I tried to make a similar algorithm to … by katkip

function u(t) {

c.width=1920 // clear the canvas
for(i=0;i<9;i++)
x.fillRect(400+i*100+S(t)*300,400,50,200) // draw 50x200 rects

} // 122/140

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    u(t) is called 60 times per second.
    t: Elapsed time in seconds.
    S: Shorthand for Math.sin.
    C: Shorthand for Math.cos.
    T: Shorthand for Math.tan.
    R: Function that generates rgba-strings, usage ex.: R(255, 255, 255, 0.5)
    c: A 1920x1080 canvas.
    x: A 2D context for that canvas.

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katkip

function u(t) {

eval(unescape(escape`稽䵡瑨⹲慮摯活楦⠡琩筘㵛崬夽孝ⱑ㴰ⱗ㴰㭦潲⡩㴱〻椭ⴻ⥘⹰畳栨稨⤪㤶〩ⱙ⹰畳栨稨⤪㤶〩㭦潲⡰⁩渠堩儫㵘孰崬圫㵙孰崬砮晩汬剥捴⡘孰崬奛灝ⰹⰹ⤻砮浯癥呯⠰ⰰ⤻砮汩湥呯⡑⼵ⱗ⼵⥽砮獴牯步⠩`.replace(/u(..)/g,"$1%")))

Dec 8 2018 7:54 PM UTC

}// 138/140

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I tried to make a similar algorithm to the linear regression algorithm! Machine learning #ai prediction inside dwitter! If you think this doesn't deserve an awesome, search on google what is linear regression ;) I couldn't golf all the formulas so I used the mean calculus. z=Math.random;if(!t){X=[],Y=[],Q=0,W=0;for(i=10;i--;)X.push(z()*960),Y.push(z()*960);for(p in X)Q+=X[p],W+=Y[p],x.fillRect(X[p],Y[p],9,9);x.moveTo(0,0);x.lineTo(Q/5,W/5)}x.stroke()


      u(t) is called 60 times per second.
      t: elapsed time in seconds.
      c: A 1920x1080 canvas.
      x: A 2D context for that canvas.
      S: Math.sin
      C: Math.cos
      T: Math.tan
      R: Generates rgba-strings, ex.: R(255, 255, 255, 0.5)

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