matplotlib · Kojoley · Feb 16, 2020 · Feb 10, 2020 · Feb 16, 2020 · Feb 16, 2020
diff --git a/doc/api/next_api_changes/behaviour.rst b/doc/api/next_api_changes/behaviour.rst
@@ -85,3 +85,11 @@ Previously, rcParams entries whose values were color-like accepted "spurious"
 extra letters or characters in the "middle" of the string, e.g. ``"(0, 1a, '0.5')"``
 would be interpreted as ``(0, 1, 0.5)``.  These extra characters (including the
 internal quotes) now cause a ValueError to be raised.
+
+`.SymLogNorm` now has a *base* parameter
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Previously, `.SymLogNorm` had no *base* kwarg, and defaulted to ``base=np.e``
+whereas the documentation said it was ``base=10``.  In preparation to make
+the default 10, calling `.SymLogNorm` without the new *base* kwarg emits a
+deprecation warning.
diff --git a/examples/userdemo/colormap_normalizations.py b/examples/userdemo/colormap_normalizations.py
@@ -69,7 +69,7 @@
 
 pcm = ax[0].pcolormesh(X, Y, Z1,
                        norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
-                                              vmin=-1.0, vmax=1.0),
+                                              vmin=-1.0, vmax=1.0, base=10),
                        cmap='RdBu_r')
 fig.colorbar(pcm, ax=ax[0], extend='both')
 

diff --git a/examples/userdemo/colormap_normalizations_symlognorm.py b/examples/userdemo/colormap_normalizations_symlognorm.py
@@ -29,7 +29,7 @@
 
 pcm = ax[0].pcolormesh(X, Y, Z,
                        norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
-                                              vmin=-1.0, vmax=1.0),
+                                              vmin=-1.0, vmax=1.0, base=10),
                        cmap='RdBu_r')
 fig.colorbar(pcm, ax=ax[0], extend='both')
 

diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -1202,8 +1202,8 @@ class SymLogNorm(Normalize):
     *linthresh* allows the user to specify the size of this range
     (-*linthresh*, *linthresh*).
     """
-    def __init__(self, linthresh, linscale=1.0,
-                 vmin=None, vmax=None, clip=False):
+    def __init__(self, linthresh, linscale=1.0, vmin=None, vmax=None,
+                 clip=False, *, base=None):
         """
         Parameters
         ----------
@@ -1213,14 +1213,29 @@ def __init__(self, linthresh, linscale=1.0,
         linscale : float, default: 1
             This allows the linear range (-*linthresh* to *linthresh*) to be
             stretched relative to the logarithmic range. Its value is the
-            number of decades to use for each half of the linear range. For
-            example, when *linscale* == 1.0 (the default), the space used for
-            the positive and negative halves of the linear range will be equal
-            to one decade in the logarithmic range.
+            number of powers of *base* (decades for base 10) to use for each
+            half of the linear range. For example, when *linscale* == 1.0
+            (the default), the space used for the positive and negative halves
+            of the linear range will be equal to a decade in the logarithmic
+            range if ``base=10``.
+        base : float, default: None
+            For v3.2 the default is the old value of ``np.e``, but that is
+            deprecated for v3.3 when base will default to 10.  During the
+            transition, specify the *base* kwarg to avoid a deprecation
+            warning.
         """
         Normalize.__init__(self, vmin, vmax, clip)
+        if base is None:
+            self._base = np.e
+            cbook.warn_deprecated("3.3", message="default base will change "
+                "from np.e to 10.  To suppress this warning specify the base "
+                "kwarg.")
+        else:
+            self._base = base
+        self._log_base = np.log(self._base)
+
         self.linthresh = float(linthresh)
-        self._linscale_adj = (linscale / (1.0 - np.e ** -1))
+        self._linscale_adj = (linscale / (1.0 - self._base ** -1))
         if vmin is not None and vmax is not None:
             self._transform_vmin_vmax()
 
