Closed ghost closed 1 year ago
I will update my Anki version to check it.
I can't reproduce this bug. Could you share the collection with me?
I reinstalled Anki and it seems it works. It's just a clean Anki and collection. Should I share the collection? I don't know, maybe my machine is old. I'll try again and write to you. I have another question. Can I change let maximumInterval = 36500 for global parameters and maximumInterval = 36500 for a specific deck? For example, 3650?? Does it work with the addon Customize Keyboard Shortcuts? (My "Good" and "Again" are not "3" and "4")
Can I change let maximumInterval = 36500 for global parameters and maximumInterval = 36500 for a specific deck?
Yep, you can. I have given the example in the code.
Does it work with the addon Customize Keyboard Shortcuts? (My "Good" and "Again" are not "3" and "4")
It doesn't matter. FSRS4Anki only consider the rating given by Anki. The keyboard shortcuts didn't modify the value of ratings.
So, I reinstalled Mac OS. First, I installed Anki 2.1.55. beta 6 qt 5 and there's the same mistake. Then I tried Anki 2.1.55 beta 6 qt6 and I think it works. I used these versions: I didn't change anything and didn't paste "_div id=deck deckname="{{Deck}}"></div" for a specific deck. I don't have any add-ons as well. Here's my collection: collection.colpkg.zip (It's just a test.) Also I have this when I run Anki 2.1.55 beta 6 qt 6:
Does it work with the addon Customize Keyboard Shortcuts? (My "Good" and "Again" are not "3" and "4")
It doesn't matter. FSRS4Anki only consider the rating given by Anki. The keyboard shortcuts didn't modify the value of ratings.
Thank you for your help!
So, I reinstalled Mac OS. First, I installed Anki 2.1.55. beta 6 qt 5 and there's the same mistake. Then I tried Anki 2.1.55 beta 6 qt6 and I think it works. I used these versions:
I guess this problem could only be solved in Anki's source code. I will report it to dae.
The Chromium bundled with Qt 5.14 does not support the optional chaining operator (?.).
So FSRS4Anki couldn't run in Qt5
version of Anki.
You can try this following compatible code:
// FSRS4Anki v3.9.5 Scheduler
set_version();
// The latest version will be released on https://github.com/open-spaced-repetition/fsrs4anki
// Default parameters of FSRS4Anki for global
var w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.12, 0.8, 2, -0.2, 0.2, 1];
// The above parameters can be optimized via FSRS4Anki optimizer.
// User's custom parameters for global
let requestRetention = 0.9; // recommended setting: 0.8 ~ 0.9
let maximumInterval = 36500;
let easyBonus = 1.3;
let hardInterval = 1.2;
// FSRS only modifies the long-term scheduling. So (re)learning steps in deck options work as usual.
// I recommend not to set steps longer than one day.
// "Fuzz" is a small random delay applied to new intervals to prevent cards from
// sticking together and always coming up for review on the same day
const enable_fuzz = true;
debugger;
// get the name of the card's deck
// need to add <div id=deck deck_name="{{Deck}}"></div> to your card's front template's first line
if (document.getElementById("deck") !== null) {
const deck_name = document.getElementById("deck").getAttribute("deck_name");
// parameters for a specific deck
if (deck_name == "ALL::Learning::English::Reading") {
var w = [1.1475, 1.401, 5.1483, -1.4221, -1.2282, 0.035, 1.4668, -0.1286, 0.7539, 1.9671, -0.2307, 0.32, 0.9451];
// User's custom parameters for the specific deck
requestRetention = 0.9;
maximumInterval = 36500;
easyBonus = 1.3;
hardInterval = 1.2;
// parameters for a deck's all sub-decks
} else if (deck_name.startsWith("ALL::Archive")) {
var w = [1.2879, 0.5135, 4.9532, -1.502, -1.0922, 0.0081, 1.3771, -0.0294, 0.6718, 1.8335, -0.4066, 0.7291, 0.5517];
// User's custom parameters for sub-decks
requestRetention = 0.9;
maximumInterval = 36500;
easyBonus = 1.3;
hardInterval = 1.2;
}
}
// auto-calculate intervalModifier
const intervalModifier = Math.log(requestRetention) / Math.log(0.9);
// global fuzz factor for all ratings.
