Midpoint (2d)

Inputs

  • Point A: xa
  • Point A: ya
  • Point B: xb
  • Point B: yb

Outputs

  • Midpoint C: xc
  • Midpoint C: yc

Neuron type

Best algorithm has been found - locked

Patterns

Pattern Input Output
1.
Point A: xa: 2
Point A: ya: 1
Point B: xb: 3
Point B: yb: 5
Midpoint C: xc: 2.5
Midpoint C: yc: 3
2.
Point A: xa: 4
Point A: ya: 6
Point B: xb: 8
Point B: yb: 10
Midpoint C: xc: 6
Midpoint C: yc: 8
3.
Point A: xa: -4
Point A: ya: 9
Point B: xb: 3
Point B: yb: -1
Midpoint C: xc: -0.5
Midpoint C: yc: 4

Applicable neurons

  • Plus (x + y)
  • Multiple (x × y)
  • Half (0.5)
  • Get first letter
  • >, < opposite

Algorithm

Test

Code made by AI:
/**
 * Plus (x + y): The addition of two whole numbers is the total amount of those quantities combined.
 *
 * @param x1 first number
 * @param x2 second number
 * @return {Array}
 */
function neuron1(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '+'+Number(x2)).toString()];
}

/**
 * 5: 
 *
 * @return {Array}
 */
function neuron505()
{
return [5];
}

/**
 * character .: 
 *
 * @return {Array}
 */
function neuron510()
{
return['.'];
}

/**
 * Connect - two inputs: 
 *
 * @param x1 Variable A
 * @param x2 Variable B
 * @return {Array}
 */
function neuron520(x1, x2)
{
return [x1.toString()+x2.toString()];
}

/**
 * Half (0.5): 
 * 
 * @return {Array}
 */
function neuron522()
{
  var outputs = [];

  arr = neuron505();
  outputs[0] = arr[0];

  arr = neuron510();
  outputs[1] = arr[0];

  arr = neuron520(outputs[1], outputs[0]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * Multiple (x × y): 
 *
 * @param x1 Number X
 * @param x2 Number Y
 * @return {Array}
 */
function neuron3(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '*'+Number(x2)).toString()];
}

/**
 * Midpoint (2d): 
 * 
 * @param x1 Point A: xa
 * @param x2 Point A: ya
 * @param x3 Point B: xb
 * @param x4 Point B: yb
 * @return {Array}
 */
function neuron659(x1, x2, x3, x4)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;
  outputs[3] = x4;

  arr = neuron1(outputs[3], outputs[1]);
  outputs[4] = arr[0];

  arr = neuron522();
  outputs[5] = arr[0];

  arr = neuron1(outputs[2], outputs[0]);
  outputs[6] = arr[0];

  arr = neuron3(outputs[4], outputs[5]);
  outputs[7] = arr[0];

  arr = neuron3(outputs[6], outputs[5]);
  outputs[8] = arr[0];

  return[outputs[8], outputs[7]];
}


Code made by AI:

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