Destroyed building (windows, walls)

Patterns

Applicable neurons

• Plus (x + y)
• Destroyed building (windows)
• Cube - surface area
• Radians into degrees
• Can we fix it? (1/0)
• character <
• name into start tag
• constant x.xxxxx
• Connect - seven inputs
• min (from 2 values)
• HH:MM:SS + HH:MM:SS = ?
• Width of persons

Algorithm

Test

/**
 * 1: 
 *
 * @return {Array}
 */
function neuron501()
{
return [1];
}

/**
 * a = b: IF a=b THEN 1 ELSE 0;
 *
 * @param x1 a
 * @param x2 b
 * @return {Array}
 */
function neuron591(x1, x2)
{
return [(x1 == x2) ? 1 : 0];
}

/**
 * IF: IF a THEN b ELSE c;
 *
 * @param x1 condition (1/0)
 * @param x2 variable for 1
 * @param x3 variable for 0
 * @return {Array}
 */
function neuron579(x1, x2, x3)
{
return [(x1) ? x2 : x3];
}

/**
 * Destroyed building (windows): 
 * 
 * @param x1 Are windows defective? (1/0)
 * @param x2 Price of repair windows
 * @return {Array}
 */
function neuron598(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron501();
  outputs[2] = arr[0];

  arr = neuron591(outputs[2], outputs[0]);
  outputs[3] = arr[0];

  arr = neuron579(outputs[3], outputs[1], outputs[3]);
  outputs[4] = arr[0];

  return[outputs[4]];
}


/**
 * 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()];
}

/**
 * Destroyed building (windows, walls): 
 * 
 * @param x1 Are windows defective? (1/0)
 * @param x2 Price of repair windows
 * @param x3 Are walls defective? (1/0)
 * @param x4 Price of repair walls
 * @return {Array}
 */
function neuron599(x1, x2, x3, x4)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;
  outputs[3] = x4;

  arr = neuron598(outputs[2], outputs[3]);
  outputs[4] = arr[0];

  arr = neuron598(outputs[0], outputs[1]);
  outputs[5] = arr[0];

  arr = neuron1(outputs[4], outputs[5]);
  outputs[6] = arr[0];

  return[outputs[6]];
}