matplotlib · tacaswell · Feb 8, 2016 · Jul 10, 2015 · Jul 10, 2015 · Nov 6, 2015
diff --git a/doc/users/whats_new/rcparams.rst b/doc/users/whats_new/rcparams.rst
@@ -22,6 +22,7 @@ Configuration (rcParams)
 ``svg.hashsalt``
 ````````````````
 
-If ``svg.hashsalt`` is ``None`` (which it is by default), the svg backend uses ``uuid4`` to generate the hash salt.
-If it is not ``None``, it must be a string that is used as the hash salt instead of ``uuid4``.
-This allows for deterministic SVG output.
+If ``svg.hashsalt`` is ``None`` (which it is by default), the svg
+backend uses ``uuid4`` to generate the hash salt.  If it is not
+``None``, it must be a string that is used as the hash salt instead of
+``uuid4``.  This allows for deterministic SVG output.
diff --git a/doc/users/whats_new/style_changes.rst b/doc/users/whats_new/style_changes.rst
@@ -0,0 +1,105 @@
+Changes to the default style
+----------------------------
+
+The most important changes in matplotlib 2.0 are the changes to the
+default style.
+
+While it is impossible to select the best default for all cases, these
+are designed to work well in the most common cases.
+
+These changes include:
+
+Colors
+``````
+
+- The default figure background color has changed from grey to white.
+  Use the rcParam ``figure.facecolor`` to control this.
+
+- The default cycle of colors to draw lines, markers and other content
+  has been changed.  It is based on the `Vega category10 palette
+  <https://github.com/vega/vega/wiki/Scales#scale-range-literals>`__.
+
+- The default color map used for images and pcolor meshes, etc., has
+  changed from ``jet`` to ``viridis``.
+
+- For markers, scatter plots, bar charts and pie charts, there is no
+  longer a black outline around filled markers by default.
+
+- Grid lines are light grey solid 1pt lines.  They are no longer dashed by
+  default.
+
+Plot layout
+```````````
+
+- The default dpi used for on-screen is now 100, which is the same as
+  the old default for saving files.  Due to this, the on-screen
+  display is now more what-you-see-is-what-you-get.
+
+- The number of ticks on an axis is now automatically determined based
+  on the length of the axis.
+
+- The limits are scaled to exactly the dimensions of the data, plus 5%
+  padding.  The old behavior was to scale to the nearest "round"
+  numbers.  To use the old behavior, set the ``rcParam``
+  ``axes.autolimit_mode`` to ``round_numbers``.  To control the
+  margins on particular side individually, pass any of the following
+  to any artist or plotting function:
+
+  - ``top_margin=False``
+  - ``bottom_margin=False``
+  - ``left_margin=False``
+  - ``right_margin=False``
+
+- Ticks now point outward by default.  To have ticks pointing inward,
+  use the ``rcParams`` ``xtick.direction`` and ``ytick.direction``.
+
+- By default, caps on the ends of errorbars are not present.  Use the
+  rcParam ``errorbar.capsize`` to control this.
+
+Images
+``````
+
+- The default mode for image interpolation, in the rcParam
+  ``image.interpolation``, is now ``nearest``.
+
+- The default shading mode for light source shading, in
+  ``matplotlib.colors.LightSource.shade``, is now ``overlay``.
+  Formerly, it was ``hsv``.
+
+- The default value for the rcParam ``image.resample`` is now
+  ``True``.  This will apply interpolation for both upsampling and
+  downsampling of an image.
+
+Fonts
+`````
+
+- The default font has changed from "Bitstream Vera Sans" to "DejaVu
+  Sans".  "DejaVu Sans" is an improvement on "Bistream Vera Sans" that
+  adds more international and math characters, but otherwise has the
+  same appearance.
+
+- The default math font when using the built-in math rendering engine
+  (mathtext) has changed from "Computer Modern" (i.e. LaTeX-like) to
+  "DejaVu Sans".  To revert to the old behavior, set the ``rcParam``
+  ``mathtext.fontset`` to ``cm``.  This change has no effect if the
+  TeX backend is used (i.e. ``text.usetex`` is ``True``).
+
+Dates
+`````
+
+- The default date formats are now all based on ISO format, i.e., with
+  the slowest-moving value first.  The date formatters are still
+  changeable through the ``date.autoformatter.*`` rcParams.  Python's
+  ``%x`` and ``%X`` date formats may be of particular interest to
+  format dates based on the current locale.
+
+Legends
+```````
+
+- By default, the number of points displayed in a legend is now 1.
+
+- The default legend location is ``best``, so the legend will be
+  automatically placed in a location to obscure the least amount of
+  data possible.
+
+- The legend now has rounded corners by default.
diff --git a/examples/api/demo_affine_image.py b/examples/api/demo_affine_image.py
@@ -37,7 +37,7 @@ def imshow_affine(ax, z, *kl, **kwargs):
 
     fig, (ax1, ax2) = plt.subplots(1, 2)
     Z = get_image()
-    im1 = imshow_affine(ax1, Z, interpolation='none', cmap=cm.jet,
+    im1 = imshow_affine(ax1, Z, interpolation='none',
                         origin='lower',
                         extent=[-2, 4, -3, 2], clip_on=True)
 
@@ -48,15 +48,15 @@ def imshow_affine(ax, z, *kl, **kwargs):
     x1, x2, y1, y2 = im1.get_extent()
     x3, y3 = x2, y1
 
-    ax1.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "r--", lw=3,
+    ax1.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "--",
              transform=trans_data2)
 
     ax1.set_xlim(-3, 5)
     ax1.set_ylim(-4, 4)
 
     # image skew
 
-    im2 = ax2.imshow(Z, interpolation='none', cmap=cm.jet,
+    im2 = ax2.imshow(Z, interpolation='none',
                      origin='lower',
                      extent=[-2, 4, -3, 2], clip_on=True)
     im2._image_skew_coordinate = (3, -2)

diff --git a/examples/api/filled_step.py b/examples/api/filled_step.py
@@ -61,9 +61,11 @@ def filled_hist(ax, edges, values, bottoms=None, orientation='v',
     values = np.r_[values, values[-1]]
     bottoms = np.r_[bottoms, bottoms[-1]]
     if orientation == 'h':
-        return ax.fill_betweenx(edges, values, bottoms, **kwargs)
+        return ax.fill_betweenx(edges, values, bottoms, left_margin=False,
+                                **kwargs)
     elif orientation == 'v':
-        return ax.fill_between(edges, values, bottoms, **kwargs)
+        return ax.fill_between(edges, values, bottoms, bottom_margin=False,
+                               **kwargs)
     else:
         raise AssertionError("you should never be here")
 
@@ -206,3 +208,5 @@ def stack_hist(ax, stacked_data, sty_cycle, bottoms=None,
 ax1.set_xlabel('counts')
 ax1.set_ylabel('x')
 ax2.set_ylabel('x')
+
+plt.show()
diff --git a/examples/api/histogram_path_demo.py b/examples/api/histogram_path_demo.py
@@ -36,8 +36,7 @@
 barpath = path.Path.make_compound_path_from_polys(XY)
 
 # make a patch out of it
-patch = patches.PathPatch(
-    barpath, facecolor='blue', edgecolor='gray', alpha=0.8)
+patch = patches.PathPatch(barpath, facecolor='blue')
 ax.add_patch(patch)
 
 # update the view limits

diff --git a/examples/api/image_zcoord.py b/examples/api/image_zcoord.py
@@ -9,7 +9,7 @@
 X = 10*np.random.rand(5, 3)
 
 fig, ax = plt.subplots()
-ax.imshow(X, cmap=cm.jet, interpolation='nearest')
+ax.imshow(X, interpolation='nearest')
 
 numrows, numcols = X.shape
 

diff --git a/examples/api/patch_collection.py b/examples/api/patch_collection.py
@@ -39,7 +39,7 @@
     patches.append(polygon)
 
 colors = 100*np.random.rand(len(patches))
-p = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
+p = PatchCollection(patches, alpha=0.4)
 p.set_array(np.array(colors))
 ax.add_collection(p)
 plt.colorbar(p)

diff --git a/examples/api/power_norm_demo.py b/examples/api/power_norm_demo.py
@@ -19,9 +19,10 @@
 
 for i, gamma in enumerate(gammas):
     plt.subplot(xgrid, ygrid, i + 2)
-    plt.title('Power law normalization\n$(\gamma=%1.1f)$' % gamma)
+    plt.title('Power law\n$(\gamma=%1.1f)$' % gamma)
     plt.hist2d(data[:, 0], data[:, 1],
                bins=100, norm=mcolors.PowerNorm(gamma))
 
-plt.subplots_adjust(hspace=0.39)
+plt.tight_layout()
+
 plt.show()
diff --git a/examples/api/sankey_demo_basics.py b/examples/api/sankey_demo_basics.py
@@ -42,10 +42,8 @@
            orientations=[-1, 1, 0, 1, 1, 1, -1, -1, 0],
            pathlengths=[0.25, 0.25, 0.25, 0.25, 0.25, 0.6, 0.25, 0.25,
                         0.25],
-           patchlabel="Widget\nA",
-           alpha=0.2, lw=2.0)  # Arguments to matplotlib.patches.PathPatch()
+           patchlabel="Widget\nA")  # Arguments to matplotlib.patches.PathPatch()
 diagrams = sankey.finish()
-diagrams[0].patch.set_facecolor('#37c959')
 diagrams[0].texts[-1].set_color('r')
 diagrams[0].text.set_fontweight('bold')
 # Notice:
@@ -66,7 +64,7 @@
 sankey = Sankey(ax=ax, unit=None)
 sankey.add(flows=flows, label='one',
            orientations=[-1, 1, 0, 1, 1, 1, -1, -1, 0])
-sankey.add(flows=[-0.25, 0.15, 0.1], fc='#37c959', label='two',
+sankey.add(flows=[-0.25, 0.15, 0.1], label='two',
            orientations=[-1, -1, -1], prior=0, connect=(0, 0))
 diagrams = sankey.finish()
 diagrams[-1].patch.set_hatch('/')

diff --git a/examples/api/sankey_demo_links.py b/examples/api/sankey_demo_links.py
@@ -12,13 +12,12 @@
 def side(sankey, n=1):
     """Generate a side chain."""
     prior = len(sankey.diagrams)
-    colors = cycle(['orange', 'b', 'g', 'r', 'c', 'm', 'y'])
     for i in range(0, 2*n, 2):
         sankey.add(flows=[1, -1], orientations=[-1, -1],
-                   patchlabel=str(prior + i), facecolor=next(colors),
+                   patchlabel=str(prior + i),
                    prior=prior + i - 1, connect=(1, 0), alpha=0.5)
         sankey.add(flows=[1, -1], orientations=[1, 1],
-                   patchlabel=str(prior + i + 1), facecolor=next(colors),
+                   patchlabel=str(prior + i + 1),
                    prior=prior + i, connect=(1, 0), alpha=0.5)
 
 

diff --git a/examples/api/sankey_demo_old.py b/examples/api/sankey_demo_old.py
@@ -187,7 +187,7 @@ def put_labels(labels, positions, output=True):
 
     patch, (intexts, outtexts) = sankey(ax, outputs=outputs,
                                         outlabels=outlabels, inputs=inputs,
-                                        inlabels=None, fc='g', alpha=0.2)
+                                        inlabels=None)
     outtexts[1].set_color('r')
     outtexts[-1].set_fontweight('bold')
 

diff --git a/examples/api/skewt.py b/examples/api/skewt.py
@@ -238,11 +238,11 @@ def _set_lim_and_transforms(self):
 
     # Plot the data using normal plotting functions, in this case using
     # log scaling in Y, as dicatated by the typical meteorological plot
-    ax.semilogy(T, p, 'r')
-    ax.semilogy(Td, p, 'g')
+    ax.semilogy(T, p)
+    ax.semilogy(Td, p)
 
     # An example of a slanted line at constant X
-    l = ax.axvline(0, color='b')
+    l = ax.axvline(0)
 
     # Disables the log-formatting that comes with semilogy
     ax.yaxis.set_major_formatter(ScalarFormatter())

diff --git a/examples/lines_bars_and_markers/barh_demo.py b/examples/lines_bars_and_markers/barh_demo.py
@@ -13,7 +13,7 @@
 performance = 3 + 10 * np.random.rand(len(people))
 error = np.random.rand(len(people))
 
-plt.barh(y_pos, performance, xerr=error, align='center', alpha=0.4)
+plt.barh(y_pos, performance, xerr=error, align='center')
 plt.yticks(y_pos, people)
 plt.xlabel('Performance')
 plt.title('How fast do you want to go today?')

diff --git a/examples/lines_bars_and_markers/fill_demo.py b/examples/lines_bars_and_markers/fill_demo.py
@@ -4,10 +4,9 @@
 import numpy as np
 import matplotlib.pyplot as plt
 
-
-x = np.linspace(0, 1)
+x = np.linspace(0, 1, 500)
 y = np.sin(4 * np.pi * x) * np.exp(-5 * x)
 
-plt.fill(x, y, 'r')
+plt.fill(x, y)
 plt.grid(True)
 plt.show()
diff --git a/examples/lines_bars_and_markers/fill_demo_features.py b/examples/lines_bars_and_markers/fill_demo_features.py
@@ -10,7 +10,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 
-x = np.linspace(0, 2 * np.pi, 100)
+x = np.linspace(0, 2 * np.pi, 500)
 y1 = np.sin(x)
 y2 = np.sin(3 * x)
 plt.fill(x, y1, 'b', x, y2, 'r', alpha=0.3)

diff --git a/examples/lines_bars_and_markers/line_demo_dash_control.py b/examples/lines_bars_and_markers/line_demo_dash_control.py
@@ -8,7 +8,7 @@
 import matplotlib.pyplot as plt
 
 
-x = np.linspace(0, 10)
+x = np.linspace(0, 10, 500)
 line, = plt.plot(x, np.sin(x), '--', linewidth=2)
 
 dashes = [10, 5, 100, 5]  # 10 points on, 5 off, 100 on, 5 off

diff --git a/examples/lines_bars_and_markers/line_styles_reference.py b/examples/lines_bars_and_markers/line_styles_reference.py
@@ -25,7 +25,7 @@ def nice_repr(text):
 
 linestyles = ['-', '--', '-.', ':']
 for y, linestyle in enumerate(linestyles):
-    ax.text(-0.5, y, nice_repr(linestyle), **text_style)
+    ax.text(-0.1, y, nice_repr(linestyle), **text_style)
