Quadratic equation (ax² + bx + c = 0)

Patterns

Applicable neurons

• Square root (√¯)
• discriminant b² - 4ac
• x / 2y
• -a + b; -a - b
• Rectangular cuboid - volume
• when sentence contains a, return b, else return c
• Get first word
• is x < 0 ?
• 0-9

Algorithm

Test

/**
 * 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]];
}


/**
 * 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]];
}


/**
 * 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()];
}

/**
 * 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()];
}

/**
 * x / 2y: 
 * 
 * @param x1 x
 * @param x2 y
 * @return {Array}
 */
function neuron715(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron1(outputs[1], outputs[1]);
  outputs[2] = arr[0];

  arr = neuron17(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()];
}

/**
 * 4: 
 *
 * @return {Array}
 */
function neuron504()
{
return [4];
}

/**
 * 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()];
}

/**
 * discriminant b² - 4ac: 
 * 
 * @param x1 a
 * @param x2 b
 * @param x3 c
 * @return {Array}
 */
function neuron602(x1, x2, x3)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;

  arr = neuron3(outputs[1], outputs[1]);
  outputs[3] = arr[0];

  arr = neuron3(outputs[0], outputs[2]);
  outputs[4] = arr[0];

  arr = neuron504();
  outputs[5] = arr[0];

  arr = neuron504();
  outputs[6] = arr[0];

  arr = neuron3(outputs[4], outputs[6]);
  outputs[7] = arr[0];

  arr = neuron2(outputs[3], outputs[7]);
  outputs[8] = arr[0];

  return[outputs[8]];
}


/**
 * 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()];
}

/**
 * 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()];
}

/**
 * a + b; a - b: 
 * 
 * @param x1 a
 * @param x2 b
 * @return {Array}
 */
function neuron717(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron1(outputs[1], outputs[0]);
  outputs[2] = arr[0];

  arr = neuron2(outputs[0], outputs[1]);
  outputs[3] = arr[0];

  return[outputs[2], outputs[3]];
}


/**
 * character -: 
 *
 * @return {Array}
 */
function neuron511()
{
return['-'];
}

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

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

/**
 * -1: 
 * 
 * @return {Array}
 */
function neuron574()
{
  var outputs = [];

  arr = neuron511();
  outputs[0] = arr[0];

  arr = neuron501();
  outputs[1] = arr[0];

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

/**
 * x × (-1): 
 * 
 * @param x1 x
 * @return {Array}
 */
function neuron710(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron574();
  outputs[1] = arr[0];

  arr = neuron3(outputs[0], outputs[1]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * -a + b; -a - b: 
 * 
 * @param x1 a
 * @param x2 b
 * @return {Array}
 */
function neuron798(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron717(outputs[1], outputs[0]);
  outputs[2] = arr[0];

;   outputs[3] = arr[1];

  arr = neuron710(outputs[2]);
  outputs[4] = arr[0];

  return[outputs[3], outputs[4]];
}


/**
 * Quadratic equation (ax² + bx + c = 0): 
 * 
 * @param x1 a
 * @param x2 b
 * @param x3 c
 * @return {Array}
 */
function neuron575(x1, x2, x3)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;

  arr = neuron554(outputs[1]);
  outputs[3] = arr[0];

  arr = neuron715(outputs[1], outputs[0]);
  outputs[4] = arr[0];

  arr = neuron715(outputs[4], outputs[1]);
  outputs[5] = arr[0];

  arr = neuron602(outputs[5], outputs[4], outputs[2]);
  outputs[6] = arr[0];

  arr = neuron798(outputs[5], outputs[4]);
  outputs[7] = arr[0];

;   outputs[8] = arr[1];

  arr = neuron602(outputs[4], outputs[7], outputs[1]);
  outputs[9] = arr[0];

  arr = neuron715(outputs[7], outputs[7]);
  outputs[10] = arr[0];

  arr = neuron554(outputs[6]);
  outputs[11] = arr[0];

  arr = neuron554(outputs[6]);
  outputs[12] = arr[0];

  arr = neuron554(outputs[6]);
  outputs[13] = arr[0];

  arr = neuron798(outputs[4], outputs[13]);
  outputs[14] = arr[0];

;   outputs[15] = arr[1];

  return[outputs[15], outputs[14]];
}