diff --git a/doc/users/whats_new/rcparams.rst b/doc/users/whats_new/rcparams.rst index 82b9d30a5581..c27a0eee8037 100644 --- 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 new file mode 100644 index 000000000000..5116f1bc12ee --- /dev/null +++ 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 + `__. + +- 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 old mode 100644 new mode 100755 index 3b5ed23b1fb9..75a7b3c01e51 --- 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) @@ -48,7 +48,7 @@ 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) @@ -56,7 +56,7 @@ def imshow_affine(ax, z, *kl, **kwargs): # 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 index 40948feb4a09..98dbd3282c08 100644 --- 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 index a7b1bd3e8106..d43f542547d7 100644 --- 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 index 38f6fbb3083c..b0a0908d3f50 100644 --- 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 index 85a3ab39e6cb..715196a27c5b 100644 --- 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 old mode 100644 new mode 100755 index 90fef637311a..dc0b9103bc6a --- 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 index 4a5f5ebed32d..ea7b6111df01 100644 --- 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 index ed2e755dbf27..f68fc251f811 100644 --- 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 index dee4ea220379..fe4d924f774b 100755 --- 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 index ba1d23b6c9e6..0eca185e6df9 100644 --- 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 index 38ab12e72c26..01993e95686c 100644 --- 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 index fff88f2e503a..55d5e238186e 100644 --- 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 index 230f1631c0ad..21bae0332be8 100644 --- 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 index 65f21b9c9207..8f4a205db761 100644 --- 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 index 625d0a5afde0..554e896f9753 100644 --- 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 index 5302822d685b..976eee902687 100644 --- 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 index d23721c28810..50d10ca4986f 100644 --- 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 index f7919d1bd9c8..0d040b076dd8 100644 --- 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 index ed17febb1705..32aaa94f9569 100644 --- 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 index 04885da3a57b..8d115842dbab 100644 --- 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] diff --git a/examples/pylab_examples/annotation_demo2.py b/examples/pylab_examples/annotation_demo2.py index 0c2b357405fe..ee6e2c95a24f 100644 --- a/examples/pylab_examples/annotation_demo2.py +++ b/examples/pylab_examples/annotation_demo2.py @@ -9,7 +9,7 @@ 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, lw=3) ax.annotate('arrowstyle', xy=(0, 1), xycoords='data', xytext=(-50, 30), textcoords='offset points', diff --git a/examples/pylab_examples/bar_stacked.py b/examples/pylab_examples/bar_stacked.py old mode 100644 new mode 100755 index 64b915b11ebd..5ce47fb8daba --- a/examples/pylab_examples/bar_stacked.py +++ b/examples/pylab_examples/bar_stacked.py @@ -12,8 +12,8 @@ ind = np.arange(N) # the x locations for the groups width = 0.35 # the width of the bars: can also be len(x) sequence -p1 = plt.bar(ind, menMeans, width, color='r', yerr=menStd) -p2 = plt.bar(ind, womenMeans, width, color='y', +p1 = plt.bar(ind, menMeans, width, yerr=menStd) +p2 = plt.bar(ind, womenMeans, width, bottom=menMeans, yerr=womenStd) plt.ylabel('Scores') diff --git a/examples/pylab_examples/errorbar_limits.py b/examples/pylab_examples/errorbar_limits.py index 78e2f0c8c861..7f62dfecdab7 100644 --- a/examples/pylab_examples/errorbar_limits.py +++ b/examples/pylab_examples/errorbar_limits.py @@ -9,7 +9,7 @@ x = np.arange(10.0) y = np.sin(np.arange(10.0)/20.0*np.pi) -plt.errorbar(x, y, yerr=0.1, capsize=3) +plt.errorbar(x, y, yerr=0.1) y = np.sin(np.arange(10.0)/20.0*np.pi) + 1 plt.errorbar(x, y, yerr=0.1, uplims=True) diff --git a/examples/pylab_examples/figure_title.py b/examples/pylab_examples/figure_title.py index 4bd967cd0f8c..c01ff4986cf8 100644 --- a/examples/pylab_examples/figure_title.py +++ b/examples/pylab_examples/figure_title.py @@ -14,16 +14,18 @@ def f(t): plt.subplot(121) -plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k') +plt.plot(t1, f(t1), 'o', t2, f(t2), '-') plt.title('subplot 1') plt.ylabel('Damped oscillation') plt.suptitle('This is a somewhat long figure title', fontsize=16) plt.subplot(122) -plt.plot(t3, np.cos(2*np.pi*t3), 'r--') +plt.plot(t3, np.cos(2*np.pi*t3), '--') plt.xlabel('time (s)') plt.title('subplot 2') plt.ylabel('Undamped') +plt.subplots_adjust(left=0.2, wspace=0.8, top=0.8) + plt.show() diff --git a/examples/pylab_examples/fill_betweenx_demo.py b/examples/pylab_examples/fill_betweenx_demo.py index 708f81903cf0..098c0688523a 100644 --- a/examples/pylab_examples/fill_betweenx_demo.py +++ b/examples/pylab_examples/fill_betweenx_demo.py @@ -16,13 +16,13 @@ ax3 = fig.add_subplot(313, sharex=ax1) ax1.fill_betweenx(x, 0, y1) -ax1.set_ylabel('between y1 and 0') +ax1.set_ylabel('(y1, 0)') ax2.fill_betweenx(x, y1, 1) -ax2.set_ylabel('between y1 and 1') +ax2.set_ylabel('(y1, 1)') ax3.fill_betweenx(x, y1, y2) -ax3.set_ylabel('between y1 and y2') +ax3.set_ylabel('(y1, y2)') ax3.set_xlabel('x') # now fill between y1 and y2 where a logical condition is met. Note diff --git a/examples/pylab_examples/geo_demo.py b/examples/pylab_examples/geo_demo.py index c1b92f12d6eb..9ef96b2b564c 100644 --- a/examples/pylab_examples/geo_demo.py +++ b/examples/pylab_examples/geo_demo.py @@ -1,18 +1,22 @@ import matplotlib.pyplot as plt -plt.subplot(221, projection="aitoff") +plt.figure() +plt.subplot(111, projection="aitoff") plt.title("Aitoff") plt.grid(True) -plt.subplot(222, projection="hammer") +plt.figure() +plt.subplot(111, projection="hammer") plt.title("Hammer") plt.grid(True) -plt.subplot(223, projection="lambert") +plt.figure() +plt.subplot(111, projection="lambert") plt.title("Lambert") plt.grid(True) -plt.subplot(224, projection="mollweide") +plt.figure() +plt.subplot(111, projection="mollweide") plt.title("Mollweide") plt.grid(True) diff --git a/examples/pylab_examples/griddata_demo.py