Merge pull request matplotlib#961 from WeatherGod/issue-807-AutoMinorLocator

Issue 807 auto minor locator

Author: jdh2358

lib/matplotlib/ticker.py

@@ -1527,15 +1527,22 @@ def __call__(self):
         try:
             majorstep = majorlocs[1] - majorlocs[0]
         except IndexError:
-            raise ValueError('Need at least two major ticks to find minor '
-                             'tick locations')
+            # Need at least two major ticks to find minor tick locations
+            # TODO: Figure out a way to still be able to display minor
+            # ticks without two major ticks visible. For now, just display
+            # no ticks at all.
+            majorstep = 0
 
         if self.ndivs is None:
-            x = int(round(10 ** (np.log10(majorstep) % 1)))
-            if x in [1, 5, 10]:
-                ndivs = 5
-            else:
-                ndivs = 4
+            if majorstep == 0 :
+                # TODO: Need a better way to figure out ndivs
+                ndivs = 1
+            else :
+                x = int(round(10 ** (np.log10(majorstep) % 1)))
+                if x in [1, 5, 10]:
+                    ndivs = 5
+                else:
+                    ndivs = 4
         else:
             ndivs = self.ndivs
 
@@ -1545,12 +1552,15 @@ def __call__(self):
         if vmin > vmax:
             vmin,vmax = vmax,vmin
 
-        t0 = majorlocs[0]
-        tmin = np.ceil((vmin - t0) / minorstep) * minorstep
-        tmax = np.floor((vmax - t0) / minorstep) * minorstep
-        locs = np.arange(tmin, tmax, minorstep) + t0
-        cond = np.abs((locs - t0) % majorstep) > minorstep/10.0
-        locs = locs.compress(cond)
+        if len(majorlocs) > 0:
+            t0 = majorlocs[0]
+            tmin = np.ceil((vmin - t0) / minorstep) * minorstep
+            tmax = np.floor((vmax - t0) / minorstep) * minorstep
+            locs = np.arange(tmin, tmax, minorstep) + t0
+            cond = np.abs((locs - t0) % majorstep) > minorstep/10.0
+            locs = locs.compress(cond)
+        else:
+            locs = []
 
         return self.raise_if_exceeds(np.array(locs))