public auto statFunction(FUNC, T)(
    FUNC func, 
    T min, 
    T max, 
    size_t precision = 50) 
if(isCallable!FUNC)

Create Aes based on a function

Parameters

func	Function
min	x coordinate to start from
max	x coordinate to end at
precision	Number of points to calculate

Examples

    /// http://blackedder.github.io/ggplotd/images/function.png
    import std.random : uniform;
    import std.typecons : Tuple; import ggplotd.stat : statFunction; 
    import ggplotd.ggplotd : GGPlotD; 
    import ggplotd.geom : geomLine, geomPoint;
    import ggplotd.range : mergeRange;

    auto f = (double x) { return x / (1 + x); };

    auto aes = statFunction(f, 0.0, 10);
    auto gg = GGPlotD().put(geomLine(aes));

    // Generate some noisy points 
    auto f2 = (double x) { return x / (1 + x) * uniform(0.75, 1.25); };
    auto aes2 = f2.statFunction(0.0, 10, 25);

    // Show points in different colour
    auto withColour = Tuple!(string, "colour")("aquamarine").mergeRange(aes2);
    gg = gg.put(withColour.geomPoint);

    gg.save("function.png");
 

private auto binID(T)(
    T value, 
    T min, 
    T max, 
    T width)

Binning

public auto statHist(AES)(
    AES aesRaw, 
    size_t noBins = 0)

Create Aes that specifies the bins to draw an histogram

Parameters

aesRaw	Data that the histogram will be based on
noBins	Optional number of bins. On a value of 0 the number of bins will be chosen automatically.

Returns

Range that holds rectangles representing different bins

public auto statHist2D(AES)(
    AES aesRange, 
    size_t noBinsX = 0, 
    size_t noBinsY = 0)

Create Aes that specifies the bins to draw an histogram

Parameters

aesRange	Data that the histogram will be based on
noBinsX	Optional number of bins for x axis. On a value of 0 the number of bins will be chosen automatically.
noBinsY	Optional number of bins for y axis. On a value of 0 the number of bins will be chosen automatically.

Returns

Range that holds rectangles representing different bins

public auto statDensity(AES)(AES aesRange)

Calculate kernel density for given data

Parameters

aesRange

Data that the histogram will be based on

Returns

InputRange that holds x and y coordinates for the kernel

Example

import std.stdio : writeln;
import std.algorithm : map;
import std.array : array;
import std.random : uniform;
import std.range : chain, iota, repeat, walkLength;

import ggplotd.aes : Aes;

auto xs = iota(0,100,1)
    .map!((i)=>uniform(0,0.75)+uniform(0.25,1))
    .array;

auto dens = statDensity( Aes!( typeof(xs), "x")( xs ) );
auto dim = dens.walkLength;
assertGreaterThan( dim, 1 );

// Test that grouping leads to longer (twice as long) result
auto cols = chain("a".repeat(50),"b".repeat(50) );
auto dens2 = statDensity( Aes!(typeof(cols), "colour", typeof(xs), "x")( cols, xs ) );
assertGreaterThan( dens2.walkLength, 1.9*dim );
assertLessThan( dens2.walkLength, 2.1*dim );

// Test that colour is passed through (merged)
assertEqual( dens2.front.colour.length, 1 );

// Test single point 
xs = [1];
dens = statDensity( Aes!( typeof(xs), "x")( xs ) );
assertEqual(dens.walkLength, 3);

public auto statDensity2D(AES)(AES aesRange)

Calculate kernel density for given x and y data

Parameters

aesRange

Data that the histogram will be based on

Returns

Range of ranges that holds polygons for the kernel

Example

import std.algorithm : map;
import std.array : array;
import std.random : uniform;
import std.range : iota, walkLength;

import ggplotd.aes : Aes;
auto xs = iota(0,500,1).map!((x) => uniform(0.0,5)+uniform(0.0,5))
    .array;
auto ys = iota(0,500,1).map!((y) => uniform(1.0,1.5)+uniform(1.0,1.5))
    .array;
auto aes = Aes!(typeof(xs), "x", typeof(ys), "y")( xs, ys);

auto sD = statDensity2D( aes );
assertGreaterThan( sD.walkLength, 1150 );
assertLessThan( sD.walkLength, 1450 );
assertEqual( sD.front.walkLength, 3 );

// One value
xs = [1];
ys = [2];
aes = Aes!(typeof(xs), "x", typeof(ys), "y")( xs, ys);

sD = statDensity2D( aes );
assertGreaterThan(sD.walkLength, 0);