Calculate VAT

Patterns

Applicable neurons

• Plus (x + y)
• Minus (x - y)
• Multiple (x × y)
• Division (x ÷ y)
• 100
• square/rhombus - Perimeter
• equilateral polygon - Perimeter
• fileName from path
• disk from path
• Can we fix it? (1/0)
• (a, +∞)
• Surface area Of a Sphere
• Decimal part of a number
• character !
• character }
• Is it odd?
• HH:MM:SS + HH:MM:SS = ?
• character j
• Validate integer

Algorithm

Test

/**
 * 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()];
}

/**
 * Division (x ÷ y): X / Y
 *
 * @param x1 first number
 * @param x2 second number
 * @return {Array}
 */
function neuron17(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '/'+Number(x2)).toString()];
}

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

/**
 * 0: 
 *
 * @return {Array}
 */
function neuron500()
{
return [0];
}

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

/**
 * 100: 
 * 
 * @return {Array}
 */
function neuron537()
{
  var outputs = [];

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

  arr = neuron500();
  outputs[1] = arr[0];

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

  arr = neuron520(outputs[0], outputs[2]);
  outputs[3] = arr[0];

  return[outputs[3]];
}


/**
 * 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()];
}

/**
 * Calculate VAT: 
 * 
 * @param x1 Price without VAT
 * @param x2 Price with VAT
 * @return {Array}
 */
function neuron655(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron2(outputs[1], outputs[0]);
  outputs[2] = arr[0];

  arr = neuron17(outputs[2], outputs[0]);
  outputs[3] = arr[0];

  arr = neuron537();
  outputs[4] = arr[0];

  arr = neuron3(outputs[4], outputs[3]);
  outputs[5] = arr[0];

  return[outputs[5]];
}