b/examples/pylab_examples/griddata_demo.py index af04748567db..74af8424fb83 100644 --- a/examples/pylab_examples/griddata_demo.py +++ b/examples/pylab_examples/griddata_demo.py @@ -16,11 +16,11 @@ zi = griddata(x, y, z, xi, yi, interp='linear') # contour the gridded data, plotting dots at the nonuniform data points. CS = plt.contour(xi, yi, zi, 15, linewidths=0.5, colors='k') -CS = plt.contourf(xi, yi, zi, 15, cmap=plt.cm.rainbow, +CS = plt.contourf(xi, yi, zi, 15, vmax=abs(zi).max(), vmin=-abs(zi).max()) plt.colorbar() # draw colorbar # plot data points. -plt.scatter(x, y, marker='o', c='b', s=5, zorder=10) +plt.scatter(x, y, marker='o', s=5, zorder=10) plt.xlim(-2, 2) plt.ylim(-2, 2) plt.title('griddata test (%d points)' % npts) diff --git a/examples/pylab_examples/legend_demo2.py b/examples/pylab_examples/legend_demo2.py index 6b7675bad558..01619f3fd897 100644 --- a/examples/pylab_examples/legend_demo2.py +++ b/examples/pylab_examples/legend_demo2.py @@ -10,8 +10,8 @@ # extracts the first element of the list into l1 using tuple # unpacking. So l1 is a Line2D instance, not a sequence of lines l1, = plt.plot(t2, np.exp(-t2)) -l2, l3 = plt.plot(t2, np.sin(2 * np.pi * t2), '--go', t1, np.log(1 + t1), '.') -l4, = plt.plot(t2, np.exp(-t2) * np.sin(2 * np.pi * t2), 'rs-.') +l2, l3 = plt.plot(t2, np.sin(2 * np.pi * t2), '--o', t1, np.log(1 + t1), '.') +l4, = plt.plot(t2, np.exp(-t2) * np.sin(2 * np.pi * t2), 's-.') plt.legend((l2, l4), ('oscillatory', 'damped'), loc='upper right', shadow=True) plt.xlabel('time') diff --git a/examples/pylab_examples/legend_demo4.py b/examples/pylab_examples/legend_demo4.py index c9b3e3be976e..2fd076a97400 100644 --- a/examples/pylab_examples/legend_demo4.py +++ b/examples/pylab_examples/legend_demo4.py @@ -18,4 +18,5 @@ bottom_ax.stem([0.3, 1.5, 2.7], [1, 3.6, 2.7], label="stem test") bottom_ax.legend() +plt.subplots_adjust(hspace=0.7) plt.show() diff --git a/examples/pylab_examples/mathtext_demo.py b/examples/pylab_examples/mathtext_demo.py index ec3e3536055f..9de179b765c3 100755 --- a/examples/pylab_examples/mathtext_demo.py +++ b/examples/pylab_examples/mathtext_demo.py @@ -9,7 +9,7 @@ fig = figure() fig.subplots_adjust(bottom=0.2) -ax = fig.add_subplot(111, facecolor='y') +ax = fig.add_subplot(111) ax.plot([1, 2, 3], 'r') x = np.arange(0.0, 3.0, 0.1) diff --git a/examples/pylab_examples/multiline.py b/examples/pylab_examples/multiline.py index 2dad624b81bd..9b1da8b446fd 100644 --- a/examples/pylab_examples/multiline.py +++ b/examples/pylab_examples/multiline.py @@ -17,15 +17,15 @@ plt.subplot(122) -plt.text(0.29, 0.7, "Mat\nTTp\n123", size=18, +plt.text(0.29, 0.4, "Mat\nTTp\n123", size=18, va="baseline", ha="right", multialignment="left", bbox=dict(fc="none")) -plt.text(0.34, 0.7, "Mag\nTTT\n123", size=18, +plt.text(0.34, 0.4, "Mag\nTTT\n123", size=18, va="baseline", ha="left", multialignment="left", bbox=dict(fc="none")) -plt.text(0.95, 0.7, "Mag\nTTT$^{A^A}$\n123", size=18, +plt.text(0.95, 0.4, "Mag\nTTT$^{A^A}$\n123", size=18, va="baseline", ha="right", multialignment="left", bbox=dict(fc="none")) @@ -35,6 +35,6 @@ plt.axhline(0.7) plt.title("test line spacing for multiline text") -plt.subplots_adjust(bottom=0.25, top=0.8) +plt.subplots_adjust(bottom=0.25, top=0.75) plt.draw() plt.show() diff --git a/examples/pylab_examples/multiple_figs_demo.py b/examples/pylab_examples/multiple_figs_demo.py index 625d1bbd752a..9097c51e4e6b 100644 --- a/examples/pylab_examples/multiple_figs_demo.py +++ b/examples/pylab_examples/multiple_figs_demo.py @@ -18,7 +18,7 @@ # now switch back to figure 1 and make some changes plt.figure(1) plt.subplot(211) -plt.plot(t, s2, 'gs') +plt.plot(t, s2, 's') ax = plt.gca() ax.set_xticklabels([]) diff --git a/examples/pylab_examples/newscalarformatter_demo.py b/examples/pylab_examples/newscalarformatter_demo.py index 1e525ad8cb6e..381ced7f3b49 100644 --- a/examples/pylab_examples/newscalarformatter_demo.py +++ b/examples/pylab_examples/newscalarformatter_demo.py @@ -23,6 +23,8 @@ ax4.xaxis.set_major_formatter(OldScalarFormatter()) ax4.yaxis.set_major_formatter(OldScalarFormatter()) +fig.subplots_adjust(wspace=0.7, hspace=0.6) + # Example 2 x = np.arange(0, 1, .01) fig, [[ax1, ax2], [ax3, ax4]] = plt.subplots(2, 2, figsize=(6, 6)) @@ -46,6 +48,8 @@ ax4.xaxis.set_major_formatter(ScalarFormatter()) ax4.yaxis.set_major_formatter(ScalarFormatter()) +fig.subplots_adjust(wspace=0.7, hspace=0.6) + # Example 3 x = np.arange(0, 1, .01) fig, [[ax1, ax2], [ax3, ax4]] = plt.subplots(2, 2, figsize=(6, 6)) @@ -69,6 +73,8 @@ ax4.xaxis.set_major_formatter(ScalarFormatter(useOffset=False)) ax4.yaxis.set_major_formatter(ScalarFormatter(useOffset=False)) +fig.subplots_adjust(wspace=0.7, hspace=0.6) + # Example 4 x = np.arange(0, 1, .01) fig, [[ax1, ax2], [ax3, ax4]] = plt.subplots(2, 2, figsize=(6, 6)) @@ -91,4 +97,7 @@ ax4.plot(-x * 1e5, -x * 1e-4) ax4.xaxis.set_major_formatter(ScalarFormatter(useMathText=True)) ax4.yaxis.set_major_formatter(ScalarFormatter(useMathText=True)) + +fig.subplots_adjust(wspace=0.7, hspace=0.6) + plt.show() diff --git a/examples/pylab_examples/pcolor_demo.py b/examples/pylab_examples/pcolor_demo.py index 7f656c6c3193..2529a57b2d67 100644 --- a/examples/pylab_examples/pcolor_demo.py +++ b/examples/pylab_examples/pcolor_demo.py @@ -39,7 +39,7 @@ plt.imshow(z, cmap='RdBu', vmin=z_min, vmax=z_max, extent=[x.min(), x.max(), y.min(), y.max()], interpolation='nearest', origin='lower') -plt.title('image (interp. nearest)') +plt.title('image (nearest)') plt.colorbar() @@ -48,5 +48,6 @@ plt.title('pcolorfast') plt.colorbar() +plt.subplots_adjust(wspace=0.5, hspace=0.5) plt.show() diff --git a/examples/pylab_examples/polar_demo.py b/examples/pylab_examples/polar_demo.py index 7497d93d2a37..149f505b2ba3 100644 --- a/examples/pylab_examples/polar_demo.py +++ b/examples/pylab_examples/polar_demo.py @@ -9,7 +9,7 @@ theta = 2 * np.pi * r ax = plt.subplot(111, projection='polar') -ax.plot(theta, r, color='r', linewidth=3) +ax.plot(theta, r) ax.set_rmax(2.0) ax.grid(True) diff --git a/examples/pylab_examples/quadmesh_demo.py b/examples/pylab_examples/quadmesh_demo.py index e47fd4e6bc1c..10707dba16dd 100755 --- a/examples/pylab_examples/quadmesh_demo.py +++ b/examples/pylab_examples/quadmesh_demo.py @@ -27,12 +27,10 @@ fig = figure() ax = fig.add_subplot(121) -ax.set_facecolor("#bdb76b") ax.pcolormesh(Qx, Qz, Z, shading='gouraud') ax.set_title('Without masked values') ax = fig.add_subplot(122) -ax.set_facecolor("#bdb76b") # You can control the color of the masked region: #cmap = cm.jet #cmap.set_bad('r', 1.0) diff --git a/examples/pylab_examples/quiver_demo.py b/examples/pylab_examples/quiver_demo.py index d1f319ffa8f3..49205ccae282 100644 --- a/examples/pylab_examples/quiver_demo.py +++ b/examples/pylab_examples/quiver_demo.py @@ -19,7 +19,7 @@ # 1 plt.figure() Q = plt.quiver(U, V) -qk = plt.quiverkey(Q, 0.5, 0.92, 2, r'$2 \frac{m}{s}$', labelpos='W', +qk = plt.quiverkey(Q, 0.5, 0.98, 2, r'$2 \frac{m}{s}$', labelpos='W', fontproperties={'weight': 'bold'}) l, r, b, t = plt.axis() dx, dy = r - l, t - b @@ -58,7 +58,7 @@ qk = plt.quiverkey(Q, 0.9, 1.05, 1, r'$1 \frac{m}{s}$', labelpos='E', fontproperties={'weight': 'bold'}) -plt.plot(X, Y, 'k.') +plt.plot(X, Y, 'k.', markersize=2) plt.axis([-1, 7, -1, 7]) plt.title("scales with x view; pivot='tip'") @@ -66,7 +66,7 @@ plt.figure() Q = plt.quiver(X[::3, ::3], Y[::3, ::3], U[::3, ::3], V[::3, ::3], color='r', units='x', - linewidths=(2,), edgecolors=('k'), headaxislength=5) + linewidths=(0.5,), edgecolors=('k'), headaxislength=5) qk = plt.quiverkey(Q, 0.5, 0.03, 1, r'$1 \frac{m}{s}$', fontproperties={'weight': 'bold'}) plt.axis([-1, 7, -1, 7]) @@ -80,7 +80,7 @@ U = ma.masked_array(U, mask=M) V = ma.masked_array(V, mask=M) Q = plt.quiver(U, V) -qk = plt.quiverkey(Q, 0.5, 0.92, 2, r'$2 \frac{m}{s}$', labelpos='W', +qk = plt.quiverkey(Q, 0.5, 0.98, 2, r'$2 \frac{m}{s}$', labelpos='W', fontproperties={'weight': 'bold'}) l, r, b, t = plt.axis() dx, dy = r - l, t - b diff --git a/examples/pylab_examples/specgram_demo.py b/examples/pylab_examples/specgram_demo.py index a5373c58fc41..63c48ea27fde 100644 --- a/examples/pylab_examples/specgram_demo.py +++ b/examples/pylab_examples/specgram_demo.py @@ -25,6 +25,5 @@ ax1 = plt.subplot(211) plt.plot(t, x) plt.subplot(212, sharex=ax1) -Pxx, freqs, bins, im = plt.specgram(x, NFFT=NFFT, Fs=Fs, noverlap=900, - cmap=plt.cm.gist_heat) +Pxx, freqs, bins, im = plt.specgram(x, NFFT=NFFT, Fs=Fs, noverlap=900) plt.show() diff --git a/examples/pylab_examples/symlog_demo.py b/examples/pylab_examples/symlog_demo.py index a93d7c3c3ce6..4c4a793abeb8 100755 --- a/examples/pylab_examples/symlog_demo.py +++ b/examples/pylab_examples/symlog_demo.py @@ -26,4 +26,6 @@ plt.grid(True) plt.ylabel('symlog both') +plt.subplots_adjust(hspace=0.5, left=0.2) + plt.show() diff --git a/examples/pylab_examples/tricontour_vs_griddata.py b/examples/pylab_examples/tricontour_vs_griddata.py index 10012cf58c79..7307d37b76c5 100644 --- a/examples/pylab_examples/tricontour_vs_griddata.py +++ b/examples/pylab_examples/tricontour_vs_griddata.py @@ -24,7 +24,7 @@ yi = np.linspace(-2.1, 2.1, ngridy) zi = mlab.griddata(x, y, z, xi, yi, interp='linear') plt.contour(xi, yi, zi, 15, linewidths=0.5, colors='k') -plt.contourf(xi, yi, zi, 15, cmap=plt.cm.rainbow, +plt.contourf(xi, yi, zi, 15, norm=plt.Normalize(vmax=abs(zi).max(), vmin=-abs(zi).max())) plt.colorbar() # draw colorbar plt.plot(x, y, 'ko', ms=3) @@ -39,7 +39,7 @@ plt.subplot(212) triang = tri.Triangulation(x, y) plt.tricontour(x, y, z, 15, linewidths=0.5, colors='k') -plt.tricontourf(x, y, z, 15, cmap=plt.cm.rainbow, +plt.tricontourf(x, y, z, 15, norm=plt.Normalize(vmax=abs(zi).max(), vmin=-abs(zi).max())) plt.colorbar() plt.plot(x, y, 'ko', ms=3) @@ -48,4 +48,6 @@ plt.title('tricontour (%d points)' % npts) print('tricontour seconds: %f' % (time.clock() - start)) +plt.subplots_adjust(hspace=0.5) + plt.show() diff --git a/examples/pylab_examples/triinterp_demo.py b/examples/pylab_examples/triinterp_demo.py index 70fac4ebf568..f955727064dd 100644 --- a/examples/pylab_examples/triinterp_demo.py +++ b/examples/pylab_examples/triinterp_demo.py @@ -35,22 +35,22 @@ # Plot linear interpolation to quad grid. plt.subplot(222) plt.contourf(xi, yi, zi_lin) -plt.plot(xi, yi, 'k-', alpha=0.5) -plt.plot(xi.T, yi.T, 'k-', alpha=0.5) +plt.plot(xi, yi, 'k-', lw=0.5, alpha=0.5) +plt.plot(xi.T, yi.T, 'k-', lw=0.5, alpha=0.5) plt.title("Linear interpolation") # Plot cubic interpolation to quad grid, kind=geom plt.subplot(223) plt.contourf(xi, yi, zi_cubic_geom) -plt.plot(xi, yi, 'k-', alpha=0.5) -plt.plot(xi.T, yi.T, 'k-', alpha=0.5) +plt.plot(xi, yi, 'k-', lw=0.5, alpha=0.5) +plt.plot(xi.T, yi.T, 'k-', lw=0.5, alpha=0.5) plt.title("Cubic interpolation,\nkind='geom'") # Plot cubic interpolation to quad grid, kind=min_E plt.subplot(224) plt.contourf(xi, yi, zi_cubic_min_E) -plt.plot(xi, yi, 'k-', alpha=0.5) -plt.plot(xi.T, yi.T, 'k-', alpha=0.5) +plt.plot(xi, yi, 'k-', lw=0.5, alpha=0.5) +plt.plot(xi.T, yi.T, 'k-', lw=0.5, alpha=0.5) plt.title("Cubic interpolation,\nkind='min_E'") plt.tight_layout() diff --git a/examples/pylab_examples/tripcolor_demo.py b/examples/pylab_examples/tripcolor_demo.py index 03e467c2a6d7..bb7bb4ed0222 100644 --- a/examples/pylab_examples/tripcolor_demo.py +++ b/examples/pylab_examples/tripcolor_demo.py @@ -35,14 +35,14 @@ # tripcolor plot. plt.figure() plt.gca().set_aspect('equal') -plt.tripcolor(triang, z, shading='flat', cmap=plt.cm.rainbow) +plt.tripcolor(triang, z, shading='flat') plt.colorbar() plt.title('tripcolor of Delaunay triangulation, flat shading') # Illustrate Gouraud shading. plt.figure() plt.gca().set_aspect('equal') -plt.tripcolor(triang, z, shading='gouraud', cmap=plt.cm.rainbow) +plt.tripcolor(triang, z, shading='gouraud') plt.colorbar() plt.title('tripcolor of Delaunay triangulation, gouraud shading') diff --git a/examples/pylab_examples/triplot_demo.py b/examples/pylab_examples/triplot_demo.py index a524547291b0..7b3cee6cdd18 100644 --- a/examples/pylab_examples/triplot_demo.py +++ b/examples/pylab_examples/triplot_demo.py @@ -34,7 +34,7 @@ # Plot the triangulation. plt.figure() plt.gca().set_aspect('equal') -plt.triplot(triang, 'bo-') +plt.triplot(triang, 'bo-', lw=1) plt.title('triplot of Delaunay triangulation') @@ -90,7 +90,7 @@ # calculations. plt.figure() plt.gca().set_aspect('equal') -plt.triplot(x, y, triangles, 'go-') +plt.triplot(x, y, triangles, 'go-', lw=1.0) plt.title('triplot of user-specified triangulation') plt.xlabel('Longitude (degrees)') plt.ylabel('Latitude (degrees)') diff --git a/examples/pylab_examples/usetex_demo.py b/examples/pylab_examples/usetex_demo.py index 93e86e820a37..05797b834597 100644 --- a/examples/pylab_examples/usetex_demo.py +++ b/examples/pylab_examples/usetex_demo.py @@ -11,16 +11,16 @@ X, (X + 1)/2, # level set distance function X, (1.4 + np.tanh(4.