Visualize the relationship of a coinâ€™s bias to its entropy with this code snippet.

Imports and implicits:

``````import scala.collection.immutable.TreeMap
import cats.implicits._
import spire.math.Rational
import axle._
import axle.stats._
import axle.quanta.Information
import axle.quanta.UnittedQuantity

type D = TreeMap[Rational, UnittedQuantity[Information, Double]]

import spire.implicits.DoubleAlgebra
import axle.jung.directedGraphJung
import edu.uci.ics.jung.graph.DirectedSparseGraph
import axle.quanta.UnitOfMeasurement

implicit val id = Information.converterGraphK2[Double, DirectedSparseGraph]

import axle.stats.H
import axle.stats.coin
``````

Create dataset

``````val hm: D = new TreeMap[Rational, UnittedQuantity[Information, Double]]() ++ (0 to 100).map(i => (Rational(i / 100d), H(coin(Rational(i.toLong, 100))))).toMap
// hm: D = Map(0 -> UnittedQuantity(0.0,UnitOfMeasurement(bit,b,None)), 5764607523034235/576460752303423488 -> UnittedQuantity(0.08079313589591118,UnitOfMeasurement(bit,b,None)), 5764607523034235/288230376151711744 -> UnittedQuantity(0.14144054254182067,UnitOfMeasurement(bit,b,None)), 1080863910568919/36028797018963968 -> UnittedQuantity(0.19439185783157623,UnitOfMeasurement(bit,b,None)), 5764607523034235/144115188075855872 -> UnittedQuantity(0.24229218908241482,UnitOfMeasurement(bit,b,None)), 3602879701896397/72057594037927936 -> UnittedQuantity(0.28639695711595625,UnitOfMeasurement(bit,b,None)), 1080863910568919/18014398509481984 -> UnittedQuantity(0.32744491915447627,UnitOfMeasurement(bit,b,None)), 1261007895663739/18014398509481984 -> UnittedQuantity(0.36592365090022316,UnitOfMeasureme...
``````

Define visualization

``````import axle.visualize._
// import axle.visualize._

implicit val bitDouble = id.bit
// bitDouble: axle.quanta.UnitOfMeasurement[axle.quanta.Information] = UnitOfMeasurement(bit,b,None)

implicit val ut = axle.quanta.unittedTicsGraphK2[Information, Double, DirectedSparseGraph]
// ut: axle.algebra.Tics[axle.quanta.UnittedQuantity[axle.quanta.Information,Double]] = axle.quanta.package\$\$anon\$6@44ff2478

val plot = Plot[String, Rational, UnittedQuantity[Information, Double], D](
() => List(("h", hm)),
connect = true,
drawKey = false,
colorOf = _ => Color.black,
xAxis = Some(0d *: bitDouble),
yAxis = Some(Rational(0)),
yAxisLabel = Some("H"),
title = Some("Entropy"))
// plot: axle.visualize.Plot[String,spire.math.Rational,axle.quanta.UnittedQuantity[axle.quanta.Information,Double],D] = Plot(<function0>,true,false,700,600,50,4,20,50,80,Courier New,12,false,Palatino,20,<function1>,Some(Entropy),None,Some(UnittedQuantity(0.0,UnitOfMeasurement(bit,b,None))),Some(p(x='HEAD)),Some(0),Some(H))
``````

Create the SVG

``````import axle.web._
// import axle.web._

svg(plot, "coinentropy.svg")
``````

The result is the classic Claude Shannon graph