@@ -1255,7 +1270,8 @@ def _transform(self, a):
         with np.errstate(invalid="ignore"):
             masked = np.abs(a) > self.linthresh
         sign = np.sign(a[masked])
-        log = (self._linscale_adj + np.log(np.abs(a[masked]) / self.linthresh))
+        log = (self._linscale_adj +
+               np.log(np.abs(a[masked]) / self.linthresh) / self._log_base)
         log *= sign * self.linthresh
         a[masked] = log
         a[~masked] *= self._linscale_adj
@@ -1265,7 +1281,8 @@ def _inv_transform(self, a):
         """Inverse inplace Transformation."""
         masked = np.abs(a) > (self.linthresh * self._linscale_adj)
         sign = np.sign(a[masked])
-        exp = np.exp(sign * a[masked] / self.linthresh - self._linscale_adj)
+        exp = np.power(self._base,
+                       sign * a[masked] / self.linthresh - self._linscale_adj)
         exp *= sign * self.linthresh
         a[masked] = exp
         a[~masked] /= self._linscale_adj

diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -398,7 +398,7 @@ def test_SymLogNorm():
     """
     Test SymLogNorm behavior
     """
-    norm = mcolors.SymLogNorm(3, vmax=5, linscale=1.2)
+    norm = mcolors.SymLogNorm(3, vmax=5, linscale=1.2, base=np.e)
     vals = np.array([-30, -1, 2, 6], dtype=float)
     normed_vals = norm(vals)
     expected = [0., 0.53980074, 0.826991, 1.02758204]
@@ -408,16 +408,30 @@ def test_SymLogNorm():
     _mask_tester(norm, vals)
 
     # Ensure that specifying vmin returns the same result as above
-    norm = mcolors.SymLogNorm(3, vmin=-30, vmax=5, linscale=1.2)
+    norm = mcolors.SymLogNorm(3, vmin=-30, vmax=5, linscale=1.2, base=np.e)
     normed_vals = norm(vals)
     assert_array_almost_equal(normed_vals, expected)
 
+    # test something more easily checked.
+    norm = mcolors.SymLogNorm(1, vmin=-np.e**3, vmax=np.e**3, base=np.e)
+    nn = norm([-np.e**3, -np.e**2, -np.e**1, -1,
+              0, 1, np.e**1, np.e**2, np.e**3])
+    xx = np.array([0., 0.109123, 0.218246, 0.32737, 0.5, 0.67263,
+                   0.781754, 0.890877, 1.])
+    assert_array_almost_equal(nn, xx)
+    norm = mcolors.SymLogNorm(1, vmin=-10**3, vmax=10**3, base=10)
+    nn = norm([-10**3, -10**2, -10**1, -1,
+              0, 1, 10**1, 10**2, 10**3])
+    xx = np.array([0., 0.121622, 0.243243, 0.364865, 0.5, 0.635135,
+                   0.756757, 0.878378, 1.])
+    assert_array_almost_equal(nn, xx)
+
 
 def test_SymLogNorm_colorbar():
     """
     Test un-called SymLogNorm in a colorbar.
     """
-    norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1)
+    norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1, base=np.e)
     fig = plt.figure()
     mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
     plt.close(fig)
@@ -428,7 +442,7 @@ def test_SymLogNorm_single_zero():
     Test SymLogNorm to ensure it is not adding sub-ticks to zero label
     """
     fig = plt.figure()
-    norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1)
+    norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1, base=np.e)
     cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
     ticks = cbar.get_ticks()
     assert sum(ticks == 0) == 1
@@ -905,9 +919,10 @@ def __add__(self, other):
     mydata = data.view(MyArray)
 
     for norm in [mcolors.Normalize(), mcolors.LogNorm(),
-                 mcolors.SymLogNorm(3, vmax=5, linscale=1),
+                 mcolors.SymLogNorm(3, vmax=5, linscale=1, base=np.e),
                  mcolors.Normalize(vmin=mydata.min(), vmax=mydata.max()),
-                 mcolors.SymLogNorm(3, vmin=mydata.min(), vmax=mydata.max()),
+                 mcolors.SymLogNorm(3, vmin=mydata.min(), vmax=mydata.max(),
+                                    base=np.e),
                  mcolors.PowerNorm(1)]:
         assert_array_equal(norm(mydata), norm(data))
         fig, ax = plt.subplots()

diff --git a/tutorials/colors/colormapnorms.py b/tutorials/colors/colormapnorms.py
@@ -98,7 +98,7 @@
 
 pcm = ax[0].pcolormesh(X, Y, Z,
                        norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
-                                              vmin=-1.0, vmax=1.0),
+                                              vmin=-1.0, vmax=1.0, base=10),
                        cmap='RdBu_r')
 fig.colorbar(pcm, ax=ax[0], extend='both')