matplotlib · thoo · Sep 18, 2018 · Sep 19, 2018 · Oct 16, 2018 · Oct 17, 2018
diff --git a/.flake8 b/.flake8
@@ -81,7 +81,7 @@ per-file-ignores =
     tutorials/introductory/images.py: E402, E501
     tutorials/introductory/pyplot.py: E402, E501
     tutorials/introductory/sample_plots.py: E501
-    tutorials/introductory/usage.py: E402, E501
+    tutorials/introductory/usage.py: E501
     tutorials/text/annotations.py: E501
     tutorials/text/pgf.py: E501
     tutorials/text/text_intro.py: E402

diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -6778,8 +6778,8 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
             return tops, bins, cbook.silent_list('Lists of Patches', patches)
 
     @_preprocess_data(replace_names=["x", "y", "weights"], label_namer=None)
-    def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
-               cmin=None, cmax=None, **kwargs):
+    def hist2d(self, x, y, bins=10, range=None, density=None, weights=None,
+               cmin=None, cmax=None, normed=None, **kwargs):
         """
         Make a 2D histogram plot.
 
@@ -6812,8 +6812,15 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
              xmax], [ymin, ymax]]``. All values outside of this range will be
              considered outliers and not tallied in the histogram.
 
-        normed : bool, optional, default: False
-             Normalize histogram.
+        density : boolean, optional
+             If False, the default, returns the number of samples in each bin.
+             If True, returns the probability *density* function at the bin,
+             ``bin_count / sample_count / bin_area``.
+
+             Default is ``None`` for both *normed* and *density*. If either is
+             set, then that value will be used. If neither are set, then the
+             args will be treated as ``False``.
+             If both *density* and *normed* are set an error is raised.
 
         weights : array_like, shape (n, ), optional, default: None
             An array of values w_i weighing each sample (x_i, y_i).
@@ -6828,6 +6835,9 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
              to none before passing to imshow) and these count values in the
              return value count histogram will also be set to nan upon return
 
+        normed : bool, optional, default: None
+             Deprecated; use the density keyword argument instead.
+
         Returns
         -------
         h : 2D array
@@ -6870,7 +6880,15 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
           in effect to gamma correction) can be accomplished with
           `.colors.PowerNorm`.
         """
+        if density is not None and normed is not None:
+            raise ValueError("kwargs 'density' and 'normed' cannot be used "
+                             "simultaneously. Please only use 'density', "
+                             "since 'normed' is deprecated.")
+        if normed is not None:
+            cbook.warn_deprecated("2.1", name="'normed'", obj_type="kwarg",
+                                  alternative="'density'", removal="3.1")
 
+        normed = bool(density) or bool(normed)
         h, xedges, yedges = np.histogram2d(x, y, bins=bins, range=range,
                                            normed=normed, weights=weights)
 

diff --git a/lib/matplotlib/axes/_base.py b/lib/matplotlib/axes/_base.py
@@ -2403,14 +2403,16 @@ def autoscale_view(self, tight=None, scalex=True, scaley=True):
         if tight is not None:
             self._tight = bool(tight)
 
-        if self.use_sticky_edges and (self._xmargin or self._ymargin):
+        if self.use_sticky_edges and (
+                (self._xmargin and scalex and self._autoscaleXon) or
+                (self._ymargin and scaley and self._autoscaleYon)):
             stickies = [artist.sticky_edges for artist in self.get_children()]
-            x_stickies = sum([sticky.x for sticky in stickies], [])
-            y_stickies = sum([sticky.y for sticky in stickies], [])
+            x_stickies = np.array([x for sticky in stickies for x in sticky.x])
+            y_stickies = np.array([y for sticky in stickies for y in sticky.y])
             if self.get_xscale().lower() == 'log':
-                x_stickies = [xs for xs in x_stickies if xs > 0]
+                x_stickies = x_stickies[x_stickies > 0]
             if self.get_yscale().lower() == 'log':
-                y_stickies = [ys for ys in y_stickies if ys > 0]
+                y_stickies = y_stickies[y_stickies > 0]
         else:  # Small optimization.
             x_stickies, y_stickies = [], []
 

diff --git a/lib/matplotlib/colorbar.py b/lib/matplotlib/colorbar.py
@@ -240,7 +240,8 @@ def tick_values(self, vmin, vmax):
         vmin = max(vmin, self._colorbar.norm.vmin)
         vmax = min(vmax, self._colorbar.norm.vmax)
         ticks = super().tick_values(vmin, vmax)
-        return ticks[(ticks >= vmin) & (ticks <= vmax)]
+        rtol = (vmax - vmin) * 1e-10
+        return ticks[(ticks >= vmin - rtol) & (ticks <= vmax + rtol)]
 
 
 class _ColorbarAutoMinorLocator(ticker.AutoMinorLocator):
@@ -296,7 +297,10 @@ def tick_values(self, vmin, vmax):
         vmin = self._colorbar.norm.vmin
         vmax = self._colorbar.norm.vmax
         ticks = super().tick_values(vmin, vmax)
-        return ticks[(ticks >= vmin) & (ticks <= vmax)]
+        rtol = (np.log10(vmax) - np.log10(vmin)) * 1e-10
+        ticks = ticks[(np.log10(ticks) >= np.log10(vmin) - rtol) &
+              (np.log10(ticks) <= np.log10(vmax) + rtol)]
+        return ticks
 
 
 class ColorbarBase(cm.ScalarMappable):
@@ -405,7 +409,6 @@ def __init__(self, ax, cmap=None,
         else:
             self.formatter = format  # Assume it is a Formatter
         # The rest is in a method so we can recalculate when clim changes.
-        self.config_axis()
         self.draw_all()
 
     def _extend_lower(self):
@@ -439,6 +442,7 @@ def draw_all(self):
         # units:
         X, Y = self._mesh()
         C = self._values[:, np.newaxis]
+        self.config_axis()
         self._config_axes(X, Y)
         if self.filled:
             self._add_solids(X, Y, C)
@@ -593,6 +597,7 @@ def _config_axes(self, X, Y):
         ax.set_frame_on(False)
         ax.set_navigate(False)
         xy = self._outline(X, Y)
+        ax.ignore_existing_data_limits = True
         ax.update_datalim(xy)
         ax.set_xlim(*ax.dataLim.intervalx)
         ax.set_ylim(*ax.dataLim.intervaly)
@@ -1150,7 +1155,6 @@ def update_bruteforce(self, mappable):
         self.set_alpha(mappable.get_alpha())
         self.cmap = mappable.cmap
         self.norm = mappable.norm
-        self.config_axis()
         self.draw_all()
         if isinstance(self.mappable, contour.ContourSet):
             CS = self.mappable

diff --git a/lib/matplotlib/figure.py b/lib/matplotlib/figure.py
@@ -685,11 +685,11 @@ def suptitle(self, t, **kwargs):
             The y location of the text in figure coordinates.
 
         horizontalalignment, ha : {'center', 'left', right'}, default: 'center'
-            The horizontal alignment of the text.
+            The horizontal alignment of the text relative to (*x*, *y*).
 
         verticalalignment, va : {'top', 'center', 'bottom', 'baseline'}, \
 default: 'top'
-            The vertical alignment of the text.
+            The vertical alignment of the text relative to (*x*, *y*).
 
         fontsize, size : default: :rc:`figure.titlesize`
             The font size of the text. See `.Text.set_size` for possible

diff --git a/lib/matplotlib/pyplot.py b/lib/matplotlib/pyplot.py
@@ -2379,8 +2379,8 @@ def angle_spectrum(
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.annotate)
-def annotate(s, xy, *args, **kwargs):
-    return gca().annotate(s, xy, *args, **kwargs)
+def annotate(*args, **kwargs):
+    return gca().annotate(*args, **kwargs)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@@ -2427,12 +2427,10 @@ def axvspan(xmin, xmax, ymin=0, ymax=1, **kwargs):
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.bar)
-def bar(
-        x, height, width=0.8, bottom=None, *, align='center',
-        data=None, **kwargs):
+def bar(*args, data=None, **kwargs):
     return gca().bar(
-        x, height, width=width, bottom=bottom, align=align,
-        **({"data": data} if data is not None else {}), **kwargs)
+        *args, **({"data": data} if data is not None else {}),
+        **kwargs)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@@ -2444,9 +2442,8 @@ def barbs(*args, data=None, **kw):
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.barh)
-def barh(y, width, height=0.8, left=None, *, align='center', **kwargs):
-    return gca().barh(
-        y, width, height=height, left=left, align=align, **kwargs)
+def barh(*args, **kwargs):
+    return gca().barh(*args, **kwargs)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@@ -2710,8 +2707,8 @@ def magnitude_spectrum(
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.margins)
-def margins(*margins, x=None, y=None, tight=True):
-    return gca().margins(*margins, x=x, y=y, tight=tight)
+def margins(*args, **kw):
+    return gca().margins(*args, **kw)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@@ -2728,27 +2725,20 @@ def minorticks_on():
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @_autogen_docstring(Axes.pcolor)
-def pcolor(
-        *args, alpha=None, norm=None, cmap=None, vmin=None,
-        vmax=None, data=None, **kwargs):
+def pcolor(*args, data=None, **kwargs):
     __ret = gca().pcolor(
-        *args, alpha=alpha, norm=norm, cmap=cmap, vmin=vmin,
-        vmax=vmax, **({"data": data} if data is not None else {}),
+        *args, **({"data": data} if data is not None else {}),
         **kwargs)
     sci(__ret)
     return __ret
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @_autogen_docstring(Axes.pcolormesh)
-def pcolormesh(
-        *args, alpha=None, norm=None, cmap=None, vmin=None,
-        vmax=None, shading='flat', antialiased=False, data=None,
-        **kwargs):
+def pcolormesh(*args, data=None, **kwargs):
     __ret = gca().pcolormesh(
-        *args, alpha=alpha, norm=norm, cmap=cmap, vmin=vmin,
-        vmax=vmax, shading=shading, antialiased=antialiased,
-        **({"data": data} if data is not None else {}), **kwargs)
+        *args, **({"data": data} if data is not None else {}),
+        **kwargs)
     sci(__ret)
     return __ret
 
