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1.1
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2
.gitignore
vendored
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2
.gitignore
vendored
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@ -0,0 +1,2 @@
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benfords-law
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benfords-law.exe
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@ -27,5 +27,5 @@ $ ./benfords-law.exe
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Press 'Enter' to continue...
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```
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This shows that Benford's law only works when the data is not random, such as natural data gathered in real life. This is because natural data is generated following a [power law](https://en.wikipedia.org/wiki/Power_law), which is common in nature.
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This shows that Benford's law only works when the data is not random, such as natural data gathered in real life. This is because for data which Benford's law does work, it's natural data generated following a [power law](https://en.wikipedia.org/wiki/Power_law), which is quite common in nature.
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36
main.go
36
main.go
@ -7,25 +7,26 @@ import (
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"math"
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"math/rand"
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"os"
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"runtime"
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"time"
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)
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const (
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randomMin = 0
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randomMax = 9999999999999999
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numSamples = 10000000
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randomMin = 1 // We specify a range which random numbers will be generated, we must start at the first possible left-most digit
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randomMax = 999999999999999999 // int64 max value is 9223372036854775807. We use one digit less than that with all 9's in order to not give bias to any digits.
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numSamples = 100000000 // A nice rounded human number
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)
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func main() {
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results := [9]int{} // There are 9 possible leading digits and 0 does not count, offset by 1 for index to actual value. Examples: To access 1 use [0]. To access 5 use [4]. To access 9 use [8].
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currentSample := 0
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// In results, we store a count of each left most leading digits as numbers are randomly genereated
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results := [9]int{} // There are 9 possible leading digits and 0 does not count, offset by 1 for index to actual value. Examples: To access count for 1 use [0]. To access 5 use [4]. To access 9 use [8].
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currentSample := 0 // A counter that increments each time a random number sample has been generated. Used for status messages
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// Start a little goroutine to output status and attach a ticker to execute it each second
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statusTicker := time.NewTicker(time.Second)
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go func() {
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for {
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<-statusTicker.C
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<-statusTicker.C // Wait for heartbeat from ticker channel
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percentCompleted := (currentSample * 100) / numSamples
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log.Printf("%d%% completed generating and analyzing samples", percentCompleted)
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}
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@ -34,33 +35,24 @@ func main() {
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log.Printf("generating numbers...")
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rand.Seed(time.Now().UnixNano())
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generatedNumbers := make(chan int, 1024)
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for i := 0; i < runtime.NumCPU(); i++ {
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go generatorWorker(generatedNumbers)
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}
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for currentSample = 0; currentSample < numSamples; currentSample++ {
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results[firstDigit(<-generatedNumbers)-1]++
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results[firstDigit(rand.Intn(randomMax-randomMin+1)+randomMin)-1]++ // Generate a random number between randomMin and randomMax, get the first digit then increment the counter in results array, remember, it's offset by 1
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}
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// Done generating and counting digits, stop the status ticker
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statusTicker.Stop()
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log.Printf("done.")
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// output results
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for digitMinusOne, count := range results {
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fmt.Printf("%d: %d (%f%%)\n", digitMinusOne+1, count, float64(count*100)/float64(numSamples))
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// Output results
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for digitMinusOne, digitCount := range results {
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fmt.Printf("%d: %d (%f%%)\n", digitMinusOne+1, digitCount, float64(digitCount*100)/float64(numSamples))
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}
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// Wait indefinitely until Enter Key is pressed, avoid terminating terminal before viewing results if ran from a shell
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fmt.Print("Press 'Enter' to continue...")
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bufio.NewReader(os.Stdin).ReadBytes('\n')
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}
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func generatorWorker(returnChannel chan int) {
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for {
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returnChannel <- rand.Intn(randomMax-randomMin+1) + randomMin // We must use Intn instead of Int because from Base10's perspective, integers cut off at a really weird spot
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}
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}
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// firstDigit returns the first/leftmost digit of the base10 representation of an integer
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func firstDigit(x int) int {
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return int(math.Abs(float64(x)) / math.Pow(10, float64(numDigits(x)-1)))
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