# Percentage (X% / 100)

## Inputs

• Number in percentage

## Outputs

• percentage / 100

## Neuron type

Best algorithm has been found - locked

## Patterns

Pattern Input Output
1.
 Number in percentage: 50
 percentage / 100: 0.5
2.
 Number in percentage: 100
 percentage / 100: 1
3.
 Number in percentage: 25
 percentage / 100: 0.25

## Applicable neurons

• Multiple (x × y)
• Division (x ÷ y)
• 100

## Algorithm

### Test

```/**
* 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]];
}

/**
* 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()];
}

/**
* Percentage (X% / 100):
*
* @param x1 Number in percentage
* @return {Array}
*/
function neuron536(x1)
{
var outputs = [];
outputs[0] = x1;

arr = neuron537();
outputs[1] = arr[0];

arr = neuron17(outputs[0], outputs[1]);
outputs[2] = arr[0];

return[outputs[2]];
}

```