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()