*X/delta))/4, # composition profile X, X < 0, 'k--', # sharp interface - linewidth=5) + ) # legend plt.legend(('phase field', 'level set', 'composition', 'sharp interface'), shadow=True, loc=(0.01, 0.55)) ltext = plt.gca().get_legend().get_texts() -plt.setp(ltext[0], fontsize=20, color='b') -plt.setp(ltext[1], fontsize=20, color='g') -plt.setp(ltext[2], fontsize=20, color='r') -plt.setp(ltext[3], fontsize=20, color='k') +plt.setp(ltext[0], fontsize=20) +plt.setp(ltext[1], fontsize=20) +plt.setp(ltext[2], fontsize=20) +plt.setp(ltext[3], fontsize=20) # the arrow height = 0.1 diff --git a/examples/statistics/errorbar_limits.py b/examples/statistics/errorbar_limits.py index 502637d611fa..f12e0e3147d9 100644 --- a/examples/statistics/errorbar_limits.py +++ b/examples/statistics/errorbar_limits.py @@ -15,23 +15,21 @@ ax = fig.add_subplot(1, 1, 1) # standard error bars -plt.errorbar(x, y, xerr=xerr, yerr=yerr, ls=ls, color='blue') +plt.errorbar(x, y, xerr=xerr, yerr=yerr, ls=ls) # including upper limits uplims = np.zeros(x.shape) uplims[[1, 5, 9]] = True -plt.errorbar(x, y + 0.5, xerr=xerr, yerr=yerr, uplims=uplims, ls=ls, - color='green') +plt.errorbar(x, y + 0.5, xerr=xerr, yerr=yerr, uplims=uplims, ls=ls) # including lower limits lolims = np.zeros(x.shape) lolims[[2, 4, 8]] = True -plt.errorbar(x, y + 1.0, xerr=xerr, yerr=yerr, lolims=lolims, ls=ls, - color='red') +plt.errorbar(x, y + 1.0, xerr=xerr, yerr=yerr, lolims=lolims, ls=ls) # including upper and lower limits plt.errorbar(x, y + 1.5, marker='o', ms=8, xerr=xerr, yerr=yerr, - lolims=lolims, uplims=uplims, ls=ls, color='magenta') + lolims=lolims, uplims=uplims, ls=ls) # including xlower and xupper limits xerr = 0.2 @@ -45,7 +43,7 @@ uplims[[3]] = True plt.errorbar(x, y + 2.1, marker='o', ms=8, xerr=xerr, yerr=yerr, xlolims=xlolims, xuplims=xuplims, uplims=uplims, lolims=lolims, - ls='none', mec='blue', capsize=0, color='cyan') + ls='none') ax.set_xlim((0, 5.5)) ax.set_title('Errorbar upper and lower limits') diff --git a/examples/statistics/histogram_demo_cumulative.py b/examples/statistics/histogram_demo_cumulative.py index b555f0060eca..23b5c8c93463 100644 --- a/examples/statistics/histogram_demo_cumulative.py +++ b/examples/statistics/histogram_demo_cumulative.py @@ -24,7 +24,6 @@ plt.hist(x, bins=bins, normed=1, histtype='step', cumulative=-1) plt.grid(True) -plt.ylim(0, 1.05) plt.title('cumulative step') plt.show() diff --git a/examples/statistics/histogram_demo_features.py b/examples/statistics/histogram_demo_features.py index 743bb21d39db..32c56cb81d41 100644 --- a/examples/statistics/histogram_demo_features.py +++ b/examples/statistics/histogram_demo_features.py @@ -22,10 +22,10 @@ num_bins = 50 # the histogram of the data -n, bins, patches = plt.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5) +n, bins, patches = plt.hist(x, num_bins, normed=1) # add a 'best fit' line y = mlab.normpdf(bins, mu, sigma) -plt.plot(bins, y, 'r--') +plt.plot(bins, y, '--') plt.xlabel('Smarts') plt.ylabel('Probability') plt.title(r'Histogram of IQ: $\mu=100$, $\sigma=15$') diff --git a/examples/subplots_axes_and_figures/subplot_demo.py b/examples/subplots_axes_and_figures/subplot_demo.py index b90b53d899e9..e00d7cb6f24b 100644 --- a/examples/subplots_axes_and_figures/subplot_demo.py +++ b/examples/subplots_axes_and_figures/subplot_demo.py @@ -12,12 +12,12 @@ y2 = np.cos(2 * np.pi * x2) plt.subplot(2, 1, 1) -plt.plot(x1, y1, 'yo-') +plt.plot(x1, y1, 'o-') plt.title('A tale of 2 subplots') plt.ylabel('Damped oscillation') plt.subplot(2, 1, 2) -plt.plot(x2, y2, 'r.-') +plt.plot(x2, y2, '.-') plt.xlabel('time (s)') plt.ylabel('Undamped') diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py index 87c6158adc82..5ad5df873583 100644 --- a/lib/matplotlib/colors.py +++ b/lib/matplotlib/colors.py @@ -1598,7 +1598,7 @@ def hillshade(self, elevation, vert_exag=1, dx=1, dy=1, fraction=1.): return intensity - def shade(self, data, cmap, norm=None, blend_mode='hsv', vmin=None, + def shade(self, data, cmap, norm=None, blend_mode='overlay', vmin=None, vmax=None, vert_exag=1, dx=1, dy=1, fraction=1, **kwargs): """ Combine colormapped data values with an illumination intensity map @@ -1618,15 +1618,16 @@ def shade(self, data, cmap, norm=None, blend_mode='hsv', vmin=None, The normalization used to scale values before colormapping. If None, the input will be linearly scaled between its min and max. blend_mode : {'hsv', 'overlay', 'soft'} or callable, optional - The type of blending used to combine the colormapped data values - with the illumination intensity. For backwards compatibility, this - defaults to "hsv". Note that for most topographic surfaces, + The type of blending used to combine the colormapped data + values with the illumination intensity. Default is + "overlay". Note that for most topographic surfaces, "overlay" or "soft" appear more visually realistic. If a - user-defined function is supplied, it is expected to combine an - MxNx3 RGB array of floats (ranging 0 to 1) with an MxNx1 hillshade - array (also 0 to 1). (Call signature `func(rgb, illum, **kwargs)`) - Additional kwargs supplied to this function will be passed on to - the *blend_mode* function. + user-defined function is supplied, it is expected to + combine an MxNx3 RGB array of floats (ranging 0 to 1) with + an MxNx1 hillshade array (also 0 to 1). (Call signature + `func(rgb, illum, **kwargs)`) Additional kwargs supplied + to this function will be passed on to the *blend_mode* + function. vmin : scalar or None, optional The minimum value used in colormapping *data*. If *None* the minimum value in *data* is used. If *norm* is specified, then this diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py index 9baf584fb5de..1427f244956b 100644 --- a/lib/matplotlib/image.py +++ b/lib/matplotlib/image.py @@ -734,8 +734,8 @@ class NonUniformImage(AxesImage): def __init__(self, ax, **kwargs): """ kwargs are identical to those for AxesImage, except - that 'interpolation' defaults to 'nearest', and 'bilinear' - is the only alternative. + that 'nearest' and 'bilinear' are the only supported 'interpolation' + options. """ interp = kwargs.pop('interpolation', 'nearest') AxesImage.