Inputs
Outputs
Neuron type
Best algorithm has been found - locked
Patterns
Pattern |
Input |
Output |
1. |
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2. |
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3. |
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Applicable neurons
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Multiple (x × y)
-
Division (x ÷ y)
-
3
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Pi (π) - 3.141592653589793
-
Rounding to whole ten thousands of something
-
Rectangle - perimeter
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ext from path
-
Rounding to whole ten thousands of something
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character n
-
convert seconds into hours, minutes and seconds
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Time to deadline
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Check if a string ends with a specified string
Algorithm
Test
Code made by AI:
/**
* 3:
*
* @return {Array}
*/
function neuron503()
{
return [3];
}
/**
* Pi (π) - 3.141592653589793:
*
* @return {Array}
*/
function neuron560()
{
math.config({number: 'BigNumber', precision: 64}); return[math.PI]; /* return [3.141592653589793] */
}
/**
* 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()];
}
/**
* 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()];
}
/**
* 0:
*
* @return {Array}
*/
function neuron500()
{
return [0];
}
/**
* 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()];
}
/**
* Connect - four inputs:
*
* @param x1 string A
* @param x2 string B
* @param x3 string C
* @param x4 string D
* @return {Array}
*/
function neuron565(x1, x2, x3, x4)
{
var outputs = [];
outputs[0] = x1;
outputs[1] = x2;
outputs[2] = x3;
outputs[3] = x4;
arr = neuron520(outputs[2], outputs[3]);
outputs[4] = arr[0];
arr = neuron520(outputs[1], outputs[4]);
outputs[5] = arr[0];
arr = neuron520(outputs[0], outputs[5]);
outputs[6] = arr[0];
return[outputs[6]];
}
/**
* Connect - two inputs:
*
* @param x1 Variable A
* @param x2 Variable B
* @return {Array}
*/
function neuron520(x1, x2)
{
return [x1.toString()+x2.toString()];
}
/**
* Connect - five inputs:
*
* @param x1 1
* @param x2 2
* @param x3 3
* @param x4 4
* @param x5 5
* @return {Array}
*/
function neuron651(x1, x2, x3, x4, x5)
{
var outputs = [];
outputs[0] = x1;
outputs[1] = x2;
outputs[2] = x3;
outputs[3] = x4;
outputs[4] = x5;
arr = neuron565(outputs[1], outputs[2], outputs[3], outputs[4]);
outputs[5] = arr[0];
arr = neuron520(outputs[0], outputs[5]);
outputs[6] = arr[0];
return[outputs[6]];
}
/**
* 10000:
*
* @return {Array}
*/
function neuron706()
{
var outputs = [];
arr = neuron500();
outputs[0] = arr[0];
arr = neuron501();
outputs[1] = arr[0];
arr = neuron651(outputs[1], outputs[0], outputs[0], outputs[0], outputs[0]);
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()];
}
/**
* Round to an integer: round(x)
*
* @param x1 Value
* @return {Array}
*/
function neuron620(x1)
{
return[Math.round(Number(x1))]
}
/**
* 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()];
}
/**
* Rounding to whole ten thousands of something:
*
* @param x1 Value
* @return {Array}
*/
function neuron705(x1)
{
var outputs = [];
outputs[0] = x1;
arr = neuron706();
outputs[1] = arr[0];
arr = neuron3(outputs[1], outputs[0]);
outputs[2] = arr[0];
arr = neuron620(outputs[2]);
outputs[3] = arr[0];
arr = neuron17(outputs[3], outputs[1]);
outputs[4] = arr[0];
return[outputs[4]];
}
/**
* Volume Of a Cone:
*
* @param x1 Radius
* @param x2 Height
* @return {Array}
*/
function neuron540(x1, x2)
{
var outputs = [];
outputs[0] = x1;
outputs[1] = x2;
arr = neuron503();
outputs[2] = arr[0];
arr = neuron560();
outputs[3] = arr[0];
arr = neuron3(outputs[0], outputs[0]);
outputs[4] = arr[0];
arr = neuron3(outputs[4], outputs[1]);
outputs[5] = arr[0];
arr = neuron3(outputs[3], outputs[5]);
outputs[6] = arr[0];
arr = neuron17(outputs[6], outputs[2]);
outputs[7] = arr[0];
arr = neuron705(outputs[7]);
outputs[8] = arr[0];
return[outputs[8]];
}
Code made by AI: