from io import BytesIO import numpy as np from matplotlib.testing.decorators import image_comparison import matplotlib.pyplot as plt import matplotlib.path as mpath import matplotlib.patches as mpatches from matplotlib.ticker import FuncFormatter @image_comparison(['bbox_inches_tight'], remove_text=True, savefig_kwarg={'bbox_inches': 'tight'}) def test_bbox_inches_tight(): #: Test that a figure saved using bbox_inches='tight' is clipped correctly data = [[66386, 174296, 75131, 577908, 32015], [58230, 381139, 78045, 99308, 160454], [89135, 80552, 152558, 497981, 603535], [78415, 81858, 150656, 193263, 69638], [139361, 331509, 343164, 781380, 52269]] colLabels = rowLabels = [''] * 5 rows = len(data) ind = np.arange(len(colLabels)) + 0.3 # the x locations for the groups cellText = [] width = 0.4 # the width of the bars yoff = np.zeros(len(colLabels)) # the bottom values for stacked bar chart fig, ax = plt.subplots(1, 1) for row in range(rows): ax.bar(ind, data[row], width, bottom=yoff, align='edge', color='b') yoff = yoff + data[row] cellText.append(['']) plt.xticks([]) plt.xlim(0, 5) plt.legend([''] * 5, loc=(1.2, 0.2)) fig.legend([''] * 5, bbox_to_anchor=(0, 0.2), loc='lower left') # Add a table at the bottom of the axes cellText.reverse() plt.table(cellText=cellText, rowLabels=rowLabels, colLabels=colLabels, loc='bottom') @image_comparison(['bbox_inches_tight_suptile_legend'], remove_text=False, savefig_kwarg={'bbox_inches': 'tight'}) def test_bbox_inches_tight_suptile_legend(): plt.plot(np.arange(10), label='a straight line') plt.legend(bbox_to_anchor=(0.9, 1), loc='upper left') plt.title('Axis title') plt.suptitle('Figure title') # put an extra long y tick on to see that the bbox is accounted for def y_formatter(y, pos): if int(y) == 4: return 'The number 4' else: return str(y) plt.gca().yaxis.set_major_formatter(FuncFormatter(y_formatter)) plt.xlabel('X axis') @image_comparison(['bbox_inches_tight_clipping'], remove_text=True, savefig_kwarg={'bbox_inches': 'tight'}) def test_bbox_inches_tight_clipping(): # tests bbox clipping on scatter points, and path clipping on a patch # to generate an appropriately tight bbox plt.scatter(np.arange(10), np.arange(10)) ax = plt.gca() ax.set_xlim([0, 5]) ax.set_ylim([0, 5]) # make a massive rectangle and clip it with a path patch = mpatches.Rectangle([-50, -50], 100, 100, transform=ax.transData, facecolor='blue', alpha=0.5) path = mpath.Path.unit_regular_star(5).deepcopy() path.vertices *= 0.25 patch.set_clip_path(path, transform=ax.transAxes) plt.gcf().artists.append(patch) @image_comparison(['bbox_inches_tight_raster'], remove_text=True, savefig_kwarg={'bbox_inches': 'tight'}) def test_bbox_inches_tight_raster(): """Test rasterization with tight_layout""" fig = plt.figure() ax = fig.add_subplot(111) ax.plot([1.0, 2.0], rasterized=True) def test_only_on_non_finite_bbox(): fig, ax = plt.subplots() ax.annotate("", xy=(0, float('nan'))) ax.set_axis_off() # we only need to test that it does not error out on save fig.savefig(BytesIO(), bbox_inches='tight', format='png') def test_tight_pcolorfast(): fig, ax = plt.subplots() ax.pcolorfast(np.arange(4).reshape((2, 2))) ax.set(ylim=(0, .1)) buf = BytesIO() fig.savefig(buf, bbox_inches="tight") buf.seek(0) height, width, _ = plt.imread(buf).shape # Previously, the bbox would include the area of the image clipped out by # the axes, resulting in a very tall image given the y limits of (0, 0.1). assert width > height def test_noop_tight_bbox(): from PIL import Image x_size, y_size = (10, 7) dpi = 100 # make the figure just the right size up front fig = plt.figure(frameon=False, dpi=dpi, figsize=(x_size/dpi, y_size/dpi)) ax = plt.Axes(fig, [0., 0., 1., 1.]) fig.add_axes(ax) ax.set_axis_off() ax.get_xaxis().set_visible(False) ax.get_yaxis().set_visible(False) data = np.arange(x_size * y_size).reshape(y_size, x_size) ax.imshow(data, rasterized=True) # When a rasterized Artist is included, a mixed-mode renderer does # additional bbox adjustment. It should also be a no-op, and not affect the # next save. fig.savefig(BytesIO(), bbox_inches='tight', pad_inches=0, format='pdf') out = BytesIO() fig.savefig(out, bbox_inches='tight', pad_inches=0) out.seek(0) im = np.asarray(Image.open(out)) assert (im[:, :, 3] == 255).all() assert not (im[:, :, :3] == 255).all() assert im.shape == (7, 10, 4)