const fuzz_factor = set_fuzz_factor();
const ratings = {
"again": 1,
"hard": 2,
"good": 3,
"easy": 4
};
// For new cards
if (is_new()) {
var _states$good$normal, _states$easy$normal;
init_states();
const good_interval = next_interval(customData.good.s);
const easy_interval = Math.max(next_interval(customData.easy.s * easyBonus), good_interval + 1);
if ((_states$good$normal = states.good.normal) !== null && _states$good$normal !== void 0 && _states$good$normal.review) {
states.good.normal.review.scheduledDays = good_interval;
}
if ((_states$easy$normal = states.easy.normal) !== null && _states$easy$normal !== void 0 && _states$easy$normal.review) {
states.easy.normal.review.scheduledDays = easy_interval;
}
// For learning/relearning cards
} else if (is_learning()) {
var _states$good$normal2, _states$easy$normal2;
// Init states if the card didn't contain customData
if (is_empty()) {
init_states();
}
const good_interval = next_interval(customData.good.s);
const easy_interval = Math.max(next_interval(customData.easy.s * easyBonus), good_interval + 1);
if ((_states$good$normal2 = states.good.normal) !== null && _states$good$normal2 !== void 0 && _states$good$normal2.review) {
states.good.normal.review.scheduledDays = good_interval;
}
if ((_states$easy$normal2 = states.easy.normal) !== null && _states$easy$normal2 !== void 0 && _states$easy$normal2.review) {
states.easy.normal.review.scheduledDays = easy_interval;
}
// For review cards
} else if (is_review()) {
var _states$current$norma, _states$again$normal, _states$hard$normal, _states$good$normal3, _states$easy$normal3;
// Convert the interval and factor to stability and difficulty if the card didn't contain customData
if (is_empty()) {
convert_states();
}
const interval = (_states$current$norma = states.current.normal) !== null && _states$current$norma !== void 0 && _states$current$norma.review.elapsedDays ? states.current.normal.review.elapsedDays : states.current.filtered.rescheduling.originalState.review.elapsedDays;
const last_d = customData.again.d;
const last_s = customData.again.s;
const retrievability = Math.exp(Math.log(0.9) * interval / last_s);
const lapses = (_states$again$normal = states.again.normal) !== null && _states$again$normal !== void 0 && _states$again$normal.relearning.review.lapses ? states.again.normal.relearning.review.lapses : states.again.filtered.rescheduling.originalState.relearning.review.lapses;
customData.again.d = next_difficulty(last_d, "again");
customData.again.s = next_forget_stability(customData.again.d, last_s, retrievability);
customData.hard.d = next_difficulty(last_d, "hard");
customData.hard.s = next_recall_stability(customData.hard.d, last_s, retrievability);
customData.good.d = next_difficulty(last_d, "good");
customData.good.s = next_recall_stability(customData.good.d, last_s, retrievability);
customData.easy.d = next_difficulty(last_d, "easy");
customData.easy.s = next_recall_stability(customData.easy.d, last_s, retrievability);
let hard_interval = next_interval(last_s * hardInterval);
let good_interval = next_interval(customData.good.s);
let easy_interval = next_interval(customData.easy.s * easyBonus);
hard_interval = Math.min(hard_interval, good_interval);
good_interval = Math.max(good_interval, hard_interval + 1);
easy_interval = Math.max(easy_interval, good_interval + 1);
if ((_states$hard$normal = states.hard.normal) !== null && _states$hard$normal !== void 0 && _states$hard$normal.review) {
states.hard.normal.review.scheduledDays = hard_interval;
}
if ((_states$good$normal3 = states.good.normal) !== null && _states$good$normal3 !== void 0 && _states$good$normal3.review) {
states.good.normal.review.scheduledDays = good_interval;
}
