dotemacs

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org-learn.el (6080B)


      1 ;;; org-learn.el --- Implements SuperMemo's incremental learning algorithm
      2 
      3 ;; Copyright (C) 2009-2021 Free Software Foundation, Inc.
      4 
      5 ;; Author: John Wiegley <johnw at gnu dot org>
      6 ;; Keywords: outlines, hypermedia, calendar, wp
      7 ;; Homepage: https://git.sr.ht/~bzg/org-contrib
      8 ;; Version: 6.32trans
      9 ;;
     10 ;; This file is not part of GNU Emacs.
     11 ;;
     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.
     16 
     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.
     21 
     22 ;; You should have received a copy of the GNU General Public License
     23 ;; along with GNU Emacs.  If not, see <https://www.gnu.org/licenses/>.
     24 ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
     25 ;;
     26 ;;; Commentary:
     27 
     28 ;; The file implements the learning algorithm described at
     29 ;; https://supermemo.com/english/ol/sm5.htm, which is a system for reading
     30 ;; material according to "spaced repetition".  See
     31 ;; https://en.wikipedia.org/wiki/Spaced_repetition for more details.
     32 ;;
     33 ;; To use, turn on state logging and schedule some piece of information you
     34 ;; want to read.  Then in the agenda buffer type
     35 
     36 (require 'org)
     37 (eval-when-compile
     38   (require 'cl))
     39 
     40 (defgroup org-learn nil
     41   "Options concerning the learning code in Org-mode."
     42   :tag "Org Learn"
     43   :group 'org-progress)
     44 
     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)
     49 
     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)
     56 
     57 (defun initial-optimal-factor (n ef)
     58   (if (= 1 n)
     59       4
     60     ef))
     61 
     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))))
     68 
     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)
     78 
     79 (defun inter-repetition-interval (n ef &optional of-matrix)
     80   (let ((of (get-optimal-factor n ef of-matrix)))
     81     (if (= 1 n)
     82 	of
     83       (* of (inter-repetition-interval (1- n) ef of-matrix)))))
     84 
     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)))))))
     89 
     90 (defun modify-of (of q fraction)
     91   (let ((temp (* of (+ 0.72 (* q 0.07)))))
     92     (+ (* (- 1 fraction) of) (* fraction temp))))
     93 
     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).
    106 
    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)))
    136 
    137 (defvar initial-repetition-state '(-1 1 2.5 nil))
    138 
    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)))))
    156 
    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)))))))
    174 
    175 (provide 'org-learn)
    176 
    177 ;;; org-learn.el ends here