Fiddle with emacs config (when to use -n, -c), get emacs using el-get.

1 files changed, 0 insertions, 180 deletions

diff --git a/.emacs.d/org-7.4/contrib/lisp/org-learn.el b/.emacs.d/org-7.4/contrib/lisp/org-learn.el
deleted file mode 100644
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--- a/.emacs.d/org-7.4/contrib/lisp/org-learn.el
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@@ -1,180 +0,0 @@
-;;; org-learn.el --- Implements SuperMemo's incremental learning algorithm
-
-;; Copyright (C) 2009
-;;   Free Software Foundation, Inc.
-
-;; Author: John Wiegley <johnw at gnu dot org>
-;; Keywords: outlines, hypermedia, calendar, wp
-;; Homepage: http://orgmode.org
-;; Version: 6.32trans
-;;
-;; This file is part of GNU Emacs.
-;;
-;; GNU Emacs 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 3 of the License, or
-;; (at your option) any later version.
-
-;; GNU Emacs 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 GNU Emacs.  If not, see <http://www.gnu.org/licenses/>.
-;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
-;;
-;;; Commentary:
-
-;; The file implements the learning algorithm described at
-;; http://supermemo.com/english/ol/sm5.htm, which is a system for reading
-;; material according to "spaced repetition".  See
-;; http://en.wikipedia.org/wiki/Spaced_repetition for more details.
-;;
-;; To use, turn on state logging and schedule some piece of information you
-;; want to read.  Then in the agenda buffer type
-
-(require 'org)
-(eval-when-compile
-  (require 'cl))
-
-(defgroup org-learn nil
-  "Options concerning the learning code in Org-mode."
-  :tag "Org Learn"
-  :group 'org-progress)
-
-(defcustom org-learn-always-reschedule nil
-  "If non-nil, always reschedule items, even if retention was \"perfect\"."
-  :type 'boolean
-  :group 'org-learn)
-
-(defcustom org-learn-fraction 0.5
-  "Controls the rate at which EF is increased or decreased.
-Must be a number between 0 and 1 (the greater it is the faster
-the changes of the OF matrix)."
-  :type 'float
-  :group 'org-learn)
-
-(defun initial-optimal-factor (n ef)
-  (if (= 1 n)
-      4
-    ef))
-
-(defun get-optimal-factor (n ef of-matrix)
-  (let ((factors (assoc n of-matrix)))
-    (or (and factors
-	     (let ((ef-of (assoc ef (cdr factors))))
-	       (and ef-of (cdr ef-of))))
-	(initial-optimal-factor n ef))))
-
-(defun set-optimal-factor (n ef of-matrix of)
-  (let ((factors (assoc n of-matrix)))
-    (if factors
-	(let ((ef-of (assoc ef (cdr factors))))
-	  (if ef-of
-	      (setcdr ef-of of)
-	    (push (cons ef of) (cdr factors))))
-      (push (cons n (list (cons ef of))) of-matrix)))
-  of-matrix)
-
-(defun inter-repetition-interval (n ef &optional of-matrix)
-  (let ((of (get-optimal-factor n ef of-matrix)))
-    (if (= 1 n)
-	of
-      (* of (inter-repetition-interval (1- n) ef of-matrix)))))
-
-(defun modify-e-factor (ef quality)
-  (if (< ef 1.3)
-      1.3
-    (+ ef (- 0.1 (* (- 5 quality) (+ 0.08 (* (- 5 quality) 0.02)))))))
-
-(defun modify-of (of q fraction)
-  (let ((temp (* of (+ 0.72 (* q 0.07)))))
-    (+ (* (- 1 fraction) of) (* fraction temp))))
-
-(defun calculate-new-optimal-factor (interval-used quality used-of
-						   old-of fraction)
-  "This implements the SM-5 learning algorithm in Lisp.
-INTERVAL-USED is the last interval used for the item in question.
-QUALITY is the quality of the repetition response.
-USED-OF is the optimal factor used in calculation of the last
-interval used for the item in question.
-OLD-OF is the previous value of the OF entry corresponding to the
-relevant repetition number and the E-Factor of the item.
-FRACTION is a number belonging to the range (0,1) determining the
-rate of modifications (the greater it is the faster the changes
-of the OF matrix).
-
-Returns the newly calculated value of the considered entry of the
-OF matrix."
-  (let (;; the value proposed for the modifier in case of q=5
-	(mod5 (/ (1+ interval-used) interval-used))
-	;; the value proposed for the modifier in case of q=2
-	(mod2 (/ (1- interval-used) interval-used))
-	;; the number determining how many times the OF value will
-	;; increase or decrease
-	modifier)
-    (if (< mod5 1.05)
-	(setq mod5 1.05))
-    (if (< mod2 0.75)
-	(setq mod5 0.75))
-    (if (> quality 4)
-	(setq modifier (1+ (* (- mod5 1) (- quality 4))))
-      (setq modifier (- 1 (* (/ (- 1 mod2) 2) (- 4 quality)))))
-    (if (< modifier 0.05)
-	(setq modifier 0.05))
-    (setq new-of (* used-of modifier))
-    (if (> quality 4)
-	(if (< new-of old-of)
-	    (setq new-of old-of)))
-    (if (< quality 4)
-	(if (> new-of old-of)
-	    (setq new-of old-of)))
-    (setq new-of (+ (* new-of fraction) (* old-of (- 1 fraction))))
-    (if (< new-of 1.2)
-	(setq new-of 1.2)
-      new-of)))
-
-(defvar initial-repetition-state '(-1 1 2.5 nil))
-
-(defun determine-next-interval (n ef quality of-matrix)
-  (assert (> n 0))
-  (assert (and (>= quality 0) (<= quality 5)))
-  (if (< quality 3)
-      (list (inter-repetition-interval n ef) (1+ n) ef nil)
-    (let ((next-ef (modify-e-factor ef quality)))
-      (setq of-matrix
-	    (set-optimal-factor n next-ef of-matrix
-				(modify-of (get-optimal-factor n ef of-matrix)
-					   quality org-learn-fraction))
-	    ef next-ef)
-      ;; For a zero-based quality of 4 or 5, don't repeat
-      (if (and (>= quality 4)
-	       (not org-learn-always-reschedule))
-	  (list 0 (1+ n) ef of-matrix)
-	(list (inter-repetition-interval n ef of-matrix) (1+ n)
-	      ef of-matrix)))))
-
-(defun org-smart-reschedule (quality)
-  (interactive "nHow well did you remember the information (on a scale of 0-5)? ")
-  (let* ((learn-str (org-entry-get (point) "LEARN_DATA"))
-	 (learn-data (or (and learn-str
-			      (read learn-str))
-			 (copy-list initial-repetition-state)))
-	 closed-dates)
-    (setq learn-data
-	  (determine-next-interval (nth 1 learn-data)
-				   (nth 2 learn-data)
-				   quality
-				   (nth 3 learn-data)))
-    (org-entry-put (point) "LEARN_DATA" (prin1-to-string learn-data))
-    (if (= 0 (nth 0 learn-data))
-	(org-schedule t)
-      (org-schedule nil (time-add (current-time)
-				  (days-to-time (nth 0 learn-data)))))))
-
-(provide 'org-learn)
-
-;; arch-tag: a46bb0e5-e4fb-4004-a9b8-63933c55af33
-
-;;; org-learn.el ends here