if ((_states$easy$normal3 = states.easy.normal) !== null && _states$easy$normal3 !== void 0 && _states$easy$normal3.review) {
states.easy.normal.review.scheduledDays = easy_interval;
}
}
function constrain_difficulty(difficulty) {
return Math.min(Math.max(difficulty.toFixed(2), 1), 10);
}
function apply_fuzz(ivl) {
if (!enable_fuzz || ivl < 2.5) return ivl;
ivl = Math.round(ivl);
const min_ivl = Math.max(2, Math.round(ivl * 0.95 - 1));
const max_ivl = Math.round(ivl * 1.05 + 1);
return Math.floor(fuzz_factor * (max_ivl - min_ivl + 1) + min_ivl);
}
function next_interval(stability) {
const new_interval = apply_fuzz(stability * intervalModifier);
return Math.min(Math.max(Math.round(new_interval), 1), maximumInterval);
}
function next_difficulty(d, rating) {
let next_d = d + w[4] * (ratings[rating] - 3);
return constrain_difficulty(mean_reversion(w[2], next_d));
}
function mean_reversion(init, current) {
return w[5] * init + (1 - w[5]) * current;
}
function next_recall_stability(d, s, r) {
return +(s * (1 + Math.exp(w[6]) * (11 - d) * Math.pow(s, w[7]) * (Math.exp((1 - r) * w[8]) - 1))).toFixed(2);
}
function next_forget_stability(d, s, r) {
return +(w[9] * Math.pow(d, w[10]) * Math.pow(s, w[11]) * Math.exp((1 - r) * w[12])).toFixed(2);
}
function init_states() {
customData.again.d = init_difficulty("again");
customData.again.s = init_stability("again");
customData.hard.d = init_difficulty("hard");
customData.hard.s = init_stability("hard");
customData.good.d = init_difficulty("good");
customData.good.s = init_stability("good");
customData.easy.d = init_difficulty("easy");
customData.easy.s = init_stability("easy");
}
function init_difficulty(rating) {
return +constrain_difficulty(w[2] + w[3] * (ratings[rating] - 3)).toFixed(2);
}
function init_stability(rating) {
return +Math.max(w[0] + w[1] * (ratings[rating] - 1), 0.1).toFixed(2);
}
function convert_states() {
const scheduledDays = states.current.normal ? states.current.normal.review.scheduledDays : states.current.filtered.rescheduling.originalState.review.scheduledDays;
const easeFactor = states.current.normal ? states.current.normal.review.easeFactor : states.current.filtered.rescheduling.originalState.review.easeFactor;
const old_s = +Math.max(scheduledDays, 0.1).toFixed(2);
const old_d = constrain_difficulty(11 - (easeFactor - 1) / (Math.exp(w[6]) * Math.pow(old_s, w[7]) * (Math.exp(0.1 * w[8]) - 1)));
customData.again.d = old_d;
customData.again.s = old_s;
customData.hard.d = old_d;
customData.hard.s = old_s;
customData.good.d = old_d;
customData.good.s = old_s;
customData.easy.d = old_d;
customData.easy.s = old_s;
}
function is_new() {
var _states$current$norma2, _states$current$filte, _states$current$filte2;
if (((_states$current$norma2 = states.current.normal) === null || _states$current$norma2 === void 0 ? void 0 : _states$current$norma2.new) !== undefined) {
var _states$current$norma3;
if (((_states$current$norma3 = states.current.normal) === null || _states$current$norma3 === void 0 ? void 0 : _states$current$norma3.new) !== null) {
return true;
}
}
if (((_states$current$filte = states.current.filtered) === null || _states$current$filte === void 0 ? void 0 : (_states$current$filte2 = _states$current$filte.rescheduling) === null || _states$current$filte2 === void 0 ? void 0 : _states$current$filte2.originalState) !== undefined) {
var _states$current$filte3, _states$current$filte4;
if ((_states$current$filte3 = states.current.filtered) !== null && _states$current$filte3 !== void 0 && (_states$current$filte4 = _states$current$filte3.rescheduling) !== null && _states$current$filte4 !== void 0 && _states$current$filte4.originalState.hasOwnProperty('new')) {
return true;
}
}
return false;
}
function is_learning() {
