TST: add test for re-normalizing image

jklymak · jklymak · commit 294ff2df5da6 · 2018-09-19T10:50:57.000-07:00
diff --git a/lib/matplotlib/tests/test_colorbar.py b/lib/matplotlib/tests/test_colorbar.py
@@ -7,6 +7,8 @@
 from matplotlib.colors import BoundaryNorm, LogNorm, PowerNorm
 from matplotlib.cm import get_cmap
 from matplotlib.colorbar import ColorbarBase
+from matplotlib.ticker import LogLocator, LogFormatter
+
 
 
 def _get_cmap_norms():
@@ -396,3 +398,28 @@ def test_colorbar_axes_kw():
     plt.imshow(([[1, 2], [3, 4]]))
     plt.colorbar(orientation='horizontal', fraction=0.2, pad=0.2, shrink=0.5,
                  aspect=10, anchor=(0., 0.), panchor=(0., 1.))
+
+
+def test_colorbar_renorm():
+    x,y = np.ogrid[-4:4:31j,-4:4:31j]
+    z = 120000*np.exp(-x**2-y**2)
+
+    fig, ax = plt.subplots()
+
+    im = ax.imshow(z)
+    cbar = fig.colorbar(im)
+
+    norm = LogNorm(z.min(), z.max())
+    im.set_norm(norm)
+    cbar.set_norm(norm)
+    cbar.locator = LogLocator()
+    cbar.formatter = LogFormatter()
+    cbar.update_normal(im)
+    assert np.isclose(cbar.vmin, z.min())
+
+    norm = LogNorm(z.min() * 1000, z.max() * 1000)
+    im.set_norm(norm)
+    cbar.set_norm(norm)
+    cbar.update_normal(im)
+    assert np.isclose(cbar.vmin, z.min() * 1000)
+    assert np.isclose(cbar.vmax, z.max() * 1000)
