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

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

@@ -0,0 +1,40 @@
+#!/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)