BUGFIX: This change fixes #2475, where contour labels added manually

lib/matplotlib/contour.py

@@ -562,26 +562,38 @@ def add_label_near(self, x, y, inline=True, inline_spacing=5,
           exact for labels at locations where the contour is
           straight, less so for labels on curved contours.
         """
-
+        # if 'do the default thing' use the axes data transform
         if transform is None:
             transform = self.ax.transData
 
+        # if transform is 'falsey' don't do any transform (this is a
+        # really awful API but is what we have)
         if transform:
+            # The point of this transform is to get the location
+            # of label position into screen units
             x, y = transform.transform_point((x, y))
 
+        # find the nearest contour _in screen units_
         conmin, segmin, imin, xmin, ymin = self.find_nearest_contour(
             x, y, self.labelIndiceList)[:5]
 
         # The calc_label_rot_and_inline routine requires that (xmin,ymin)
         # be a vertex in the path. So, if it isn't, add a vertex here
+
+        # grab the paths from the collections
         paths = self.collections[conmin].get_paths()
-        lc = paths[segmin].vertices
-        if transform:
-            xcmin = transform.inverted().transform([xmin, ymin])
-        else:
-            xcmin = np.array([xmin, ymin])
+        # grab the correct segment
+        active_path = paths[segmin]
+        # grab it's verticies
+        lc = active_path.vertices
+        # sort out where the new vertex should be added in the path's data
+        # units
+        xcmin = self.ax.transData.inverted().transform_point([xmin, ymin])
+        # if there isn't a vertex close enough
         if not np.allclose(xcmin, lc[imin]):
+            # insert new data into the vertex list
             lc = np.r_[lc[:imin], np.array(xcmin)[None, :], lc[imin:]]
+            # replace the path with the new one
             paths[segmin] = mpath.Path(lc)
 
         # Get index of nearest level in subset of levels used for labeling

lib/matplotlib/tests/test_contour.py

@@ -1,5 +1,5 @@
 import numpy as np
-
+from matplotlib import mlab
 from matplotlib.testing.decorators import cleanup, image_comparison
 from matplotlib import pyplot as plt
 
@@ -183,6 +183,34 @@ def test_given_colors_levels_and_extends():
         plt.colorbar()
 
 
+@image_comparison(baseline_images=['contour_test_label_transforms'],
+                  extensions=['png'], remove_text=True)
+def test_labels():
+    # Adapted from pylab_examples example code: contour_demo.py
+    # see issues #2475, #2843, and #2818 for explanation
+    delta = 0.025
+    x = np.arange(-3.0, 3.0, delta)
+    y = np.arange(-2.0, 2.0, delta)
+    X, Y = np.meshgrid(x, y)
+    Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
+    Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
+    # difference of Gaussians
+    Z = 10.0 * (Z2 - Z1)
+
+    fig, ax = plt.subplots(1, 1)
+    CS = ax.contour(X, Y, Z)
+    disp_units = [(216, 177), (359, 290), (521, 406)]
+    data_units = [(-2, .5), (0, -1.5), (2.8, 1)]
+
+    CS.clabel()
+
+    for x, y in data_units:
+        CS.add_label_near(x, y, inline=True, transform=None)
+
+    for x, y in disp_units:
+        CS.add_label_near(x, y, inline=True, transform=False)
+
+
 if __name__ == '__main__':
     import nose
     nose.runmodule(argv=['-s', '--with-doctest'], exit=False)