Visualize

Visualize

This package is part of the Axle domain specific language.

The show function is available in the axle.visualize._ package. It can be applied to several types of Axle objects. That package also contains functions for creating files from the images: png, jpeg, gif, bmp.

For example:

show(plot)
png(plot, "plot.png")

XY Plots

axle.visualize.Plot

  import util.Random
  import collection._
  import math.{ Pi, cos, sin }
  import axle.visualize._
  import axle.visualize.Plottable._
  import org.joda.time.DateTime

  val now = new DateTime()

  def randomTimeSeries(i: Int) = {
    val (phase, amp, f) = (Random.nextDouble, Random.nextDouble, Random.nextDouble)
    ("series %d %1.2f %1.2f %1.2f".format(i, phase, amp, f),
      new immutable.TreeMap[DateTime, Double]() ++
      (0 to 100).map(j => (now.plusMinutes(2 * j) -> amp * sin(phase + (j / (10 * f))))).toMap)
  }

  val plot = new Plot((0 until 20).map(i => randomTimeSeries(i)).toList, true,
    title = Some("Random Waves"), xAxis = 0.0, xAxisLabel = Some("time (t)"),
    yAxis = now, yAxisLabel = Some("a * sin(p + t/10f)"))

  show(plot)

Bar Charts

import axle.visualize._
import collection._

val fruits = Vector("apple", "banana", "coconut")

val years = Vector(2011, 2012)

val sales = Map(
  ("apple", 2011) -> 43.0,
  ("apple", 2012) -> 83.8,
  ("banana", 2011) -> 11.3,
  ("banana", 2012) -> 77.9,
  ("coconut", 2011) -> 88.0,
  ("coconut", 2012) -> 10.1
)

val chart = BarChart(
  fruits,
  years,
  (fruit: String, year: Int) => sales((fruit, year)),
  xAxis = 0.0,
  title = Some("fruit sales")
)

show(chart)

Scatter Plots

TODO: show example of 2-feature KMeans clustering

Graph

TODO: show directed and undirected graph visualizations