     ax.plot(y * points, linestyle=linestyle, color=color, linewidth=3)
     format_axes(ax)
     ax.set_title('line styles')

diff --git a/examples/mplot3d/lorenz_attractor.py b/examples/mplot3d/lorenz_attractor.py
@@ -40,7 +40,7 @@ def lorenz(x, y, z, s=10, r=28, b=2.667):
 fig = plt.figure()
 ax = fig.gca(projection='3d')
 
-ax.plot(xs, ys, zs)
+ax.plot(xs, ys, zs, lw=0.5)
 ax.set_xlabel("X Axis")
 ax.set_ylabel("Y Axis")
 ax.set_zlabel("Z Axis")

diff --git a/examples/mplot3d/surface3d_demo3.py b/examples/mplot3d/surface3d_demo3.py
@@ -21,7 +21,7 @@
         colors[x, y] = colortuple[(x + y) % len(colortuple)]
 
 surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, facecolors=colors,
-                       linewidth=0, antialiased=False)
+                       linewidth=0)
 
 ax.set_zlim3d(-1, 1)
 ax.w_zaxis.set_major_locator(LinearLocator(6))

diff --git a/examples/mplot3d/trisurf3d_demo.py b/examples/mplot3d/trisurf3d_demo.py
@@ -27,6 +27,6 @@
 fig = plt.figure()
 ax = fig.gca(projection='3d')
 
-ax.plot_trisurf(x, y, z, cmap=cm.jet, linewidth=0.2)
+ax.plot_trisurf(x, y, z, linewidth=0.2, antialiased=True)
 
 plt.show()
diff --git a/examples/pie_and_polar_charts/pie_demo_features.py b/examples/pie_and_polar_charts/pie_demo_features.py
@@ -21,10 +21,9 @@
 # The slices will be ordered and plotted counter-clockwise.
 labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
 sizes = [15, 30, 45, 10]
-colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
 explode = (0, 0.1, 0, 0)  # only "explode" the 2nd slice (i.e. 'Hogs')
 
-plt.pie(sizes, explode=explode, labels=labels, colors=colors,
+plt.pie(sizes, explode=explode, labels=labels,
         autopct='%1.1f%%', shadow=True, startangle=90)
 # Set aspect ratio to be equal so that pie is drawn as a circle.
 plt.axis('equal')
@@ -33,16 +32,16 @@
 ax = fig.gca()
 import numpy as np
 
-ax.pie(np.random.random(4), explode=explode, labels=labels, colors=colors,
+ax.pie(np.random.random(4), explode=explode, labels=labels,
        autopct='%1.1f%%', shadow=True, startangle=90,
        radius=0.25, center=(0, 0), frame=True)
-ax.pie(np.random.random(4), explode=explode, labels=labels, colors=colors,
+ax.pie(np.random.random(4), explode=explode, labels=labels,
        autopct='%1.1f%%', shadow=True, startangle=90,
        radius=0.25, center=(1, 1), frame=True)
-ax.pie(np.random.random(4), explode=explode, labels=labels, colors=colors,
+ax.pie(np.random.random(4), explode=explode, labels=labels,
        autopct='%1.1f%%', shadow=True, startangle=90,
        radius=0.25, center=(0, 1), frame=True)
-ax.pie(np.random.random(4), explode=explode, labels=labels, colors=colors,
+ax.pie(np.random.random(4), explode=explode, labels=labels,
        autopct='%1.1f%%', shadow=True, startangle=90,
        radius=0.25, center=(1, 0), frame=True)
 

diff --git a/examples/pylab_examples/annotation_demo.py b/examples/pylab_examples/annotation_demo.py
@@ -48,7 +48,7 @@
 
     t = np.arange(0.0, 5.0, 0.01)
     s = np.cos(2*np.pi*t)
-    line, = ax.plot(t, s, lw=3, color='purple')
+    line, = ax.plot(t, s)
 
     ax.annotate('axes center', xy=(.5, .5), xycoords='axes fraction',
                 horizontalalignment='center', verticalalignment='center')
@@ -97,7 +97,7 @@
     ax = fig.add_subplot(111, projection='polar')
     r = np.arange(0, 1, 0.001)
     theta = 2*2*np.pi*r
-    line, = ax.plot(theta, r, color='#ee8d18', lw=3)
+    line, = ax.plot(theta, r)
 
     ind = 800
     thisr, thistheta = r[ind], theta[ind]