__init__(self, ax, diff --git a/lib/matplotlib/rcsetup.py b/lib/matplotlib/rcsetup.py index 1977a87a1361..e0d36acbb88a 100644 --- a/lib/matplotlib/rcsetup.py +++ b/lib/matplotlib/rcsetup.py @@ -825,7 +825,7 @@ def validate_hist_bins(s): 'verbose.fileo': ['sys.stdout', six.text_type], # line props - 'lines.linewidth': [1.0, validate_float], # line width in points + 'lines.linewidth': [2.5, validate_float], # line width in points 'lines.linestyle': ['-', six.text_type], # solid line 'lines.color': ['b', validate_color], # blue 'lines.marker': ['None', six.text_type], # black @@ -843,7 +843,7 @@ def validate_hist_bins(s): ## patch props 'patch.linewidth': [None, validate_float_or_None], # line width in points 'patch.edgecolor': ['k', validate_color], # black - 'patch.facecolor': ['b', validate_color], # blue + 'patch.facecolor': ['#1f77b4', validate_color], # blue (first color in color cycle) 'patch.antialiased': [True, validate_bool], # antialiased (no jaggies) ## Histogram properties @@ -939,11 +939,11 @@ def validate_hist_bins(s): 'mathtext.fallback_to_cm': [True, validate_bool], 'image.aspect': ['equal', validate_aspect], # equal, auto, a number - 'image.interpolation': ['bilinear', six.text_type], - 'image.cmap': ['jet', six.text_type], # one of gray, jet, etc + 'image.interpolation': ['nearest', six.text_type], + 'image.cmap': ['viridis', six.text_type], # one of gray, jet, etc 'image.lut': [256, validate_int], # lookup table 'image.origin': ['upper', six.text_type], # lookup table - 'image.resample': [False, validate_bool], + 'image.resample': [True, validate_bool], # Specify whether vector graphics backends will combine all images on a # set of axes into a single composite image 'image.composite_image': [True, validate_bool], @@ -954,7 +954,7 @@ def validate_hist_bins(s): 'contour.corner_mask': [True, validate_corner_mask], # errorbar props - 'errorbar.capsize': [3, validate_float], + 'errorbar.capsize': [0, validate_float], # axes props 'axes.axisbelow': [False, validate_bool], @@ -998,8 +998,12 @@ def validate_hist_bins(s): # This entry can be either a cycler object or a # string repr of a cycler-object, which gets eval()'ed # to create the object. - 'axes.prop_cycle': [ccycler('color', 'bgrcmyk'), - validate_cycler], + 'axes.prop_cycle': [ + ccycler('color', + ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', + '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', + '#bcbd22', '#17becf']), + validate_cycler], # If 'data', axes limits are set close to the data. # If 'round_numbers' axes limits are set to the nearest round numbers. 'axes.autolimit_mode': [ @@ -1024,16 +1028,16 @@ def validate_hist_bins(s): 'date.autoformatter.second': ['%H:%M:%S.%f', six.text_type], #legend properties - 'legend.fancybox': [False, validate_bool], + 'legend.fancybox': [True, validate_bool], # at some point, legend.loc should be changed to 'best' - 'legend.loc': ['upper right', validate_legend_loc], + 'legend.loc': ['best', validate_legend_loc], # this option is internally ignored - it never served any useful purpose 'legend.isaxes': [True, validate_bool], # the number of points in the legend line - 'legend.numpoints': [2, validate_int], + 'legend.numpoints': [1, validate_int], # the number of points in the legend line for scatter 'legend.scatterpoints': [3, validate_int], 'legend.fontsize': ['large', validate_fontsize], @@ -1070,8 +1074,8 @@ def validate_hist_bins(s): 'xtick.bottom': [True, validate_bool], # draw ticks on the bottom side 'xtick.major.size': [4, validate_float], # major xtick size in points 'xtick.minor.size': [2, validate_float], # minor xtick size in points - 'xtick.major.width': [0.5, validate_float], # major xtick width in points - 'xtick.minor.width': [0.5, validate_float], # minor xtick width in points + 'xtick.major.width': [1.0, validate_float], # major xtick width in points + 'xtick.minor.width': [1.0, validate_float], # minor xtick width in points 'xtick.major.pad': [4, validate_float], # distance to label in points 'xtick.minor.pad': [4, validate_float], # distance to label in points 'xtick.color': ['k', validate_color], # color of the xtick labels @@ -1079,14 +1083,14 @@ def validate_hist_bins(s): # fontsize of the xtick labels 'xtick.labelsize': ['medium', validate_fontsize], - 'xtick.direction': ['in', six.text_type], # direction of xticks + 'xtick.direction': ['out', six.text_type], # direction of xticks 'ytick.left': [True, validate_bool], # draw ticks on the left side 'ytick.right': [True, validate_bool], # draw ticks on the right side 'ytick.major.size': [4, validate_float], # major ytick size in points 'ytick.minor.size': [2, validate_float], # minor ytick size in points - 'ytick.major.width': [0.5, validate_float], # major ytick width in points - 'ytick.minor.width': [0.5, validate_float], # minor ytick width in points + 'ytick.major.width': [1.0, validate_float], # major ytick width in points + 'ytick.minor.width': [1.0, validate_float], # minor ytick width in points 'ytick.major.pad': [4, validate_float], # distance to label in points 'ytick.minor.pad': [4, validate_float], # distance to label in points 'ytick.color': ['k', validate_color], # color of the ytick labels @@ -1094,11 +1098,11 @@ def validate_hist_bins(s): # fontsize of the ytick labels 'ytick.labelsize': ['medium', validate_fontsize], - 'ytick.direction': ['in', six.text_type], # direction of yticks + 'ytick.direction': ['out', six.text_type], # direction of yticks - 'grid.color': ['k', validate_color], # grid color - 'grid.linestyle': [':', six.text_type], # dotted - 'grid.linewidth': [0.5, validate_float], # in points + 'grid.color': ['#b0b0b0', validate_color], # grid color + 'grid.linestyle': ['-', six.text_type], # solid + 'grid.linewidth': [1.0, validate_float], # in points 'grid.alpha': [1.0, validate_float], @@ -1110,7 +1114,7 @@ def validate_hist_bins(s): # figure size in inches: width by height 'figure.figsize': [[8.0, 6.0], validate_nseq_float(2)], 'figure.dpi': [100, validate_float], # DPI - 'figure.facecolor': ['0.75', validate_color], # facecolor; scalar gray + 'figure.facecolor': ['w', validate_color], # facecolor; white 'figure.edgecolor': ['w', validate_color], # edgecolor; white 'figure.frameon': [True, validate_bool], 