# Distance between two points (3d)

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

• 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

```/**
* 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]];
}

```