data:image/png;base64,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data:image/png;base64,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 THE GAME TO TURBO MODESET GAME TO TURBO MODESpriteCheck if player 1 wins horizontallycounter0i1Check if player 1 wins vertically 411321231141511421331241421331241151611521431341521431341251431341251161621531441351531441351261441351261171631541451361541451361271641551461371641531421311651541431321541431321211661551441331551441331221441331221111671561451341561451341231451341231121571461351241461351241131471361251141falseCheck if player 1 wins diagonally Checks if player 2 wins horizontallycounter0i1Checks if player 2 wins vertically412322232142512422332242422332242152612522432342522432342252432342252162622532442352532442352262442352262172632542452362542452362272642552462372642532422312652542432322542432322212662552442332552442332222442332222112672562452342562452342232452342232122572462352242462352242132472362252142falseChecks if player 2 wins diagonallyEach time you press space and the last tile of the column is empty, this algorithm will check if player 1 (red chip) has win.Each time you press space and the last tile of the column is empty, this algorithm will check if player 1 (black chip) has win.Each time you press space and the last tile of the column is empty, this algorithm will check if player 2 (black chip) has win.anythingtruei1move madetrue42Each time you press space and the last tile of the column is empty, this algorithm will check if player 2 (black chip) has win.anythingtrueSad TromboneLooks like a tie2not valid if there are no more empty tiles to put a chipStart GameThis would change from player 1 to player 2 (changes the costumes, red = player 1; black = player 2)1804.75145.251#inoutLABEL will stamp text on the stage at the given font size. The direction of the text is the direction the sprite is facing, and color will match the pen color.de:drucke _ in Größe _
ca:etiqueta _ de mida _
es:etiqueta _ de tamaño _
fr:étiquette _ d'une taille de _
Hello!12de:behalte Elemente, die _ aus _
ca:manté els elements on _ de _
es:mantener los elementos donde _ de _
fr:garder les items tels que _ de _
1de:kombiniere mit _ die Elemente von _
ca:combina amb _ els elements de _
es:combinar con _ los elementos de _
fr:combine avec _ les items de _
1de:für _ = _ bis _ _
ca:per _ = _ fins _ _
es:para _ = _ hasta _ _
fr:pour _ allant de _ à _ _
110ide:füge Wörter zusammen _
ca:uneix les paraules _
es:unir las palabras _
fr:fusionne les mots _
121de:Liste $arrowRight Satz _
ca:llista $arrowRight frase _
es:lista $arrowRight frase _
fr:liste $arrowRight phrase _
de:Satz $arrowRight Liste _
ca:frase $arrowRight llista _
es:frase $arrowRight lista _
fr:phrase $arrowRight liste _
de:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
cont3de:wirf _
ca:llança _
es:lanzar _
fr:lance _
catchtagde:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
contde:wirf _ _
ca:llança _ _
es:lanzar _ _
fr:lance _ _
catchtagde:falls _ dann _ und pause $pause-1-255-220-0
ca:si _ fes _ i atura-ho tot $pause-1-255-220-0
es:si _ haz _ y páralo todo $pause-1-255-220-0
fr:si _ faire _ et mettre tout en pause $pause-1-255-220-0
de:Wort $arrowRight Liste _
ca:paraula $arrowRight llista _
es:palabra $arrowRight lista _
fr:mot $arrowRight liste _
de:ignoriere _
ca:ignora _
es:ignorar _
fr:ignore _
de:Liste $arrowRight Wort _
ca:llista $arrowRight paraula _
es:lista $arrowRight palabra _
fr:liste $arrowRight mot _
de:Zahlen von _ bis _
ca:nombres des de _ a _
es:números de _ a _
fr:nombres de _ à _
1101de:wende _ an auf _
ca:mapeja _ sobre _
es:mapear _ sobre _
fr:appliquer _ à _
1Take any number of input lists, and create a new list containing the items of the input lists. So
APPEND [A B] [C D]
where the [,,,] are lists reports the list
[A B C D]
not [[A B] [C D]].11111Reports a new list containing the items of the input list, but in the opposite order.1inputresultReports a new list whose items are the same as in the input list, except that if two or more equal items appear in the input list, only the last one is kept in the result.1Reports a sorted version of the list in its first input slot, using the comparison function in the second input slot. For a list of numbers, using < as the comparison function will sort from low to high; using > will sort from high to low.1even itemsmerge11#1#2The second input is an "association list," a list of two-item lists. Each of those smaller lists has a "key" as its first item and a "value" as its second. ASSOC reports the first key-value pair in the association list whose key matches the first input.11#11datacountmapmany##1#1data listscount#1datacount1durationname
duration
length
number of channels
sample rate
samplessamplessoundvar base64, binaryString, len, bytes, i,
arrayBuffer, audioCtx;
if (sound.audioBuffer) {
return;
}
base64 = sound.audio.src.split(',')[1];
binaryString = window.atob(base64);
len = binaryString.length;
bytes = new Uint8Array(len);
for (i = 0; i < len; i += 1) {
bytes[i] = binaryString.charCodeAt(i);
}
arrayBuffer = bytes.buffer;
Note.prototype.setupContext();
audioCtx = Note.prototype.audioContext;
audioCtx.decodeAudioData(arrayBuffer, function(buffer) {
sound.audioBuffer = buffer;
});soundreturn !isNil(sound.audioBuffer);soundchoiceswitch (choice) {
case 'sample rate':
return sound.audioBuffer.sampleRate;
case 'duration':
return sound.audioBuffer.duration;
case 'length':
return sound.audioBuffer.length;
case 'number of channels':
return sound.audioBuffer.numberOfChannels;
default:
return sound.audioBuffer;
}play back a sound, a list of samples (single channel), or a list of lists (multiple channels) at the given sample rate.