var _states$current$norma4, _states$current$filte5, _states$current$filte6, _states$current$norma6, _states$current$filte9, _states$current$filte10;
if (((_states$current$norma4 = states.current.normal) === null || _states$current$norma4 === void 0 ? void 0 : _states$current$norma4.learning) !== undefined) {
var _states$current$norma5;
if (((_states$current$norma5 = states.current.normal) === null || _states$current$norma5 === void 0 ? void 0 : _states$current$norma5.learning) !== null) {
return true;
}
}
if (((_states$current$filte5 = states.current.filtered) === null || _states$current$filte5 === void 0 ? void 0 : (_states$current$filte6 = _states$current$filte5.rescheduling) === null || _states$current$filte6 === void 0 ? void 0 : _states$current$filte6.originalState) !== undefined) {
var _states$current$filte7, _states$current$filte8;
if ((_states$current$filte7 = states.current.filtered) !== null && _states$current$filte7 !== void 0 && (_states$current$filte8 = _states$current$filte7.rescheduling) !== null && _states$current$filte8 !== void 0 && _states$current$filte8.originalState.hasOwnProperty('learning')) {
return true;
}
}
if (((_states$current$norma6 = states.current.normal) === null || _states$current$norma6 === void 0 ? void 0 : _states$current$norma6.relearning) !== undefined) {
var _states$current$norma7;
if (((_states$current$norma7 = states.current.normal) === null || _states$current$norma7 === void 0 ? void 0 : _states$current$norma7.relearning) !== null) {
return true;
}
}
if (((_states$current$filte9 = states.current.filtered) === null || _states$current$filte9 === void 0 ? void 0 : (_states$current$filte10 = _states$current$filte9.rescheduling) === null || _states$current$filte10 === void 0 ? void 0 : _states$current$filte10.originalState) !== undefined) {
var _states$current$filte11, _states$current$filte12;
if ((_states$current$filte11 = states.current.filtered) !== null && _states$current$filte11 !== void 0 && (_states$current$filte12 = _states$current$filte11.rescheduling) !== null && _states$current$filte12 !== void 0 && _states$current$filte12.originalState.hasOwnProperty('relearning')) {
return true;
}
}
return false;
}
function is_review() {
var _states$current$norma8, _states$current$filte13, _states$current$filte14;
if (((_states$current$norma8 = states.current.normal) === null || _states$current$norma8 === void 0 ? void 0 : _states$current$norma8.review) !== undefined) {
var _states$current$norma9;
if (((_states$current$norma9 = states.current.normal) === null || _states$current$norma9 === void 0 ? void 0 : _states$current$norma9.review) !== null) {
return true;
}
}
if (((_states$current$filte13 = states.current.filtered) === null || _states$current$filte13 === void 0 ? void 0 : (_states$current$filte14 = _states$current$filte13.rescheduling) === null || _states$current$filte14 === void 0 ? void 0 : _states$current$filte14.originalState) !== undefined) {
var _states$current$filte15, _states$current$filte16;
if ((_states$current$filte15 = states.current.filtered) !== null && _states$current$filte15 !== void 0 && (_states$current$filte16 = _states$current$filte15.rescheduling) !== null && _states$current$filte16 !== void 0 && _states$current$filte16.originalState.hasOwnProperty('review')) {
return true;
}
}
return false;
}
function is_empty() {
return !customData.again.d | !customData.again.s | !customData.hard.d | !customData.hard.s | !customData.good.d | !customData.good.s | !customData.easy.d | !customData.easy.s;
}
function set_version() {
const version = "3.9.5";
customData.again.v = version;
customData.hard.v = version;
customData.good.v = version;
customData.easy.v = version;
}
function set_fuzz_factor() {
