added image 'csv-2d-multivariate-distributions'

tikz/csv-2d-gaussian-multivarate-distributions/Makefile

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+SOURCE = csv-2d-gaussian-multivarate-distributions
+DELAY = 80
+DENSITY = 300
+WIDTH = 512
+
+make:
+	pdflatex $(SOURCE).tex -output-format=pdf
+	make clean
+
+clean:
+	rm -rf  $(TARGET) *.class *.html *.log *.aux *.data *.gnuplot
+
+gif:
+	pdfcrop $(SOURCE).pdf
+	convert -verbose -delay $(DELAY) -loop 0 -density $(DENSITY) $(SOURCE)-crop.pdf $(SOURCE).gif
+	make clean
+
+png:
+	make
+	make svg
+	inkscape $(SOURCE).svg -w $(WIDTH) --export-png=$(SOURCE).png
+
+transparentGif:
+	convert $(SOURCE).pdf -transparent white result.gif
+	make clean
+
+svg:
+	make
+	#inkscape $(SOURCE).pdf --export-plain-svg=$(SOURCE).svg
+	pdf2svg $(SOURCE).pdf $(SOURCE).svg
+	# Necessary, as pdf2svg does not always create valid svgs:
+	inkscape $(SOURCE).svg --export-plain-svg=$(SOURCE).svg
+	rsvg-convert -a -w $(WIDTH) -f svg $(SOURCE).svg -o $(SOURCE)2.svg
+	inkscape $(SOURCE)2.svg --export-plain-svg=$(SOURCE).svg
+	rm $(SOURCE)2.svg

tikz/csv-2d-gaussian-multivarate-distributions/README.md

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+Compiled example
+----------------
+![Example](csv-2d-gaussian-multivarate-distributions.png)

tikz/csv-2d-gaussian-multivarate-distributions/csv-2d-gaussian-multivarate-distributions.tex

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+\documentclass[varwidth=true, border=5pt]{article}
+\usepackage[active,tightpage]{preview}
+\usepackage[latin1]{inputenc}
+\usepackage{amsmath}
+\usepackage{pgfplots}
+\pgfplotsset{compat=1.10}
+\usepackage{tikz}
+\usetikzlibrary{arrows,positioning} 
+\usepackage{helvet}
+\usepackage[eulergreek]{sansmath}
+
+\begin{document}
+\begin{preview}
+\begin{tikzpicture}
+    \begin{axis}[
+        width=13.4cm,
+        height=10.0cm,
+        % Grid
+        grid = major,
+        % size
+        xmin= 40,     % start the diagram at this x-coordinate
+        xmax= 90,   % end   the diagram at this x-coordinate
+        ymin= 0,     % start the diagram at this y-coordinate
+        ymax= 60, % end   the diagram at this y-coordinate
+        % Legende
+        legend style={
+            font=\large\sansmath\sffamily,
+            at={(0.5,-0.18)},
+            anchor=north,
+            legend cell align=left,
+            legend columns=-1,
+            column sep=0.5cm
+        },
+        % Ticks
+        tick align=inside,
+        every axis/.append style={font=\large\sansmath\sffamily},
+        minor tick style={thick},
+        scaled y ticks = false,
+        % Axis
+        axis line style = {very thick,shorten <=-0.5\pgflinewidth},
+        axis lines = middle,
+        axis line style = very thick,
+        xlabel=Gesamtausgaben,
+        x label style={at={(axis description cs:0.5,-0.05)},
+                       anchor=north,
+                       font=\boldmath\sansmath\sffamily\Large},
+        ylabel=Luxusausgaben,
+        y label style={at={(axis description cs:-0.05,0.5)},
+                       anchor=south,
+                       rotate=90,
+                       font=\boldmath\sansmath\sffamily\Large},
+        ]
+\addplot[
+scatter,
+only marks,
+point meta=explicit symbolic,
+scatter/classes={
+a={mark=x,red!90!black},%
+b={mark=x,cyan!50!black}},
+]
+table[col sep=comma, meta=label] {data.csv};
+
+\addplot[
+scatter,
+only marks,
+point meta=explicit symbolic,
+scatter/classes={
+b={mark=*,mark size=3pt,red!30!white,draw=black},%
+c={mark=*,mark size=3pt,cyan!30!white,draw=black},%
+a={mark=*,mark size=3pt,green!70!black,draw=black}},
+]
+table[meta=label] {
+    x   y   label
+    65  35  a
+    70  40  b
+    60  20  c
+};
+% \addlegendentry{Gruppe 1}
+% \addlegendentry{Gruppe 2}
+\end{axis}
+\end{tikzpicture}
+\end{preview}
+\end{document}

tikz/csv-2d-gaussian-multivarate-distributions/multivariate-random.py

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+#!/usr/bin/env python
+
+import matplotlib.pyplot as plt
+import numpy
+import csv
+
+cov = [[25, 20], [20, 25]]  # diagonal covariance, points lie on x or y-axis
+
+meanI = [70, 40]
+datapointsI = 2000
+
+meanII = [60, 20]
+datapointsII = 2000
+
+dataI = numpy.random.multivariate_normal(meanI, cov, datapointsI).T
+x, y = dataI
+plt.plot(x, y, 'x')
+
+dataII = numpy.random.multivariate_normal(meanII, cov, datapointsII).T
+x, y = dataII
+plt.plot(x, y, 'x')
+
+plt.axis('equal')
+plt.show()
+
+data = []
+xs, ys = dataI
+for x, y in zip(xs, ys):
+    data.append([x, y, 'a'])
+xs, ys = dataII
+for x, y in zip(xs, ys):
+    data.append([x, y, 'b'])
+
+# Write data to csv files
+with open("data.csv", 'wb') as csvfile:
+    csvfile.write("x,y,label\n")
+    spamwriter = csv.writer(csvfile, delimiter=',',
+                            quotechar='"', quoting=csv.QUOTE_MINIMAL)
+    for datapoint in data:
+        spamwriter.writerow(datapoint)