from __future__ import division # GNU Solfege - free ear training software # Copyright (C) 2005, 2007 Tom Cato Amundsen # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program 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 General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin ST, Fifth Floor, Boston, MA 02110-1301 USA import random import cfg class Random(object): def __init__(self, choices): #TODO add assert that all choices are unique self.m_choices = choices self.m_choice_count = len(choices) * [0] # The number of randoms generated self.m_count = 0 self.m_last_choices = [] def reset(self): self.m_last_choices = [] self.m_choice_count = len(self.m_choices) * [0] self.m_count = 0 def get_random_by_random_data(self, available_choices): not_selected_factor = 2 data = [] count = 0.0 for k in available_choices: count += self.m_choice_count[k] / self.m_count data.append([k, self.m_choice_count[k] / self.m_count, 0.0]) maxval = 0.0 for v in data: if v[1] != 0.0: v[2] = 1/pow(v[1], cfg.get_float("app/randomness")) maxval = max(maxval, v[2]) # Give the questions that has not been asked any times, twice as # big chance to be asked as the question that has been asked # fewest times. for v in data: if v[1] == 0.0: v[2] = maxval * not_selected_factor return data def random_by_random(self, available_choices): """ Select by random, but make it more likely that choices that has been selected few times are selected than questions that has been selected many times. """ if self.m_count == 0: return random.choice(available_choices) data = self.get_random_by_random_data(available_choices) f = 0.0 for v in data: f += v[2] v.append(f) selectval = data[-1][3] * random.random() for v in data: if selectval < v[3]: return v[0] return data[-1][0] def random_by_random2(self, available_choices): """ Select by random, but make it more likely that choices that has been selected few times are selected than questions that has been selected many times. """ if self.m_count == 0: return random.choice(available_choices) data = self.get_random_by_random_data(available_choices) if self.m_last_choices: data[self.m_last_choices[-1]][2] *= 0.5 if len(self.m_last_choices) >= 2 and self.m_last_choices[-1] == self.m_last_choices[-2]: data[self.m_last_choices[-1]][2] *= 0.5 f = 0.0 for v in data: f += v[2] v.append(f) selectval = data[-1][3] * random.random() for v in data: if selectval < v[3]: return v[0] return data[-1][0] def random_by_selection(self, available_choices): """ The smallest randomness value is 1 Larger value make things more even. Smaller value make things more random. """ v = [] if self.m_count > len(self.m_choices): for k in available_choices: if self.m_choice_count[k] / self.m_count < 1 / (len(self.m_choices) * self.get_float("app/randomness")): v.append(k) if v: return random.choice(v) return random.choice(self.m_choices) def add(self, idx): self.m_choice_count[idx] += 1 self.m_count += 1 self.m_last_choices.append(idx) if len(self.m_last_choices) > len(self.m_choices) * 2: self.m_last_choices.pop(0)