# This file is part of Lerot.
#
# Lerot is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Lerot is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with Lerot. If not, see <http://www.gnu.org/licenses/>.
import numpy as np
from numpy import zeros
from AbstractUserModel import AbstractUserModel
[docs]class PositionBasedUserModel(AbstractUserModel):
"""Defines a positions based user model."""
def __init__(self, p):
self.p_param = p
[docs] def p(self, i):
return self.p_param ** i
[docs] def get_clicks(self, result_list, labels, **kwargs):
"""simulate clicks on list l"""
c = zeros(len(result_list), dtype='int')
for pos, d in enumerate(result_list):
E = np.random.binomial(1, self.p(pos))
label = labels[d.get_id()]
if E and label:
c[pos] = 1
return c
[docs] def get_examination_prob(self, result_list, **kwargs):
return [self.p(i) for i in range(len(result_list))]