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[org-mode.git] / contrib / lisp / org-learn.el
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1 ;;; org-learn.el --- Implements SuperMemo's incremental learning algorithm
3 ;; Copyright (C) 2009-2014 Free Software Foundation, Inc.
5 ;; Author: John Wiegley <johnw at gnu dot org>
6 ;; Keywords: outlines, hypermedia, calendar, wp
7 ;; Homepage: http://orgmode.org
8 ;; Version: 6.32trans
9 ;;
10 ;; This file is not part of GNU Emacs.
12 ;; This program is free software: you can redistribute it and/or modify
13 ;; it under the terms of the GNU General Public License as published by
14 ;; the Free Software Foundation, either version 3 of the License, or
15 ;; (at your option) any later version.
17 ;; This program is distributed in the hope that it will be useful,
18 ;; but WITHOUT ANY WARRANTY; without even the implied warranty of
19 ;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
20 ;; GNU General Public License for more details.
22 ;; You should have received a copy of the GNU General Public License
23 ;; along with GNU Emacs. If not, see <http://www.gnu.org/licenses/>.
24 ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
26 ;;; Commentary:
28 ;; The file implements the learning algorithm described at
29 ;; http://supermemo.com/english/ol/sm5.htm, which is a system for reading
30 ;; material according to "spaced repetition". See
31 ;; http://en.wikipedia.org/wiki/Spaced_repetition for more details.
33 ;; To use, turn on state logging and schedule some piece of information you
34 ;; want to read. Then in the agenda buffer type
36 (require 'org)
37 (eval-when-compile
38 (require 'cl))
40 (defgroup org-learn nil
41 "Options concerning the learning code in Org-mode."
42 :tag "Org Learn"
43 :group 'org-progress)
45 (defcustom org-learn-always-reschedule nil
46 "If non-nil, always reschedule items, even if retention was \"perfect\"."
47 :type 'boolean
48 :group 'org-learn)
50 (defcustom org-learn-fraction 0.5
51 "Controls the rate at which EF is increased or decreased.
52 Must be a number between 0 and 1 (the greater it is the faster
53 the changes of the OF matrix)."
54 :type 'float
55 :group 'org-learn)
57 (defun initial-optimal-factor (n ef)
58 (if (= 1 n)
60 ef))
62 (defun get-optimal-factor (n ef of-matrix)
63 (let ((factors (assoc n of-matrix)))
64 (or (and factors
65 (let ((ef-of (assoc ef (cdr factors))))
66 (and ef-of (cdr ef-of))))
67 (initial-optimal-factor n ef))))
69 (defun set-optimal-factor (n ef of-matrix of)
70 (let ((factors (assoc n of-matrix)))
71 (if factors
72 (let ((ef-of (assoc ef (cdr factors))))
73 (if ef-of
74 (setcdr ef-of of)
75 (push (cons ef of) (cdr factors))))
76 (push (cons n (list (cons ef of))) of-matrix)))
77 of-matrix)
79 (defun inter-repetition-interval (n ef &optional of-matrix)
80 (let ((of (get-optimal-factor n ef of-matrix)))
81 (if (= 1 n)
83 (* of (inter-repetition-interval (1- n) ef of-matrix)))))
85 (defun modify-e-factor (ef quality)
86 (if (< ef 1.3)
87 1.3
88 (+ ef (- 0.1 (* (- 5 quality) (+ 0.08 (* (- 5 quality) 0.02)))))))
90 (defun modify-of (of q fraction)
91 (let ((temp (* of (+ 0.72 (* q 0.07)))))
92 (+ (* (- 1 fraction) of) (* fraction temp))))
94 (defun calculate-new-optimal-factor (interval-used quality used-of
95 old-of fraction)
96 "This implements the SM-5 learning algorithm in Lisp.
97 INTERVAL-USED is the last interval used for the item in question.
98 QUALITY is the quality of the repetition response.
99 USED-OF is the optimal factor used in calculation of the last
100 interval used for the item in question.
101 OLD-OF is the previous value of the OF entry corresponding to the
102 relevant repetition number and the E-Factor of the item.
103 FRACTION is a number belonging to the range (0,1) determining the
104 rate of modifications (the greater it is the faster the changes
105 of the OF matrix).
107 Returns the newly calculated value of the considered entry of the
108 OF matrix."
109 (let (;; the value proposed for the modifier in case of q=5
110 (mod5 (/ (1+ interval-used) interval-used))
111 ;; the value proposed for the modifier in case of q=2
112 (mod2 (/ (1- interval-used) interval-used))
113 ;; the number determining how many times the OF value will
114 ;; increase or decrease
115 modifier)
116 (if (< mod5 1.05)
117 (setq mod5 1.05))
118 (if (< mod2 0.75)
119 (setq mod5 0.75))
120 (if (> quality 4)
121 (setq modifier (1+ (* (- mod5 1) (- quality 4))))
122 (setq modifier (- 1 (* (/ (- 1 mod2) 2) (- 4 quality)))))
123 (if (< modifier 0.05)
124 (setq modifier 0.05))
125 (setq new-of (* used-of modifier))
126 (if (> quality 4)
127 (if (< new-of old-of)
128 (setq new-of old-of)))
129 (if (< quality 4)
130 (if (> new-of old-of)
131 (setq new-of old-of)))
132 (setq new-of (+ (* new-of fraction) (* old-of (- 1 fraction))))
133 (if (< new-of 1.2)
134 (setq new-of 1.2)
135 new-of)))
137 (defvar initial-repetition-state '(-1 1 2.5 nil))
139 (defun determine-next-interval (n ef quality of-matrix)
140 (assert (> n 0))
141 (assert (and (>= quality 0) (<= quality 5)))
142 (if (< quality 3)
143 (list (inter-repetition-interval n ef) (1+ n) ef nil)
144 (let ((next-ef (modify-e-factor ef quality)))
145 (setq of-matrix
146 (set-optimal-factor n next-ef of-matrix
147 (modify-of (get-optimal-factor n ef of-matrix)
148 quality org-learn-fraction))
149 ef next-ef)
150 ;; For a zero-based quality of 4 or 5, don't repeat
151 (if (and (>= quality 4)
152 (not org-learn-always-reschedule))
153 (list 0 (1+ n) ef of-matrix)
154 (list (inter-repetition-interval n ef of-matrix) (1+ n)
155 ef of-matrix)))))
157 (defun org-smart-reschedule (quality)
158 (interactive "nHow well did you remember the information (on a scale of 0-5)? ")
159 (let* ((learn-str (org-entry-get (point) "LEARN_DATA"))
160 (learn-data (or (and learn-str
161 (read learn-str))
162 (copy-list initial-repetition-state)))
163 closed-dates)
164 (setq learn-data
165 (determine-next-interval (nth 1 learn-data)
166 (nth 2 learn-data)
167 quality
168 (nth 3 learn-data)))
169 (org-entry-put (point) "LEARN_DATA" (prin1-to-string learn-data))
170 (if (= 0 (nth 0 learn-data))
171 (org-schedule t)
172 (org-schedule nil (time-add (current-time)
173 (days-to-time (nth 0 learn-data)))))))
175 (provide 'org-learn)
177 ;;; org-learn.el ends here