'figure.autolayout': [False, validate_bool], diff --git a/lib/matplotlib/tests/baseline_images/test_artist/default_edges.png b/lib/matplotlib/tests/baseline_images/test_artist/default_edges.png index 612eb3dd3c48..27c3d8273233 100644 Binary files a/lib/matplotlib/tests/baseline_images/test_artist/default_edges.png and b/lib/matplotlib/tests/baseline_images/test_artist/default_edges.png differ diff --git a/lib/matplotlib/tests/baseline_images/test_axes/auto_numticks.png b/lib/matplotlib/tests/baseline_images/test_axes/auto_numticks.png index 91d220768457..c1ff468c2954 100644 Binary files a/lib/matplotlib/tests/baseline_images/test_axes/auto_numticks.png and b/lib/matplotlib/tests/baseline_images/test_axes/auto_numticks.png differ diff --git a/lib/matplotlib/tests/baseline_images/test_axes/markevery.pdf b/lib/matplotlib/tests/baseline_images/test_axes/markevery.pdf index 009d8e0cbc48..8a2a4887d2d7 100644 Binary files a/lib/matplotlib/tests/baseline_images/test_axes/markevery.pdf and b/lib/matplotlib/tests/baseline_images/test_axes/markevery.pdf differ diff --git a/lib/matplotlib/tests/baseline_images/test_axes/markevery.svg b/lib/matplotlib/tests/baseline_images/test_axes/markevery.svg index 71cae974f072..283ccf567d4c 100644 --- a/lib/matplotlib/tests/baseline_images/test_axes/markevery.svg +++ b/lib/matplotlib/tests/baseline_images/test_axes/markevery.svg @@ -38,109 +38,109 @@ C -2.683901 -1.55874 -3 -0.795609 -3 0 C -3 0.795609 -2.683901 1.55874 -2.12132 2.12132 C -1.55874 2.683901 -0.795609 3 0 3 z -" id="m7012dc2431" style="stroke:#000000;stroke-width:0.500000;"/> +" id="m19995b3cae" style="stroke:#000000;stroke-width:0.5;"/> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -150,109 +150,109 @@ L 2.545584 0 L 0 -4.242641 L -2.545584 -0 z -" id="mff394ba7f2" style="stroke:#000000;stroke-linejoin:miter;stroke-width:0.500000;"/> +" id="m5310570bd3" style="stroke:#000000;stroke-linejoin:miter;stroke-width:0.5;"/> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -262,19 +262,19 @@ L 3 3 L 3 -3 L -3 -3 z -" id="mc8ace52358" style="stroke:#000000;stroke-linejoin:miter;stroke-width:0.500000;"/> +" id="m10b9748a1a" style="stroke:#000000;stroke-linejoin:miter;stroke-width:0.5;"/> - - - - - - - - - - - + + + + + + + + + + + @@ -283,14 +283,14 @@ z L 3 0 M 0 3 L 0 -3 -" id="m91198510cc" style="stroke:#00bfbf;stroke-width:0.500000;"/> +" id="m41da80ca8e" style="stroke:#00bfbf;stroke-width:0.5;"/> - - - - - - + + + + + + @@ -319,80 +319,80 @@ L 518.4 43.2 +" id="ma0952b939b" style="stroke:#000000;stroke-width:0.5;"/> - + +" id="mde7172798e" style="stroke:#000000;stroke-width:0.5;"/> - + - + - + - + - + - + - + - + - + - + - + @@ -403,80 +403,80 @@ L 0 4 +" id="mbe1077638f" style="stroke:#000000;stroke-width:0.5;"/> - + +" id="m33e20e690d" style="stroke:#000000;stroke-width:0.5;"/> - + - + - + - + - + - + - + - + - + - + - + @@ -493,8 +493,8 @@ z - - + + @@ -645,21 +645,21 @@ L 9.28125 70.21875 z " id="DejaVuSans-74"/> - + - - - + + + - - + + - - + + @@ -725,22 +725,22 @@ z " id="DejaVuSans-6b"/> - + - - - - - + + + + + - + - - + + @@ -804,27 +804,27 @@ Q 6.59375 54.828125 13.0625 64.515625 Q 19.53125 74.21875 31.78125 74.21875 " id="DejaVuSans-30"/> - + - - - - - - - - - - - - + + + + + + + + + + + + - - + + @@ -946,33 +946,33 @@ L 54.390625 54.6875 z " id="DejaVuSans-67"/> - + - - - - - - - - - - - - + + + + + + + + + + + + - - - - - - - - - - - - + + + + + + + + + + + + @@ -980,8 +980,8 @@ z - - + + diff --git a/lib/matplotlib/tests/baseline_images/test_axes/markevery_line.pdf b/lib/matplotlib/tests/baseline_images/test_axes/markevery_line.pdf index 6087ecd1e56a..9bff9fcd374d 100644 Binary files a/lib/matplotlib/tests/baseline_images/test_axes/markevery_line.pdf and b/lib/matplotlib/tests/baseline_images/test_axes/markevery_line.pdf differ diff --git a/lib/matplotlib/tests/baseline_images/test_axes/markevery_line.svg b/lib/matplotlib/tests/baseline_images/test_axes/markevery_line.svg index d964e5bbaf77..c7534826bab5 100644 --- a/lib/matplotlib/tests/baseline_images/test_axes/markevery_line.svg +++ b/lib/matplotlib/tests/baseline_images/test_axes/markevery_line.svg @@ -27,7 +27,7 @@ z " style="fill:#ffffff;"/> - +" id="m2fc0b09e3a" style="stroke:#000000;stroke-width:0.5;"/> - 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- + - + - + - + - + - + - + - + - + - + - + +" style="fill:#0000ff;stroke:#000000;stroke-width:0.5;"/> +" id="md9645c3112" style="stroke:#000000;stroke-width:0.5;"/> - + +" id="mff0e058049" style="stroke:#000000;stroke-width:0.5;"/> - + @@ -224,22 +224,22 @@ L 10.6875 0 z " id="DejaVuSans-2e"/> - + - - + + - + - + @@ -270,22 +270,22 @@ Q 14.890625 38.140625 10.796875 36.28125 z " id="DejaVuSans-35"/> - + - - + + - + - + @@ -305,42 +305,42 @@ L 12.40625 0 z " id="DejaVuSans-31"/> - + - - + + - + - + - + - - + + - + - + @@ -370,42 +370,42 @@ Q 44.1875 33.984375 37.640625 27.21875 Q 31.109375 20.453125 19.1875 8.296875 " id="DejaVuSans-32"/> - + - - + + - + - + - + - - + + - + - + @@ -443,42 +443,42 @@ Q 53.90625 49.265625 50.4375 45.09375 Q 46.96875 40.921875 40.578125 39.3125 " id="DejaVuSans-33"/> - + - - + + - + - + - + - - + + - + - + @@ -502,10 +502,10 @@ L 4.890625 26.703125 z " id="DejaVuSans-34"/> - + - - + + @@ -516,188 +516,188 @@ z +" id="mca48cf166e" style="stroke:#000000;stroke-width:0.5;"/> - 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+ - + - + - + @@ -3685,21 +3685,21 @@ Q 44.1875 33.984375 37.640625 27.21875 Q 31.109375 20.453125 19.1875 8.296875 " id="DejaVuSans-32"/> - + - + - + - + @@ -3719,21 +3719,21 @@ L 12.40625 0 z " id="DejaVuSans-31"/> - + - + - + - + @@ -3759,7 +3759,7 @@ Q 6.59375 54.828125 13.0625 64.515625 Q 19.53125 74.21875 31.78125 74.21875 " id="DejaVuSans-30"/> - + @@ -3767,17 +3767,17 @@ Q 19.53125 74.21875 31.78125 74.21875 - + - + - + @@ -3785,17 +3785,17 @@ Q 19.53125 74.21875 31.78125 74.21875 - + - + - + @@ -3803,17 +3803,17 @@ Q 19.53125 74.21875 31.78125 74.21875 - + - + - + @@ -3825,82 +3825,82 @@ Q 19.53125 74.21875 31.78125 74.21875 +" id="m74778f61cf" style="stroke:#000000;stroke-width:0.5;"/> - + +" id="m71bffc4b38" style="stroke:#000000;stroke-width:0.5;"/> - + - + - + - + - + - + - + - + - + - + - + - + - + - + @@ -3908,17 +3908,17 @@ L -4 0 - + - + - + @@ -3926,17 +3926,17 @@ L -4 0 - + - + - + @@ -3944,17 +3944,17 @@ L -4 0 - + - + - + @@ -3963,8 +3963,8 @@ L -4 0 - - + + diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py index c9166a5a7db3..e440f07c4867 100644 --- a/lib/matplotlib/tests/test_colors.py +++ b/lib/matplotlib/tests/test_colors.py @@ -352,41 +352,44 @@ def test_light_source_shading_default(): rgb = ls.shade(z, cmap) # Result stored transposed and rounded for for more compact display... - expect = np.array([[[0.87, 0.85, 0.90, 0.90, 0.82, 0.62, 0.34, 0.00], - [0.85, 0.94, 0.99, 1.00, 1.00, 0.96, 0.62, 0.17], - [0.90, 0.99, 1.00, 1.00, 1.00, 1.00, 0.71, 0.33], - [0.90, 1.00, 1.00, 1.00, 1.00, 0.98, 0.51, 0.29], - [0.82, 1.00, 1.00, 1.00, 1.00, 0.64, 0.25, 0.13], - [0.62, 0.96, 1.00, 0.98, 0.64, 0.22, 0.06, 0.03], - [0.34, 0.62, 0.71, 0.51, 0.25, 0.06, 0.00, 0.01], - [0.00, 0.17, 0.33, 0.29, 0.13, 0.03, 0.01, 0.00]], - - [[0.87, 0.79, 0.83, 0.80, 0.66, 0.44, 0.23, 0.00], - [0.79, 0.88, 0.93, 0.92, 0.83, 0.66, 0.38, 0.10], - [0.83, 0.93, 0.99, 1.00, 0.92, 0.75, 0.40, 0.18], - [0.80, 0.92, 1.00, 0.99, 0.93, 0.75, 0.28, 0.14], - [0.66, 0.83, 0.92, 0.93, 0.87, 0.44, 0.12, 0.06], - [0.44, 0.66, 0.75, 0.75, 0.44, 0.12, 0.03, 0.01], - [0.23, 0.38, 0.40, 0.28, 0.12, 0.03, 0.00, 0.00], - [0.00, 0.10, 0.18, 0.14, 0.06, 0.01, 0.00, 0.00]], - - [[0.87, 0.75, 0.78, 0.73, 0.55, 0.33, 0.16, 0.00], - [0.75, 0.85, 0.90, 0.86, 0.71, 0.48, 0.23, 0.05], - [0.78, 0.90, 0.98, 1.00, 0.82, 0.51, 0.21, 0.08], - [0.73, 0.86, 1.00, 0.97, 0.84, 0.47, 0.11, 0.05], - [0.55, 0.71, 0.82, 0.84, 0.71, 0.20, 0.03, 0.01], - [0.33, 0.48, 0.51, 0.47, 0.20, 0.02, 0.00, 0.00], - [0.16, 0.23, 0.21, 0.11, 0.03, 0.00, 0.00, 0.00], - [0.00, 0.05, 0.08, 0.05, 0.01, 0.00, 0.00, 0.00]], - - [[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00]]]).T + expect = np.array( + [[[0.00, 0.45, 0.90, 0.90, 0.82, 0.62, 0.28, 0.00], + [0.45, 0.94, 0.99, 1.00, 1.00, 0.96, 0.65, 0.17], + [0.90, 0.99, 1.00, 1.00, 1.00, 1.00, 0.94, 0.35], + [0.90, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 0.49], + [0.82, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 0.41], + [0.62, 0.96, 1.00, 1.00, 1.00, 1.00, 0.90, 0.07], + [0.28, 0.65, 0.94, 1.00, 1.00, 0.90, 0.35, 0.01], + [0.00, 0.17, 0.35, 0.49, 0.41, 0.07, 0.01, 0.00]], + + [[0.00, 0.28, 0.59, 0.72, 0.62, 0.40, 0.18, 0.00], + [0.28, 0.78, 0.93, 0.92, 0.83, 0.66, 0.39, 0.11], + [0.59, 0.93, 0.99, 1.00, 0.92, 0.75, 0.50, 0.21], + [0.72, 0.92, 1.00, 0.99, 0.93, 0.76, 0.51, 0.18], + [0.62, 0.83, 0.92, 0.93, 0.87, 0.68, 0.42, 0.08], + [0.40, 0.66, 0.75, 0.76, 0.68, 0.52, 0.23, 0.02], + [0.18, 0.39, 0.50, 0.51, 0.42, 0.23, 0.00, 0.00], + [0.00, 0.11, 0.21, 0.18, 0.08, 0.02, 0.00, 0.00]], + + [[0.00, 0.18, 0.38, 0.46, 0.39, 0.26, 0.11, 0.00], + [0.18, 0.50, 0.70, 0.75, 0.64, 0.44, 0.25, 0.07], + [0.38, 0.70, 0.91, 0.98, 0.81, 0.51, 0.29, 0.13], + [0.46, 0.75, 0.98, 0.96, 0.84, 0.48, 0.22, 0.12], + [0.39, 0.64, 0.81, 0.84, 0.71, 0.31, 0.11, 0.05], + [0.26, 0.44, 0.51, 0.48, 0.31, 0.10, 0.03, 0.01], + [0.11, 0.25, 0.29, 0.22, 0.11, 0.03, 0.00, 0.00], + [0.00, 0.07, 0.13, 0.12, 0.05, 0.01, 0.00, 0.00]], + + [[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00]] + ]).T + if (V(np.__version__) == V('1.9.0')): # Numpy 1.9.0 uses a 2. order algorithm on the edges by default # This was changed back again in 1.9.1 @@ -414,41 +417,43 @@ def test_light_source_masked_shading(): rgb = ls.shade(z, cmap) # Result stored transposed and rounded for for more compact display... - expect = np.array([[[0.90, 0.88, 0.91, 0.91, 0.84, 0.64, 0.36, 0.00], - [0.88, 0.96, 1.00, 1.00, 1.00, 0.97, 0.64, 0.18], - [0.91, 1.00, 1.00, 1.00, 1.00, 1.00, 0.74, 0.34], - [0.91, 1.00, 1.00, 0.00, 0.00, 1.00, 0.52, 0.30], - [0.84, 1.00, 1.00, 0.00, 0.00, 1.00, 0.25, 0.13], - [0.64, 0.97, 1.00, 1.00, 1.00, 0.23, 0.07, 0.03], - [0.36, 0.64, 0.74, 0.52, 0.25, 0.07, 0.00, 0.01], - [0.00, 0.18, 0.34, 0.30, 0.13, 0.03, 0.01, 0.00]], - - [[0.90, 0.82, 0.85, 0.82, 0.68, 0.46, 0.24, 0.00], - [0.82, 0.91, 0.95, 0.93, 0.85, 0.68, 0.39, 0.10], - [0.85, 0.95, 1.00, 0.78, 0.78, 0.77, 0.42, 0.18], - [0.82, 0.93, 0.78, 0.00, 0.00, 0.78, 0.30, 0.15], - [0.68, 0.85, 0.78, 0.00, 0.00, 0.78, 0.13, 0.06], - [0.46, 0.68, 0.77, 0.78, 0.78, 0.13, 0.03, 0.01], - [0.24, 0.39, 0.42, 0.30, 0.13, 0.03, 0.00, 0.00], - [0.00, 0.10, 0.18, 0.15, 0.06, 0.01, 0.00, 0.00]], - - [[0.90, 0.79, 0.81, 0.76, 0.58, 0.35, 0.17, 0.00], - [0.79, 0.88, 0.92, 0.88, 0.73, 0.50, 0.24, 0.05], - [0.81, 0.92, 1.00, 0.50, 0.50, 0.53, 0.22, 0.09], - [0.76, 0.88, 0.50, 0.00, 0.00, 0.50, 0.12, 0.05], - [0.58, 0.73, 0.50, 0.00, 0.00, 0.50, 0.03, 0.01], - [0.35, 0.50, 0.53, 0.50, 0.50, 0.02, 0.00, 0.00], - [0.17, 0.24, 0.22, 0.12, 0.03, 0.00, 0.00, 0.00], - [0.00, 0.05, 0.09, 0.05, 0.01, 0.00, 0.00, 0.00]], - - [[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], - [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00]]]).T + expect = np.array( + [[[0.00, 0.46, 0.91, 0.91, 0.84, 0.64, 0.29, 0.00], + [0.46, 0.96, 1.00, 1.00, 1.00, 0.97, 0.67, 0.18], + [0.91, 1.00, 1.00, 1.00, 1.00, 1.00, 0.96, 0.36], + [0.91, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 0.51], + [0.84, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 0.44], + [0.64, 0.97, 1.00, 1.00, 1.00, 1.00, 0.94, 0.09], + [0.29, 0.67, 0.96, 1.00, 1.00, 0.94, 0.38, 0.01], + [0.00, 0.18, 0.36, 0.51, 0.44, 0.09, 0.01, 0.00]], + + [[0.00, 0.29, 0.61, 0.75, 0.64, 0.41, 0.18, 0.00], + [0.29, 0.81, 0.95, 0.93, 0.85, 0.68, 0.40, 0.11], + [0.61, 0.95, 1.00, 0.78, 0.78, 0.77, 0.52, 0.22], + [0.75, 0.93, 0.78, 0.00, 0.00, 0.78, 0.54, 0.19], + [0.64, 0.85, 0.78, 0.00, 0.00, 0.78, 0.45, 0.08], + [0.41, 0.68, 0.77, 0.78, 0.78, 0.55, 0.25, 0.02], + [0.18, 0.40, 0.52, 0.54, 0.45, 0.25, 0.00, 0.00], + [0.00, 0.11, 0.22, 0.19, 0.08, 0.02, 0.00, 0.00]], + + [[0.00, 0.19, 0.39, 0.48, 0.41, 0.26, 0.12, 0.00], + [0.19, 0.52, 0.73, 0.78, 0.66, 0.46, 0.26, 0.07], + [0.39, 0.73, 0.95, 0.50, 0.50, 0.53, 0.30, 0.14], + [0.48, 0.78, 0.50, 0.00, 0.00, 0.50, 0.23, 0.12], + [0.41, 0.66, 0.50, 0.00, 0.00, 0.50, 0.11, 0.05], + [0.26, 0.46, 0.53, 0.50, 0.50, 0.11, 0.03, 0.01], + [0.12, 0.26, 0.30, 0.23, 0.11, 0.03, 0.00, 0.00], + [0.00, 0.07, 0.14, 0.12, 0.05, 0.01, 0.00, 0.00]], + + [[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00], + [1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00]], + ]).T assert_array_almost_equal(rgb, expect, decimal=2) diff --git