for demo purposes this block also fast-plots the samples on the stage4410022.05 kHz=22050
44.1 kHz=44100
88.2 kHz=88200
96 kHz=96000samplesratevar audioCtx, channels, frameCount, arrayBuffer, i, source;
Note.prototype.setupContext();
audioCtx = Note.prototype.audioContext;
channels = (samples.at(1) instanceof List) ? samples.length() : 1;
frameCount = (channels === 1) ? samples.length() : samples.at(1).length();
arrayBuffer = audioCtx.createBuffer(channels, frameCount, rate);
if (!arrayBuffer.copyToChannel) {
arrayBuffer.copyToChannel = function (src, channel) {
var buffer = this.getChannelData(channel);
for (i = 0; i < src.length; i += 1) {
buffer[i] = src[i];
}
}
}
if (channels === 1) {
arrayBuffer.copyToChannel(Float32Array.from(samples.asArray()), 0, 0);
} else {
for (i = 0; i < channels; i += 1) {
arrayBuffer.copyToChannel(Float32Array.from(samples.at(i + 1).asArray()), i, 0);
}
}
source = audioCtx.createBufferSource();
source.buffer = arrayBuffer;
source.connect(audioCtx.destination);
source.start();
source.pause = source.stop;
this.parentThatIsA(StageMorph).activeSounds.push(source);generate a list of samples representing a sine wave at the given frequency, duration and sample rate440a 55=55
a 110=110
a 220=220
a 440=440
a 880=880
a 1760=1760
a 3520=352014410022.05 kHz=22050
44.1 kHz=44100
88.2 kHz=88200
96 kHz=96000quickly plot the samples of a sound, a list of samples (single channel), or a list of lists (multiple channels) to the stage at a lower resolution.1offset-2records an audio snippet and reports it as a new sound, or zero if the user cancelsca:volum del so
es:volumen del sonido
return typeof meter != 'undefined'return Math.floor(meter.volume * 100);reports a list of all pixels in the given costume. Each pixel is represented by a 4-item sublist of RGBA valuespixelsname
pixels
width
heightwidthheightcostume var i,
pixels = [],
src = costume.contents.getContext('2d').getImageData(
0,
0,
costume.width(),
costume.height()
);
for (i = 0; i < src.data.length; i += 4) {
pixels.push(new List([
src.data[i],
src.data[i + 1],
src.data[i + 2],
src.data[i + 3]
]));
}
return new List(pixels);overwrite the pixels in the given costume with another list of pixels.
Caution! This operation directly changes the costume. Make sure to use a copy in case you would like to revert changes later.reports the sprite's actual current costume, which may or may not be part of its wardrobe e.g. if it is a copyreports a copy of the given costume. This is especially useful when modifying a costume, so you can keep the original arounddisplay the given bitmap in a copy of the current costume (so you can switch back to the original costume again)takes a snapshot with the webcam and reports it as a new costume, or zero if the user cancels5010.51501linearlinear
quadratic={
quadratic-in
quadratic-out
quadratic-in-out
}
cubic={
cubic-in
cubic-out
cubic-in-out
}
quart={
quart-in
quart-out
quart-in-out
}
sinusoidal={
sine-in
sine-out
sine-in-out
}
elasticx positionx position
y position
direction
size501linearlinear
quadratic={
quadratic-in
quadratic-out
quadratic-in-out
}
cubic={
cubic-in
cubic-out
cubic-in-out
}
quart={
quart-in
quart-out
quart-in-out
}
sinusoidal={
sine-in
sine-out
sine-in-out
}
elasticgettergettergettergetterlinearlinear
quadratic={
quadratic-in
quadratic-out
quadratic-in-out
}
cubic={
cubic-in
cubic-out
cubic-in-out
}
quart={
quart-in
quart-out
quart-in-out
}
sinusoidal={
sine-in
sine-out
sine-in-out
}
elasticquadratic-inquadratic-outquadratic-in-outcubic-incubic-outcubic-in-outquart-inquart-outquart-in-outsine-insine-outsine-in-outelasticunknown easing function ""01001linearlinear
quadratic={
quadratic-in
quadratic-out
quadratic-in-out
}
cubic={
cubic-in
cubic-out
cubic-in-out
}
quart={
quart-in
quart-out
quart-in-out
}
sinusoidal={
sine-in
sine-out
sine-in-out
}
elastic50,0,0,0,0,0,00,0,0,0,0,0,00,0,0,0,0,0,00,0,0,0,0,0,00,0,0,0,0,0,00,0,0,0,0,0,01-480,0,0,1,2,10,0,0,1,0,0,00