DOC: Add contour finding example.

doc/examples/plot_contours.py

@@ -0,0 +1,44 @@
+"""
+===============
+Contour finding
+===============
+
+``skimage.measure.find_contours`` uses a marching squares method to
+find constant valued contours in an image.  Array values are linearly
+interpolated to provide better precision of the output contours.
+Contours which intersect the image edge are open; all others
+are closed.
+
+The `marching squares algorithm
+<http://www.essi.fr/~lingrand/MarchingCubes/algo.html>`__ is a special
+case of the marching cubes algorithm (Lorensen, William and Harvey
+E. Cline. Marching Cubes: A High Resolution 3D Surface Construction
+Algorithm. Computer Graphics (SIGGRAPH 87 Proceedings) 21(4) July
+1987, p. 163-170).
+
+"""
+
+from skimage import data
+from skimage import measure
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Construct some test data
+x, y = np.ogrid[-np.pi:np.pi:100j, -np.pi:np.pi:100j]
+r = np.sin(np.exp((np.sin(x)**3 + np.cos(y)**2)))
+
+# Find contours at a constant value of 0.8
+contours = measure.find_contours(r, 0.8)
+
+# Display the image and plot all contours found
+plt.imshow(r, interpolation='nearest')
+
+for n, contour in enumerate(contours):
+    plt.plot(contour[:, 1], contour[:, 0], linewidth=2)
+
+plt.axis('image')
+plt.xticks([])
+plt.yticks([])
+plt.show()
+