def test_illegal_bootstrap_count(self):
with self.assertRaises(ValueError):
Bootstrapper(bootstrap_count=0)
with self.assertRaises(ValueError):
Bootstrapper(bootstrap_count=-1)
with self.assertRaises(ValueError):
Bootstrapper(bootstrap_count=128.256)
def __init__(self,
host,
port,
db,
matrix,
rel,
seeds,
n,
keep,
reset,
scorer,
it=1):
self.logger = multiprocessing.get_logger()
#self.logger.setLevel(logging.DEBUG)
self.logger.setLevel(logging.INFO)
#self.logger.setLevel(logging.WARNING)
if len(self.logger.handlers) == 0:
handler = logging.StreamHandler()
handler.setLevel(logging.INFO)
fmt = '%(asctime)s [%(levelname)s/CPL:' + rel + '] %(message)s'
formatter = logging.Formatter(fmt)
handler.setFormatter(formatter)
self.logger.addHandler(handler)
self.boot_i = '%s_%s_cpl_i' % (matrix, rel)
self.boot_p = '%s_%s_cpl_p' % (matrix, rel)
Bootstrapper.__init__(self, host, port, db, matrix, rel, seeds, n,
keep, reset, scorer, it)
def __init__(self,
host,
port,
db,
matrix,
rel,
seeds,
n,
keep,
reset,
scorer,
it=1):
#logging.basicConfig()
self.logger = logging.getLogger('Espresso')
self.logger.setLevel(logging.INFO)
#self.logger.setLevel(logging.WARNING)
if len(self.logger.handlers) == 0:
handler = logging.StreamHandler()
handler.setLevel(logging.INFO)
fmt = '%(asctime)s [%(levelname)s/Espresso:' + rel + '] %(message)s'
formatter = logging.Formatter(fmt)
handler.setFormatter(formatter)
self.logger.addHandler(handler)
Bootstrapper.__init__(self, host, port, db, matrix, rel, seeds, n,
keep, reset, scorer, it)
def test_illegal_n_jobs(self):
with self.assertRaises(ValueError):
Bootstrapper(n_jobs=0)
with self.assertRaises(ValueError):
Bootstrapper(n_jobs=-2)
with self.assertRaises(ValueError):
Bootstrapper(n_jobs=1.2)
def __init__(self, host, port, db, matrix, rel, seeds, n, keep, reset, scorer, it=1):
# logging.basicConfig()
self.logger = logging.getLogger("Espresso")
self.logger.setLevel(logging.INFO)
# self.logger.setLevel(logging.WARNING)
if len(self.logger.handlers) == 0:
handler = logging.StreamHandler()
handler.setLevel(logging.INFO)
fmt = "%(asctime)s [%(levelname)s/Espresso:" + rel + "] %(message)s"
formatter = logging.Formatter(fmt)
handler.setFormatter(formatter)
self.logger.addHandler(handler)
Bootstrapper.__init__(self, host, port, db, matrix, rel, seeds, n, keep, reset, scorer, it)
def __init__(self, host, port, db, matrix, rel,
seeds, n, keep, reset, scorer, it=1):
self.logger = multiprocessing.get_logger()
#self.logger.setLevel(logging.DEBUG)
self.logger.setLevel(logging.INFO)
#self.logger.setLevel(logging.WARNING)
if len(self.logger.handlers) == 0:
handler = logging.StreamHandler()
handler.setLevel(logging.INFO)
fmt = '%(asctime)s [%(levelname)s/CPL:' + rel + '] %(message)s'
formatter = logging.Formatter(fmt)
handler.setFormatter(formatter)
self.logger.addHandler(handler)
self.boot_i = '%s_%s_cpl_i' % (matrix, rel)
self.boot_p = '%s_%s_cpl_p' % (matrix, rel)
Bootstrapper.__init__(
self, host, port, db, matrix, rel,
seeds, n, keep, reset, scorer, it
)
def one_rep_bootstrap(self) -> None:
self.one_rep()
loglik = self.res.llf
bs = Bootstrapper(self.df)
df_copies = [self.df.copy()] * bs.num_copies
loglik_copies = [0.] * bs.num_copies
self.bootstrap_and_refit(bs, df_copies, loglik_copies)
if loglik < max(loglik_copies):
max_index = np.argmax(loglik_copies)
self.df = df_copies[max_index]
def setUp(self):
self.number_of_resamples = 10000
# import dataset from file
filename = 'flicker.xlsx'
self.__fh = FileHandling()
self.original_data_dict = self.__fh.import_spreadsheet(filename)
# resample dataset
self.__bootstrapper = Bootstrapper(self.original_data_dict,
self.number_of_resamples)
#init bootstrap analysis tools
self.analysis = BootstrapAnalysis(self.__bootstrapper)
def __init__(self, filename, number_of_resamples=10000):
"""
Initializing the Bootstrapit class executes the resampling of the imported dataset.
:param filename: The filename including filepath to the import data file.
:param number_of_resamples: The number of resamples to perform.
"""
self.number_of_resamples = number_of_resamples
# import dataset from file
self.__fh = FileHandling()
self.original_data_dict = self.__fh.import_spreadsheet(filename)
# resample dataset
self.__bootstrapper = Bootstrapper(self.original_data_dict, number_of_resamples)
#init bootstrap analysis tools
self.__analysis = BootstrapAnalysis(self.__bootstrapper)
#init plotter
self.__plotter = Plotting(self.__fh.export_order)
from flask import Flask, render_template, request, Response
import qbittorrentapi
from bootstrapper import Status, Bootstrapper
app = Flask(__name__)
app.config['DEBUG'] = True
bs = Bootstrapper()
@app.route("/")
def index():
return render_template("index.html")
@app.route("/bootstrap", methods=['POST'])
def bootstrap():
if bs is not None and bs.is_working():
res = Response()
return res, 102
bs.bootstrap(request.json['magnet'])
return " ".join(["OK", bs.token])
@app.route("/status")
def status():
if bs is None:
return "0 IDLE"
else:
return " ".join([bs.get_status(), bs.get_status_string()])
def test_full_argument(self):
Bootstrapper(n_jobs=2, bootstrap_count=256)
def test_emtpy_argument(self):
Bootstrapper()
def main():
bootstrapper = Bootstrapper()
bootstrapper.initialize()
tests = Tests()
tests.run()
