFIG_FILE,
e)
sys.exit()
# Check that all keys are here
for k in [
'dl_cache_dir', 'dl_cache_readonly', 'tmp_dir', 'cru_dir',
'rgi_dir', 'test_dir', 'has_internet'
]:
if k not in config:
raise RuntimeError('The oggm config file ({}) should have an '
'entry for {}.'.format(CONFIG_FILE, k))
# Override defaults with env variables if available
if os.environ.get('OGGM_DOWNLOAD_CACHE_RO') is not None:
ro = bool(strtobool(os.environ.get('OGGM_DOWNLOAD_CACHE_RO')))
config['dl_cache_readonly'] = ro
if os.environ.get('OGGM_DOWNLOAD_CACHE') is not None:
config['dl_cache_dir'] = os.environ.get('OGGM_DOWNLOAD_CACHE')
if os.environ.get('OGGM_EXTRACT_DIR') is not None:
# This is for the directories where OGGM needs to extract things
# On the cluster it might be useful to do it on a fast disc
edir = os.path.abspath(os.environ.get('OGGM_EXTRACT_DIR'))
config['tmp_dir'] = os.path.join(edir, 'tmp')
config['cru_dir'] = os.path.join(edir, 'cru')
config['rgi_dir'] = os.path.join(edir, 'rgi')
if not config['dl_cache_dir']:
raise RuntimeError('At the very least, the "dl_cache_dir" entry '
'should be provided in the oggm config file '
'({})'.format(CONFIG_FILE, k))
# Fill the PATH dict
for k, v in config.iteritems():
if not k.endswith('_dir'):
continue
PATHS[k] = os.path.abspath(os.path.expanduser(v))
# Other
PARAMS['has_internet'] = config.as_bool('has_internet')
PARAMS['dl_cache_readonly'] = config.as_bool('dl_cache_readonly')
# Create cache dir if possible
if not os.path.exists(PATHS['dl_cache_dir']):
if not PARAMS['dl_cache_readonly']:
os.makedirs(PATHS['dl_cache_dir'])
sys.setdefaultencoding("UTF-8")
current_locale_encoding = locale.getlocale()[1].lower()
logger.debug("sys default encoding %s", sys.getdefaultencoding())
logger.debug("After %s", locale.nl_langinfo(locale.CODESET))
if current_locale_encoding not in ["utf-8", "utf8"]:
logger.error("Need a UTF-8 locale. Currently '%s'. Exiting..." %
current_locale_encoding)
sys.exit(1)
configure_locale()
# loading config file
try:
config = ConfigObj("/etc/airtime/airtime.conf")
except Exception as e:
logger.error("Error loading config file: %s", e)
sys.exit(1)
class Global:
def __init__(self, api_client):
self.api_client = api_client
def selfcheck(self):
return self.api_client.is_server_compatible()
def test_api(self):
self.api_client.test()
def start(args):
# Load config file
config = ConfigObj(infile=args.config.name)
data_dir = config['data_dir']
uwsgi_log_path = config['uwsgi_log_path']
min_msecs = int(config.get('min_msecs', DEFAULT_MIN_MSECS))
url_file = config.get('url_file')
# Load custom url rules
url_rules = []
if url_file:
with open(url_file, 'r') as fp:
url_rules = parse_url_rules(fp)
html_dir = os.path.join(data_dir, 'html')
db_dir = os.path.join(data_dir, 'data')
makedir_if_none_exists(html_dir)
makedir_if_none_exists(db_dir)
save_point = SavePoint(db_dir)
last_log_datetime = save_point.get_last_datetime() or \
(datetime.datetime.now() - datetime.timedelta(seconds=REALTIME_UPDATE_INTERVAL))
logger.info('Start from last savepoint, last_log_datetime: %s' %
last_log_datetime)
last_update_datetime = None
url_classifier = URLClassifier(user_defined_rules=url_rules)
analyzer = RealtimeLogAnalyzer(url_classifier=url_classifier,
min_msecs=min_msecs,
start_from_datetime=last_log_datetime)
file_tailer = Tailer(uwsgi_log_path)
html_render = HTMLRender(html_dir, domain=config.get('domain'))
# Listen INT/TERM signal
def gracefully_exit(*args):
logger.info('Sinal received, exit.')
file_tailer.stop_follow()
signal.signal(signal.SIGINT, gracefully_exit)
for line in file_tailer:
# Analyze line
if line != no_new_line:
analyzer.analyze_line(line)
now = datetime.datetime.now()
if not file_tailer.trailing:
continue
if last_update_datetime and \
total_seconds(now - last_update_datetime) < REALTIME_UPDATE_INTERVAL:
continue
# Render HTML file when:
# - file_tailer reaches end of file.
# - last_update_datetime if over one `interval` from now
# Render latest interval HTML file
html_render.render_requests_data_to_html(
analyzer.get_data('last_interval'),
'latest_5mins.html',
context={'datetime_range': 'Last 5 minutes'})
analyzer.clean_data_by_key('last_interval')
for date in list(analyzer.data.keys()):
day_requests_data = RequestsData(date, db_dir)
merge_requests_data_to(day_requests_data.data,
analyzer.get_data(date))
# Render to HTML file
html_render.render_requests_data_to_html(
day_requests_data.data,
'day_%s.html' % date,
context={'datetime_range': date})
# Save data to pickle file
day_requests_data.save()
# Reset Everything
analyzer.clean_data_by_key(date)
update_html_symlink(html_dir)
last_update_datetime = now
if analyzer.last_analyzed_datetime:
save_point.set_last_datetime(analyzer.last_analyzed_datetime)
save_point.save()
