Exemplo n.º 1
0
def main():
    bootstrap()
    display_introduction()
    factory = Router()

    command = None
    while not is_command_exit(command):
        clear_screen()
        command = get_command()
        try:
            factory.execute_command(command)
        except Exception as e:
            print(e)
Exemplo n.º 2
0
def plot_bar(variations, q=None, show_title=False):
    index = np.arange(len(variations))
    bar_width = 0.8

    mu = np.empty(len(variations))
    se = np.empty(len(variations))
    for i, v in enumerate(variations):
        scores = v.LOO_scores
        if q is None:
            f = np.mean
        else:

            def f(vals):
                return np.percentile(vals, q)

        mu[i], se[i] = bootstrap(scores, f)

    fig = plt.figure()
    ax = fig.add_axes([0.12, 0.12, 0.8, 0.8])
    ax.bar(
        index,
        mu,
        yerr=se,
        width=bar_width,
        color='b',
        error_kw={
            'ecolor': '0.3',
            'linewidth': 2
        },
    )
    ttl = ''
    if q is None:
        ttl = 'Mean $R^2$ dependence on priors'
        ylabel = 'mean $R^2$'
    else:
        ttl = '{} percentile $R^2$ dependence on priors'.format(q)
        ylabel = '{} percentile $R^2$'.format(q)
    if show_title:
        ax.set_title(ttl, fontsize=fontsize)
    ax.set_xlabel('which priors', fontsize=fontsize)
    ax.set_ylabel(ylabel, fontsize=fontsize)
    ax.set_xticks(index + bar_width / 2)
    ax.set_xticklabels([latex_label(v.theta, v.sigma) for v in variations])
    ticks = [0, 0.1, 0.2, 0.3]
    ax.set_yticks(ticks)
    ax.set_yticklabels(['{:g}'.format(t) for t in ticks])
    ax.tick_params(axis='both', labelsize=fontsize)
    ax.set_ylim(0, 0.3)

    return fig
Exemplo n.º 3
0
def analyze_variant(theta,sigma):
    theta_priors = priors_name if theta else None
    sigma_prior = 'normal' if sigma else None
    shape = Sigslope(theta_priors)
    fitter = Fitter(shape,sigma_prior)
    fits = get_all_fits(data,fitter,allow_new_computation=False)
    LOO_scores = [f.LOO_score for f in iterate_fits(fits) if f.LOO_score is not None]
    mu,sem = bootstrap(LOO_scores, np.mean)
    return Bunch(
        theta = theta,
        sigma = sigma,
        LOO_scores = LOO_scores,
        mu = mu,
        sem = sem,
    )
Exemplo n.º 4
0
def analyze_variant(theta, sigma):
    theta_priors = priors_name if theta else None
    sigma_prior = 'normal' if sigma else None
    shape = Sigslope(theta_priors)
    fitter = Fitter(shape, sigma_prior)
    fits = get_all_fits(data, fitter, allow_new_computation=False)
    LOO_scores = [
        f.LOO_score for f in iterate_fits(fits) if f.LOO_score is not None
    ]
    mu, sem = bootstrap(LOO_scores, np.mean)
    return Bunch(
        theta=theta,
        sigma=sigma,
        LOO_scores=LOO_scores,
        mu=mu,
        sem=sem,
    )
Exemplo n.º 5
0
def plot_bar(variations, q=None, show_title=False):
    index = np.arange(len(variations))
    bar_width = 0.8
    
    mu = np.empty(len(variations))
    se = np.empty(len(variations))
    for i,v in enumerate(variations):
        scores = v.LOO_scores
        if q is None:
            f = np.mean
        else:
            def f(vals): return np.percentile(vals,q)
        mu[i],se[i] = bootstrap(scores, f)
    
    fig = plt.figure()
    ax = fig.add_axes([0.12,0.12,0.8,0.8])
    ax.bar(
        index, 
        mu, 
        yerr=se,
        width=bar_width,
        color='b',
        error_kw = {'ecolor': '0.3', 'linewidth': 2},
    )  
    ttl = ''
    if q is None:
        ttl = 'Mean $R^2$ dependence on priors'
        ylabel = 'mean $R^2$'
    else:
        ttl = '{} percentile $R^2$ dependence on priors'.format(q)
        ylabel = '{} percentile $R^2$'.format(q)
    if show_title:
        ax.set_title(ttl, fontsize=fontsize)
    ax.set_xlabel('which priors', fontsize=fontsize)
    ax.set_ylabel(ylabel, fontsize=fontsize)
    ax.set_xticks(index + bar_width/2)
    ax.set_xticklabels([latex_label(v.theta,v.sigma) for v in variations])
    ticks = [0,0.1,0.2,0.3]
    ax.set_yticks(ticks)
    ax.set_yticklabels(['{:g}'.format(t) for t in ticks])
    ax.tick_params(axis='both', labelsize=fontsize)
    ax.set_ylim(0,0.3)

    return fig
 def setUpClass(cls):
     bootstrap()
Exemplo n.º 7
0
from datetime import datetime, timedelta
import pytest

from app.storage import Storage
from utils.bootstrap import bootstrap

bootstrap()
storage = Storage()


class TestToken:
    @pytest.fixture(scope='class')
    def new_token(self):
        return storage.add_token()

    def test_add_token(self, new_token):
        token, expires = new_token
        assert token
        assert not expires

    def test_verify_expire_token(self, new_token):
        token, expires = new_token
        assert storage.verify_token(token)
        assert storage.expire_token(token)

    def test_expired_token(self, new_token):
        token, expires = new_token
        assert not storage.verify_token(token)

    def test_delete_token(self, new_token):
        token, expires = new_token