Add density plots (see #1)

Author: ruivieira

README.md

@@ -2,11 +2,11 @@
 
 A Nim wrapper for matplotlib.
 
-# Features
+## Features
 
 * Line plots
 * Scatter plots
-* Histograms
+* Histograms (and KDE denisty plots)
 * Line segments
 * Axis (horizontal and vertical) lines
 * Font customisation
@@ -16,14 +16,14 @@ A Nim wrapper for matplotlib.
 * Horizontal and vertical limits
 * Custom markers
 
-# Examples
+## Examples
 
 Examples can be found [here](docs/README.md).
 
-# Contributing
+## Contributing
 
- * Fork it (https://github.com/ruivieira/matplotnim)
- * Create your feature branch (`git checkout -b my-new-feature`)
- * Commit your changes (`git commit -am 'Add some feature'`)
- * Push to the branch (`git push origin my-new-feature`)
- * Create a new Pull Request
+* Fork it (https://github.com/ruivieira/matplotnim)
+* Create your feature branch (`git checkout -b my-new-feature`)
+* Commit your changes (`git commit -am 'Add some feature'`)
+* Push to the branch (`git push origin my-new-feature`)
+* Create a new Pull Request

docs/README.md

@@ -57,6 +57,19 @@ figure3.save "docs/hist_bins.png"
 
 ![](hist_bins.png)
 
+You can also create KDE density plots.
+For instance:
+
+```nim
+let x = rnorm(1000, 0.0, 2.0)
+let figure = newFigure()
+let dp = newDensity(x)
+figure.add dp
+figure.save("docs/density.png")
+```
+
+![](density1.png)
+
 ### line segments
 
 With default values:

docs/density1.png

@@ -57,6 +57,7 @@ proc save*(figure: Figure, dest: string) =
   let script_str = script.join("\n")
   # get the temporary file
   var (file, name) = mkstemp(suffix = ".py")
+  echo name
   writeFile(name, script_str)
   echo name
   discard execShellCmd fmt"/usr/local/bin/python3 {name}"
@@ -146,6 +147,32 @@ method render[A](this: Histogram[A]): string =
 proc newHistogram*[A](x: seq[A]): Histogram[A] =
   Histogram[A](bins: 0,  x: x)
 
+type Density[A] = ref object of Plot
+  x*:seq[A]
+  steps*: int
+method render[A](this: Density[A]): string =
+  let xs = makeList(this.x)
+
+  var s: seq[string] = @[]
+  s.add("from scipy import stats")
+  s.add("import numpy as np")
+  s.add(fmt"_data = {xs}")
+  let x_max = foldr(this.x, max(a, b))
+  let x_min = foldr(this.x, min(a, b))
+  
+  let steps = abs(x_max - x_min) / float(this.steps)
+  s.add("_density = stats.kde.gaussian_kde(_data)")
+  echo fmt"x_max = {x_max}, x_min = {x_min}, steps = {steps}"
+  s.add(fmt"_x = np.arange({x_min}, {x_max}, {steps})")
+
+  s.add("plt.plot(_x, _density(_x))")
+
+  return s.join("\n")
+
+proc newDensity*[A](x: seq[A]): Density[A] =
+  Density[A](steps: 100,  x: x)
+  
+
 # Line segments
 type Line[A,B] = ref object of Plot
   p0*: tuple[x: A, y: B]