a/lib/mpl_toolkits/tests/baseline_images/test_axes_grid1/inset_locator.png b/lib/mpl_toolkits/tests/baseline_images/test_axes_grid1/inset_locator.png index 541d36788674..a89e0e4a272d 100644 Binary files a/lib/mpl_toolkits/tests/baseline_images/test_axes_grid1/inset_locator.png and b/lib/mpl_toolkits/tests/baseline_images/test_axes_grid1/inset_locator.png differ diff --git a/matplotlibrc.template b/matplotlibrc.template index f52ea5794772..7504f04ae54f 100644 --- a/matplotlibrc.template +++ b/matplotlibrc.template @@ -59,7 +59,7 @@ backend : $TEMPLATE_BACKEND # When True, the figures rendered in the nbagg backend are created with # a transparent background. -# nbagg.transparent : True +# nbagg.transparent : False # if you are running pyplot inside a GUI and your backend choice # conflicts, we will automatically try to find a compatible one for @@ -78,7 +78,7 @@ backend : $TEMPLATE_BACKEND ### LINES # See http://matplotlib.org/api/artist_api.html#module-matplotlib.lines for more # information on line properties. -#lines.linewidth : 1.0 # line width in points +#lines.linewidth : 2.0 # line width in points #lines.linestyle : - # solid line #lines.color : blue # has no affect on plot(); see axes.prop_cycle #lines.marker : None # the default marker @@ -100,7 +100,7 @@ backend : $TEMPLATE_BACKEND #patch.linewidth : None # edge width in points. # If None, use axes.linewidth when patch # is not filled. -#patch.facecolor : b +#patch.facecolor : #1f77b4 #patch.edgecolor : black #patch.antialiased : True # render patches in antialiased (no jaggies) @@ -315,7 +315,10 @@ backend : $TEMPLATE_BACKEND #axes.unicode_minus : True # use unicode for the minus symbol # rather than hyphen. See # http://en.wikipedia.org/wiki/Plus_and_minus_signs#Character_codes -#axes.prop_cycle : cycler('color', 'bgrcmyk') +#axes.prop_cycle : cycler('color', +# ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', +# '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', +# '#bcbd22', '#17becf']) # color cycle for plot lines # as list of string colorspecs: # single letter, long name, or @@ -347,44 +350,45 @@ backend : $TEMPLATE_BACKEND ### TICKS # see http://matplotlib.org/api/axis_api.html#matplotlib.axis.Tick - #xtick.top : True # draw ticks on the top side #xtick.bottom : True # draw ticks on the bottom side #xtick.major.size : 4 # major tick size in points #xtick.minor.size : 2 # minor tick size in points -#xtick.major.width : 0.5 # major tick width in points -#xtick.minor.width : 0.5 # minor tick width in points +#xtick.major.width : 1.0 # major tick width in points +#xtick.minor.width : 1.0 # minor tick width in points #xtick.major.pad : 4 # distance to major tick label in points #xtick.minor.pad : 4 # distance to the minor tick label in points #xtick.color : k # color of the tick labels #xtick.labelsize : medium # fontsize of the tick labels -#xtick.direction : in # direction: in, out, or inout - +#xtick.direction : out # direction: in, out, or inout +#xtick.minor.visible : False # visibility of minor ticks on x-axis #ytick.left : True # draw ticks on the left side #ytick.right : True # draw ticks on the right side #ytick.major.size : 4 # major tick size in points #ytick.minor.size : 2 # minor tick size in points -#ytick.major.width : 0.5 # major tick width in points -#ytick.minor.width : 0.5 # minor tick width in points +#ytick.major.width : 1.0 # major tick width in points +#ytick.minor.width : 1.0 # minor tick width in points #ytick.major.pad : 4 # distance to major tick label in points #ytick.minor.pad : 4 # distance to the minor tick label in points #ytick.color : k # color of the tick labels #ytick.labelsize : medium # fontsize of the tick labels -#ytick.direction : in # direction: in, out, or inout +#ytick.direction : out # direction: in, out, or inout +#ytick.minor.visible : False # visibility of minor ticks on y-axis ### GRIDS -#grid.color : black # grid color -#grid.linestyle : : # dotted -#grid.linewidth : 0.5 # in points -#grid.alpha : 1.0 # transparency, between 0.0 and 1.0 +#grid.color : '#b0b0b0' # grid color +#grid.linestyle : - # solid +#grid.linewidth : 1.0 # in points +#grid.alpha : 1.0 # transparency, between 0.0 and 1.0 ### Legend -#legend.fancybox : False # if True, use a rounded box for the - # legend, else a rectangle +#legend.fancybox : True # if True, use a rounded box for the + # legend, else a rectangle +#legend.loc : best #legend.isaxes : True -#legend.numpoints : 2 # the number of points in the legend line +#legend.numpoints : 1 # the number of points in the legend line #legend.fontsize : large #legend.borderpad : 0.5 # border whitespace in fontsize units #legend.markerscale : 1.0 # the relative size of legend markers vs. original @@ -407,8 +411,8 @@ backend : $TEMPLATE_BACKEND #figure.titlesize : medium # size of the figure title #figure.titleweight : normal # weight of the figure title #figure.figsize : 8, 6 # figure size in inches -#figure.dpi : 100 # figure dots per inch -#figure.facecolor : 0.75 # figure facecolor; 0.75 is scalar gray +#figure.dpi : 100 # figure dots per inch +#figure.facecolor : white # figure facecolor; 0.75 is scalar gray #figure.edgecolor : white # figure edgecolor #figure.autolayout : False # When True, automatically adjust subplot # parameters to make the plot fit the figure @@ -427,11 +431,11 @@ backend : $TEMPLATE_BACKEND ### IMAGES #image.aspect : equal # equal | auto | a number -#image.interpolation : bilinear # see help(imshow) for options -#image.cmap : jet # gray | jet etc... +#image.interpolation : nearest # see help(imshow) for options +#image.cmap : viridis # A colormap name, gray etc... #image.lut : 256 # the size of the colormap lookup table #image.origin : upper # lower | upper -#image.resample : False +#image.resample : True #image.composite_image : True # When True, all the images on a set of axes are # combined into a single composite image before # saving a figure as a vector graphics file, @@ -442,7 +446,7 @@ backend : $TEMPLATE_BACKEND #contour.corner_mask : True # True | False | legacy ### ERRORBAR PLOTS -#errorbar.capsize : 3 # length of end cap on error bars in pixels +#errorbar.capsize : 0 # length of end cap on error bars in pixels ### HISTOGRAM PLOTS #hist.bins : 10 # The default number of histogram bins. pFad - Phonifier reborn

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