Distance between two points (3d)

Inputs

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

Outputs

  • Distance

Neuron type

Best algorithm has been found - locked

Patterns

Pattern Input Output
1.
Point A: xa: 7
Point A: ya: 4
Point A: za: 3
Point B: xb: 10
Point B: yb: 8
Point B: zb: 3
Distance: 5
2.
Point A: xa: -5
Point A: ya: -8
Point A: za: 9
Point B: xb: -1
Point B: yb: -8
Point B: zb: 12
Distance: 5
3.
Point A: xa: -20
Point A: ya: -50
Point A: za: -20
Point B: xb: -20
Point B: yb: -10
Point B: zb: -50
Distance: 50

Applicable neurons

  • Minus (x - y)
  • √¯(a² + b² + c²)
  • ax + b = 0
  • right angled triangle, find Hypotenuse c, given a, b
  • Connect - two words (with space)
  • [a, b]
  • [a, +∞)
  • before decimal point

Algorithm

Test

Code made by AI:
/**
 * Minus (x - y): 
 *
 * @param x1 Number X
 * @param x2 Number Y
 * @return {Array}
 */
function neuron2(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '-'+Number(x2)).toString()];
}

/**
 * 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()];
}

/**
 * x to the 2 (x²): x squared
 * 
 * @param x1 Number X
 * @return {Array}
 */
function neuron7(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron3(outputs[0], outputs[0]);
  outputs[1] = arr[0];

  return[outputs[1]];
}


/**
 * 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()];
}

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

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

/**
 * 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 = neuron510();
  outputs[0] = arr[0];

  arr = neuron505();
  outputs[1] = arr[0];

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

  return[outputs[2]];
}


/**
 * x to the a  (xª): value of the number x to be the power of a
 *
 * @param x1 x - The base
 * @param x2 a - The exponent
 * @return {Array}
 */
function neuron18(x1, x2)
{
return[Math.pow(Number(x1), Number(x2))];
}

/**
 * Square root (√¯): 
 * 
 * @param x1 Number X
 * @return {Array}
 */
function neuron554(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron522();
  outputs[1] = arr[0];

  arr = neuron18(outputs[0], outputs[1]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * √¯(a² + b² + c²): 
 * 
 * @param x1 a
 * @param x2 b
 * @param x3 c
 * @return {Array}
 */
function neuron709(x1, x2, x3)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;

  arr = neuron7(outputs[2]);
  outputs[3] = arr[0];

  arr = neuron7(outputs[1]);
  outputs[4] = arr[0];

  arr = neuron7(outputs[0]);
  outputs[5] = arr[0];

  arr = neuron1(outputs[4], outputs[3]);
  outputs[6] = arr[0];

  arr = neuron1(outputs[5], outputs[6]);
  outputs[7] = arr[0];

  arr = neuron554(outputs[7]);
  outputs[8] = arr[0];

  return[outputs[8]];
}


/**
 * Distance between two points (3d): 
 * 
 * @param x1 Point A: xa
 * @param x2 Point A: ya
 * @param x3 Point A: za
 * @param x4 Point B: xb
 * @param x5 Point B: yb
 * @param x6 Point B: zb
 * @return {Array}
 */
function neuron657(x1, x2, x3, x4, x5, x6)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;
  outputs[3] = x4;
  outputs[4] = x5;
  outputs[5] = x6;

  arr = neuron2(outputs[3], outputs[0]);
  outputs[6] = arr[0];

  arr = neuron2(outputs[2], outputs[5]);
  outputs[7] = arr[0];

  arr = neuron2(outputs[1], outputs[4]);
  outputs[8] = arr[0];

  arr = neuron709(outputs[6], outputs[8], outputs[7]);
  outputs[9] = arr[0];

  return[outputs[9]];
}


Code made by AI:

Create your family tree for free