WIP: added symmetrical norm

phobson · phobson · commit 2d4166415ef6 · 2014-11-27T15:37:59.000-08:00
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -225,6 +225,7 @@ def rgb2hex(rgb):
     a = '#%02x%02x%02x' % tuple([int(np.round(val * 255)) for val in rgb[:3]])
     return a
 
+
 hexColorPattern = re.compile("\A#[a-fA-F0-9]{6}\Z")
 
 
@@ -1043,6 +1044,14 @@ def inverse(self, value):
             return inverted[0]
 
 
+class SymmetricalNorm(Normalize):
+    def __init__(self, vmin=None, vmax=None, clip=False):
+        limit = np.max(np.abs([vmin, vmax]))
+        self.vmin = limit * -1
+        self.vmax = limit
+        self.clip = clip
+
+
 class LogNorm(Normalize):
     """
     Normalize a given value to the 0-1 range on a log scale
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -101,13 +101,21 @@ def setup(self):
         self.vals = np.array([-1, -0.5, 0.0, 1.0, 2.0, 3.0, 4.0])
         self.expected = np.array([0.0, 0.25, 0.5, 0.625, 0.75, 0.875, 1.0])
 
+
 class test_OffsetNorm_Even(_base_NormMixin):
     def setup(self):
         self.norm = mcolors.OffsetNorm(vmin=-2, vcenter=0, vmax=5)
         self.vals = np.array([-2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0])
         self.expected = np.array([0.0, 0.25, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0])
 
 
+class test_SymmetricalNorm(_base_NormMixin):
+    def setup(self):
+        self.norm = mcolors.SymmetricalNorm(vmin=-2, vmax=4)
+        self.vals = np.array([-2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0])
+        self.expected = np.array([0.25, 0.375, 0.5, 0.625, 0.75, 0.875, 1.0])
+
+
 def test_SymLogNorm():
     """
     Test SymLogNorm behavior