// Note: Originally copied from seedrandom.js package (https://github.com/davidbau/seedrandom)
!function(f,a,c){var s,l=256,p="random",d=c.pow(l,6),g=c.pow(2,52),y=2*g,h=l-1;function n(n,t,r){function e(){for(var n=u.g(6),t=d,r=0;n<g;)n=(n+r)*l,t*=l,r=u.g(1);for(;y<=n;)n/=2,t/=2,r>>>=1;return(n+r)/t}var o=[],i=j(function n(t,r){var e,o=[],i=typeof t;if(r&&"object"==i)for(e in t)try{o.push(n(t[e],r-1))}catch(n){}return o.length?o:"string"==i?t:t+"\0"}((t=1==t?{entropy:!0}:t||{}).entropy?[n,S(a)]:null==n?function(){try{var n;return s&&(n=s.randomBytes)?n=n(l):(n=new Uint8Array(l),(f.crypto||f.msCrypto).getRandomValues(n)),S(n)}catch(n){var t=f.navigator,r=t&&t.plugins;return[+new Date,f,r,f.screen,S(a)]}}():n,3),o),u=new m(o);return e.int32=function(){return 0|u.g(4)},e.quick=function(){return u.g(4)/4294967296},e.double=e,j(S(u.S),a),(t.pass||r||function(n,t,r,e){return e&&(e.S&&v(e,u),n.state=function(){return v(u,{})}),r?(c[p]=n,t):n})(e,i,"global"in t?t.global:this==c,t.state)}function m(n){var t,r=n.length,u=this,e=0,o=u.i=u.j=0,i=u.S=[];for(r||(n=[r++]);e<l;)i[e]=e++;for(e=0;e<l;e++)i[e]=i[o=h&o+n[e%r]+(t=i[e])],i[o]=t;(u.g=function(n){for(var t,r=0,e=u.i,o=u.j,i=u.S;n--;)t=i[e=h&e+1],r=r*l+i[h&(i[e]=i[o=h&o+t])+(i[o]=t)];return u.i=e,u.j=o,r})(l)}function v(n,t){return t.i=n.i,t.j=n.j,t.S=n.S.slice(),t}function j(n,t){for(var r,e=n+"",o=0;o<e.length;)t[h&o]=h&(r^=19*t[h&o])+e.charCodeAt(o++);return S(t)}function S(n){return String.fromCharCode.apply(0,n)}if(j(c.random(),a),"object"==typeof module&&module.exports){module.exports=n;try{s=require("crypto")}catch(n){}}else"function"==typeof define&&define.amd?define(function(){return n}):c["seed"+p]=n}("undefined"!=typeof self?self:this,[],Math);
// MIT License
// Copyright 2019 David Bau.
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
let seed = !customData.again.seed | !customData.hard.seed | !customData.good.seed | !customData.easy.seed ? document.getElementById("qa").innerText : customData.good.seed;
const generator = new Math.seedrandom(seed);
const fuzz_factor = generator();
seed = Math.round(fuzz_factor * 10000)
customData.again.seed = (seed + 1) % 10000;
customData.hard.seed = (seed + 2) % 10000;
customData.good.seed = (seed + 3) % 10000;
customData.easy.seed = (seed + 4) % 10000;
return fuzz_factor;
}
Is this also a problem with Qt 5.15 on Windows 10?
Is this also a problem with Qt 5.15 on Windows 10?
It is a problem with Qt 5, regardless of the OS platform.
"So FSRS4Anki couldn't run in Qt5 version of Anki.
You can try this following compatible code:
// FSRS4Anki v3.9.5 Scheduler set_version(); // The latest version will be released on https://github.com/open-spaced-repetition/fsrs4anki
// Default parameters of FSRS4Anki for global var w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.12, 0.8, 2, -0.2, 0.2, 1]; // The above parameters can be optimized via FSRS4Anki optimizer.
// User's custom parameters for global let requestRetention = 0.9; // recommended setting: 0.8 ~ 0.9 let maximumInterval = 36500; let easyBonus = 1.3; let hardInterval = 1.2; // FSRS only modifies the long-term scheduling. So (re)learning steps in deck options work as usual. // I recommend not to set steps longer than one day."
Sorry for replying late. I've tried the code and everything's alright. Will you also update the code for Qt5 in the future?
Sorry for replying late. I've tried the code and everything's alright. Will you also update the code for Qt5 in the future?
Thanks to your reply and test. I will release the code and maintain it.
Cool! Thanks again for help!
Hi. I wanted to try your schedule but I have this mistake. Anki 2.1.55 beta 6, Mac OS Bug Sur 11.7.1. It's a new collection and it doesn't have any add-ons except AnkiWEb Inspector.