Merge pull request matplotlib#8322 from dstansby/min-exponent

ENH: Use scalars below a certain exponent in labes of log-scales axis

Author: tacaswell

doc/users/whats_new/min_log_scale_exponent.rst

@@ -0,0 +1,5 @@
+Specify minimum value to format as scalar for ``LogFormatterMathtext``
+----------------------------------------------------------------------
+
+``LogFormatterMathtext`` now includes the option to specify a minimum value
+exponent to format as a scalar (ie. 0.001 instead of 10^-3).

lib/matplotlib/rcsetup.py

@@ -1164,6 +1164,7 @@ def _validate_linestyle(ls):
     'axes.formatter.use_locale': [False, validate_bool],
                                # Use the current locale to format ticks
     'axes.formatter.use_mathtext': [False, validate_bool],
+    'axes.formatter.min_exponent': [0, validate_int],  # minimum exponent to format in scientific notation
     'axes.formatter.useoffset': [True, validate_bool],
     'axes.formatter.offset_threshold': [4, validate_int],
     'axes.unicode_minus': [True, validate_bool],

lib/matplotlib/tests/test_ticker.py

@@ -282,6 +282,26 @@ def test_blank(self):
         assert formatter(10**0.1) == ''
 
 
+class TestLogFormatterMathtext():
+    fmt = mticker.LogFormatterMathtext()
+    test_data = [
+        (0, 1, '$\\mathdefault{10^{0}}$'),
+        (0, 1e-2, '$\\mathdefault{10^{-2}}$'),
+        (0, 1e2, '$\\mathdefault{10^{2}}$'),
+        (3, 1, '$\\mathdefault{1}$'),
+        (3, 1e-2, '$\\mathdefault{0.01}$'),
+        (3, 1e2, '$\\mathdefault{100}$'),
+        (3, 1e-3, '$\\mathdefault{10^{-3}}$'),
+        (3, 1e3, '$\\mathdefault{10^{3}}$'),
+    ]
+
+    @pytest.mark.parametrize('min_exponent, value, expected', test_data)
+    def test_min_exponent(self, min_exponent, value, expected):
+        with matplotlib.rc_context({'axes.formatter.min_exponent':
+                                    min_exponent}):
+            assert self.fmt(value) == expected
+
+
 class TestLogFormatterSciNotation(object):
     test_data = [
         (2, 0.03125, '$\\mathdefault{2^{-5}}$'),

lib/matplotlib/ticker.py

@@ -1075,7 +1075,7 @@ def _non_decade_format(self, sign_string, base, fx, usetex):
             return (r'$%s%s^{%.2f}$') % (sign_string, base, fx)
         else:
             return ('$%s$' % _mathdefault('%s%s^{%.2f}' %
-                (sign_string, base, fx)))
+                                          (sign_string, base, fx)))
 
     def __call__(self, x, pos=None):
         """
@@ -1084,6 +1084,8 @@ def __call__(self, x, pos=None):
         The position `pos` is ignored.
         """
         usetex = rcParams['text.usetex']
+        min_exp = rcParams['axes.formatter.min_exponent']
+
         if x == 0:  # Symlog
             if usetex:
                 return '$0$'
@@ -1099,6 +1101,8 @@ def __call__(self, x, pos=None):
         is_x_decade = is_close_to_int(fx)
         exponent = np.round(fx) if is_x_decade else np.floor(fx)
         coeff = np.round(x / b ** exponent)
+        if is_x_decade:
+            fx = nearest_long(fx)
 
         if self.labelOnlyBase and not is_x_decade:
             return ''
@@ -1111,7 +1115,13 @@ def __call__(self, x, pos=None):
         else:
             base = '%s' % b
 
-        if not is_x_decade:
+        if np.abs(fx) < min_exp:
+            if usetex:
+                return r'${0}{1:g}$'.format(sign_string, x)
+            else:
+                return '${0}$'.format(_mathdefault(
+                    '{0}{1:g}'.format(sign_string, x)))
+        elif not is_x_decade:
             return self._non_decade_format(sign_string, base, fx, usetex)
         else:
             if usetex:

matplotlibrc.template

@@ -315,6 +315,7 @@ backend      : $TEMPLATE_BACKEND
                                    # separator in the fr_FR locale.
 #axes.formatter.use_mathtext : False # When True, use mathtext for scientific
                                      # notation.
+#axes.formatter.min_exponent: 0 # minimum exponent to format in scientific notation
 #axes.formatter.useoffset      : True    # If True, the tick label formatter
                                          # will default to labeling ticks relative
                                          # to an offset when the data range is