matplotlib
diff --git a/‎doc/users/next_whats_new/logit_scale_stuff.rst
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diff --git a/‎examples/scales/logit_demo.py
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diff --git a/‎examples/scales/scales.py
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diff --git a/‎lib/matplotlib/scale.py
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@@ -0,0 +1,13 @@
+Improvements in Logit scale ticker and formatter
+------------------------------------------------
+
+Introduced in version 1.5, the logit scale didn't have an appropriate ticker and
+formatter. Previously, the location of ticks was not zoom dependent, too many labels
+were displayed causing overlapping which broke readability, and label formatting
+did not adapt to precision.
+
+Starting from this version, the logit locator has nearly the same behavior as the
+locator for the log scale or the linear
+scale, depending on used zoom. The number of ticks is controlled. Some minor
+labels are displayed adaptively as sublabels in log scale. Formatting is adapted
+for probabilities and the precision is adapts to the scale.
@@ -0,0 +1,61 @@
+"""
+================
+Logit Demo
+================
+
+Examples of plots with logit axes.
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+xmax = 10
+x = np.linspace(-xmax, xmax, 10000)
+cdf_norm = np.array([np.math.erf(w / np.sqrt(2)) / 2 + 1 / 2 for w in x])
+cdf_laplacian = np.array(
+    [1 / 2 * np.exp(w) if w < 0 else 1 - 1 / 2 * np.exp(-w) for w in x]
+)
+cdf_cauchy = 1 / np.pi * np.arctan(x) + 1 / 2
+
+fig, axs = plt.subplots(nrows=3, ncols=2, figsize=(6.4, 8.5))
+
+# Common part, for the example, we will do the same plots on all graphs
+for i in range(3):
+    for j in range(2):
+        axs[i, j].plot(x, cdf_norm, label=r"$\mathcal{N}$")
+        axs[i, j].plot(x, cdf_laplacian, label=r"$\mathcal{L}$")
+        axs[i, j].plot(x, cdf_cauchy, label="Cauchy")
+        axs[i, j].legend()
+        axs[i, j].grid()
+
+# First line, logitscale, with standard notation
+axs[0, 0].set(title="logit scale")
+axs[0, 0].set_yscale("logit")
+axs[0, 0].set_ylim(1e-5, 1 - 1e-5)
+
+axs[0, 1].set(title="logit scale")
+axs[0, 1].set_yscale("logit")
+axs[0, 1].set_xlim(0, xmax)
+axs[0, 1].set_ylim(0.8, 1 - 5e-3)
+
+# Second line, logitscale, with survival notation (with `use_overline`), and
+# other format display 1/2
+axs[1, 0].set(title="logit scale")
+axs[1, 0].set_yscale("logit", one_half="1/2", use_overline=True)
+axs[1, 0].set_ylim(1e-5, 1 - 1e-5)
+
+axs[1, 1].set(title="logit scale")
+axs[1, 1].set_yscale("logit", one_half="1/2", use_overline=True)
+axs[1, 1].set_xlim(0, xmax)
+axs[1, 1].set_ylim(0.8, 1 - 5e-3)
+
+# Third line, linear scale
+axs[2, 0].set(title="linear scale")
+axs[2, 0].set_ylim(0, 1)
+
+axs[2, 1].set(title="linear scale")
+axs[2, 1].set_xlim(0, xmax)
+axs[2, 1].set_ylim(0.8, 1)
+
+fig.tight_layout()
+plt.show()
@@ -55,9 +55,6 @@
 ax.set_yscale('logit')
 ax.set_title('logit')
 ax.grid(True)
-# Format the minor tick labels of the y-axis into empty strings with
-# `NullFormatter`, to avoid cumbering the axis with too many labels.
-ax.yaxis.set_minor_formatter(NullFormatter())
 
 
 # Function x**(1/2)
 
@@ -654,8 +654,15 @@ class LogitScale(ScaleBase):
     """
     name = 'logit'
 
-    def __init__(self, axis, nonpos='mask'):
-        """
+    def __init__(
+        self,
+        axis,
+        nonpos='mask',
+        *,
+        one_half=r"\frac{1}{2}",
+        use_overline=False,
+    ):
+        r"""
         Parameters
         ----------
         axis : `matplotlib.axis.Axis`
@@ -664,8 +671,15 @@ def __init__(self, axis, nonpos='mask'):
             Determines the behavior for values beyond the open interval ]0, 1[.
             They can either be masked as invalid, or clipped to a number very
             close to 0 or 1.
+        use_overline : bool, default: False
+            Indicate the usage of survival notation (\overline{x}) in place of
+            standard notation (1-x) for probability close to one.
+        one_half : str, default: r"\frac{1}{2}"
+            The string used for ticks formatter to represent 1/2.
         """
         self._transform = LogitTransform(nonpos)
+        self._use_overline = use_overline
+        self._one_half = one_half
 
     def get_transform(self):
         """Return the `.LogitTransform` associated with this scale."""
@@ -675,9 +689,20 @@ def set_default_locators_and_formatters(self, axis):
         # docstring inherited
         # ..., 0.01, 0.1, 0.5, 0.9, 0.99, ...
         axis.set_major_locator(LogitLocator())
-        axis.set_major_formatter(LogitFormatter())
+        axis.set_major_formatter(
+            LogitFormatter(
+                one_half=self._one_half,
+                use_overline=self._use_overline
+            )
+        )
         axis.set_minor_locator(LogitLocator(minor=True))
-        axis.set_minor_formatter(LogitFormatter())
+        axis.set_minor_formatter(
+            LogitFormatter(
+                minor=True,
+                one_half=self._one_half,
+                use_overline=self._use_overline
+            )
+        )
 
     def limit_range_for_scale(self, vmin, vmax, minpos):
         """