contrib/lisp/org-learn.el

   1 ;;; org-learn.el --- Implements SuperMemo's incremental learning algorithm
   2
   3 ;; Copyright (C) 2009
   4 ;;   Free Software Foundation, Inc.
   5
   6 ;; Author: John Wiegley <johnw at gnu dot org>
   7 ;; Keywords: outlines, hypermedia, calendar, wp
   8 ;; Homepage: http://orgmode.org
   9 ;; Version: 6.32trans
  10 ;;
  11 ;; This file is part of GNU Emacs.
  12 ;;
  13 ;; GNU Emacs is free software: you can redistribute it and/or modify
  14 ;; it under the terms of the GNU General Public License as published by
  15 ;; the Free Software Foundation, either version 3 of the License, or
  16 ;; (at your option) any later version.
  17
  18 ;; GNU Emacs is distributed in the hope that it will be useful,
  19 ;; but WITHOUT ANY WARRANTY; without even the implied warranty of
  20 ;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  21 ;; GNU General Public License for more details.
  22
  23 ;; You should have received a copy of the GNU General Public License
  24 ;; along with GNU Emacs.  If not, see <http://www.gnu.org/licenses/>.
  25 ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
  26 ;;
  27 ;;; Commentary:
  28
  29 ;; The file implements the learning algorithm described at
  30 ;; http://supermemo.com/english/ol/sm5.htm, which is a system for reading
  31 ;; material according to "spaced repetition".  See
  32 ;; http://en.wikipedia.org/wiki/Spaced_repetition for more details.
  33 ;;
  34 ;; To use, turn on state logging and schedule some piece of information you
  35 ;; want to read.  Then in the agenda buffer type
  36
  37 (require 'org)
  38 (eval-when-compile
  39   (require 'cl)
  40   (require 'calendar))
  41
  42 (defgroup org-learn nil
  43   "Options concerning the learning code in Org-mode."
  44   :tag "Org Learn"
  45   :group 'org-progress)
  46
  47 (defcustom org-learn-always-reschedule nil
  48   "If non-nil, always reschedule items, even if retention was \"perfect\"."
  49   :type 'boolean
  50   :group 'org-learn)
  51
  52 (defcustom org-learn-fraction 0.5
  53   "Controls the rate at which EF is increased or decreased.
  54 Must be a number between 0 and 1 (the greater it is the faster
  55 the changes of the OF matrix)."
  56   :type 'float
  57   :group 'org-learn)
  58
  59 (defun initial-optimal-factor (n ef)
  60   (if (= 1 n)
  61       4
  62     ef))
  63
  64 (defun get-optimal-factor (n ef of-matrix)
  65   (let ((factors (assoc n of-matrix)))
  66     (or (and factors
  67              (let ((ef-of (assoc ef (cdr factors))))
  68                (and ef-of (cdr ef-of))))
  69         (initial-optimal-factor n ef))))
  70
  71 (defun set-optimal-factor (n ef of-matrix of)
  72   (let ((factors (assoc n of-matrix)))
  73     (if factors
  74         (let ((ef-of (assoc ef (cdr factors))))
  75           (if ef-of
  76               (setcdr ef-of of)
  77             (push (cons ef of) (cdr factors))))
  78       (push (cons n (list (cons ef of))) of-matrix)))
  79   of-matrix)
  80
  81 (defun inter-repetition-interval (n ef &optional of-matrix)
  82   (let ((of (get-optimal-factor n ef of-matrix)))
  83     (if (= 1 n)
  84         of
  85       (* of (inter-repetition-interval (1- n) ef of-matrix)))))
  86
  87 (defun modify-e-factor (ef quality)
  88   (if (< ef 1.3)
  89       1.3
  90     (+ ef (- 0.1 (* (- 5 quality) (+ 0.08 (* (- 5 quality) 0.02)))))))
  91
  92 (defun modify-of (of q fraction)
  93   (let ((temp (* of (+ 0.72 (* q 0.07)))))
  94     (+ (* (- 1 fraction) of) (* fraction temp))))
  95
  96 (defun calculate-new-optimal-factor (interval-used quality used-of
  97                                                    old-of fraction)
  98   "This implements the SM-5 learning algorithm in Lisp.