@@ -2783,10 +2773,10 @@ def pie(
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.plot)
-def plot(*args, scalex=True, scaley=True, data=None, **kwargs):
+def plot(*args, data=None, **kwargs):
     return gca().plot(
-        *args, scalex=scalex, scaley=scaley, **({"data": data} if data
-        is not None else {}), **kwargs)
+        *args, **({"data": data} if data is not None else {}),
+        **kwargs)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@@ -2823,8 +2813,8 @@ def quiver(*args, data=None, **kw):
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.quiverkey)
-def quiverkey(Q, X, Y, U, label, **kw):
-    return gca().quiverkey(Q, X, Y, U, label, **kw)
+def quiverkey(*args, **kw):
+    return gca().quiverkey(*args, **kw)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@@ -2893,21 +2883,18 @@ def stackplot(x, *args, data=None, **kwargs):
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.stem)
-def stem(
-        *args, linefmt=None, markerfmt=None, basefmt=None, bottom=0,
-        label=None, data=None):
+def stem(*args, data=None, **kwargs):
     return gca().stem(
-        *args, linefmt=linefmt, markerfmt=markerfmt, basefmt=basefmt,
-        bottom=bottom, label=label, **({"data": data} if data is not
-        None else {}))
+        *args, **({"data": data} if data is not None else {}),
+        **kwargs)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.step)
-def step(x, y, *args, where='pre', data=None, **kwargs):
+def step(x, y, *args, data=None, **kwargs):
     return gca().step(
-        x, y, *args, where=where, **({"data": data} if data is not
-        None else {}), **kwargs)
+        x, y, *args, **({"data": data} if data is not None else {}),
+        **kwargs)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@@ -2949,13 +2936,8 @@ def tick_params(axis='both', **kwargs):
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
 @docstring.copy_dedent(Axes.ticklabel_format)
-def ticklabel_format(
-        *, axis='both', style='', scilimits=None, useOffset=None,
-        useLocale=None, useMathText=None):
-    return gca().ticklabel_format(
-        axis=axis, style=style, scilimits=scilimits,
-        useOffset=useOffset, useLocale=useLocale,
-        useMathText=useMathText)
+def ticklabel_format(**kwargs):
+    return gca().ticklabel_format(**kwargs)
 
 
 # Autogenerated by boilerplate.py.  Do not edit as changes will be lost.

diff --git a/lib/matplotlib/tests/test_colorbar.py b/lib/matplotlib/tests/test_colorbar.py
@@ -7,6 +7,7 @@
 from matplotlib.colors import BoundaryNorm, LogNorm, PowerNorm
 from matplotlib.cm import get_cmap
 from matplotlib.colorbar import ColorbarBase
+from matplotlib.ticker import LogLocator, LogFormatter
 
 
 def _get_cmap_norms():
@@ -411,3 +412,27 @@ def test_colorbar_log_minortick_labels():
                     r'$\mathdefault{4\times10^{4}}$']
         for l, exp in zip(lb, expected):
             assert l.get_text() == exp
+
+
+def test_colorbar_renorm():
+    x, y = np.ogrid[-4:4:31j, -4:4:31j]
+    z = 120000*np.exp(-x**2 - y**2)
+
+    fig, ax = plt.subplots()
+    im = ax.imshow(z)
+    cbar = fig.colorbar(im)
+
+    norm = LogNorm(z.min(), z.max())
+    im.set_norm(norm)
+    cbar.set_norm(norm)
+    cbar.locator = LogLocator()
+    cbar.formatter = LogFormatter()
+    cbar.update_normal(im)
+    assert np.isclose(cbar.vmin, z.min())
+
+    norm = LogNorm(z.min() * 1000, z.max() * 1000)
+    im.set_norm(norm)
+    cbar.set_norm(norm)
+    cbar.update_normal(im)
+    assert np.isclose(cbar.vmin, z.min() * 1000)
+    assert np.isclose(cbar.vmax, z.max() * 1000)
diff --git a/tutorials/introductory/usage.py b/tutorials/introductory/usage.py
@@ -603,18 +603,18 @@ def my_plotter(ax, data1, data2, param_dict):
 # Prior to version 1.0, show() generally could not be called
 # more than once in a single script (although sometimes one
 # could get away with it); for version 1.0.1 and above, this
-# restriction is lifted, so one can write a script like this:
-
-import numpy as np
-import matplotlib.pyplot as plt
-
-plt.ioff()
-for i in range(3):
-    plt.plot(np.random.rand(10))
-    plt.show()
-
-###############################################################################
-# which makes three plots, one at a time.
+# restriction is lifted, so one can write a script like this::
+#
+#     import numpy as np
+#     import matplotlib.pyplot as plt
+#
+#     plt.ioff()
+#     for i in range(3):
+#         plt.plot(np.random.rand(10))
+#         plt.show()
+#
+# which makes three plots, one at a time. I.e. the second plot will show up,
+# once the first plot is closed.
 #
 # Summary
 # -------