  99 INTERVAL-USED is the last interval used for the item in question.
 100 QUALITY is the quality of the repetition response.
 101 USED-OF is the optimal factor used in calculation of the last
 102 interval used for the item in question.
 103 OLD-OF is the previous value of the OF entry corresponding to the
 104 relevant repetition number and the E-Factor of the item.
 105 FRACTION is a number belonging to the range (0,1) determining the
 106 rate of modifications (the greater it is the faster the changes
 107 of the OF matrix).
 108
 109 Returns the newly calculated value of the considered entry of the
 110 OF matrix."
 111   (let (;; the value proposed for the modifier in case of q=5
 112         (mod5 (/ (1+ interval-used) interval-used))
 113         ;; the value proposed for the modifier in case of q=2
 114         (mod2 (/ (1- interval-used) interval-used))
 115         ;; the number determining how many times the OF value will
 116         ;; increase or decrease
 117         modifier)
 118     (if (< mod5 1.05)
 119         (setq mod5 1.05))
 120     (if (< mod2 0.75)
 121         (setq mod5 0.75))
 122     (if (> quality 4)
 123         (setq modifier (1+ (* (- mod5 1) (- quality 4))))
 124       (setq modifier (- 1 (* (/ (- 1 mod2) 2) (- 4 quality)))))
 125     (if (< modifier 0.05)
 126         (setq modifier 0.05))
 127     (setq new-of (* used-of modifier))
 128     (if (> quality 4)
 129         (if (< new-of old-of)
 130             (setq new-of old-of)))
 131     (if (< quality 4)
 132         (if (> new-of old-of)
 133             (setq new-of old-of)))
 134     (setq new-of (+ (* new-of fraction) (* old-of (- 1 fraction))))
 135     (if (< new-of 1.2)
 136         (setq new-of 1.2)
 137       new-of)))
 138
 139 (defvar initial-repetition-state '(-1 1 2.5 nil))
 140
 141 (defun determine-next-interval (n ef quality of-matrix)
 142   (assert (> n 0))
 143   (assert (and (>= quality 0) (<= quality 5)))
 144   (if (< quality 3)
 145       (list (inter-repetition-interval n ef) (1+ n) ef nil)
 146     (let ((next-ef (modify-e-factor ef quality)))
 147       (setq of-matrix
 148             (set-optimal-factor n next-ef of-matrix
 149                                 (modify-of (get-optimal-factor n ef of-matrix)
 150                                            quality org-learn-fraction))
 151             ef next-ef)
 152       ;; For a zero-based quality of 4 or 5, don't repeat
 153       (if (and (>= quality 4)
 154                (not org-learn-always-reschedule))
 155           (list 0 (1+ n) ef of-matrix)
 156         (list (inter-repetition-interval n ef of-matrix) (1+ n)
 157               ef of-matrix)))))
 158
 159 (defun org-smart-reschedule (quality)
 160   (interactive "nHow well did you remember the information (on a scale of 0-5)? ")
 161   (let* ((learn-str (org-entry-get (point) "LEARN_DATA"))
 162          (learn-data (or (and learn-str
 163                               (read learn-str))
 164                          (copy-list initial-repetition-state)))
 165          closed-dates)
 166     (setq learn-data
 167           (determine-next-interval (nth 1 learn-data)
 168                                    (nth 2 learn-data)
 169                                    quality
 170                                    (nth 3 learn-data)))
 171     (org-entry-put (point) "LEARN_DATA" (prin1-to-string learn-data))
 172     (if (= 0 (nth 0 learn-data))
 173         (org-schedule t)
 174       (org-schedule nil (time-add (current-time)
 175                                   (days-to-time (nth 0 learn-data)))))))
 176
 177 (provide 'org-learn)
 178
 179 ;; arch-tag: a46bb0e5-e4fb-4004-a9b8-63933c55af33
 180
 181 ;;; org-learn.el ends here