from io import BytesIO import pickle import platform import numpy as np import pytest from matplotlib import cm from matplotlib.testing.decorators import image_comparison from matplotlib.dates import rrulewrapper import matplotlib.pyplot as plt import matplotlib.transforms as mtransforms import matplotlib.figure as mfigure def test_simple(): fig = plt.figure() pickle.dump(fig, BytesIO(), pickle.HIGHEST_PROTOCOL) ax = plt.subplot(121) pickle.dump(ax, BytesIO(), pickle.HIGHEST_PROTOCOL) ax = plt.axes(projection='polar') plt.plot(np.arange(10), label='foobar') plt.legend() pickle.dump(ax, BytesIO(), pickle.HIGHEST_PROTOCOL) # ax = plt.subplot(121, projection='hammer') # pickle.dump(ax, BytesIO(), pickle.HIGHEST_PROTOCOL) plt.figure() plt.bar(x=np.arange(10), height=np.arange(10)) pickle.dump(plt.gca(), BytesIO(), pickle.HIGHEST_PROTOCOL) fig = plt.figure() ax = plt.axes() plt.plot(np.arange(10)) ax.set_yscale('log') pickle.dump(fig, BytesIO(), pickle.HIGHEST_PROTOCOL) @image_comparison(['multi_pickle.png'], remove_text=True, style='mpl20', tol=0 if platform.machine() == 'x86_64' else 0.082) def test_complete(): fig = plt.figure('Figure with a label?', figsize=(10, 6)) plt.suptitle('Can you fit any more in a figure?') # make some arbitrary data x, y = np.arange(8), np.arange(10) data = u = v = np.linspace(0, 10, 80).reshape(10, 8) v = np.sin(v * -0.6) # Ensure lists also pickle correctly. plt.subplot(3, 3, 1) plt.plot(list(range(10))) plt.subplot(3, 3, 2) plt.contourf(data, hatches=['//', 'ooo']) plt.colorbar() plt.subplot(3, 3, 3) plt.pcolormesh(data) plt.subplot(3, 3, 4) plt.imshow(data) plt.subplot(3, 3, 5) plt.pcolor(data) ax = plt.subplot(3, 3, 6) ax.set_xlim(0, 7) ax.set_ylim(0, 9) plt.streamplot(x, y, u, v) ax = plt.subplot(3, 3, 7) ax.set_xlim(0, 7) ax.set_ylim(0, 9) plt.quiver(x, y, u, v) plt.subplot(3, 3, 8) plt.scatter(x, x**2, label='$x^2$') plt.legend(loc='upper left') plt.subplot(3, 3, 9) plt.errorbar(x, x * -0.5, xerr=0.2, yerr=0.4) # # plotting is done, now test its pickle-ability # result_fh = BytesIO() pickle.dump(fig, result_fh, pickle.HIGHEST_PROTOCOL) plt.close('all') # make doubly sure that there are no figures left assert plt._pylab_helpers.Gcf.figs == {} # wind back the fh and load in the figure result_fh.seek(0) fig = pickle.load(result_fh) # make sure there is now a figure manager assert plt._pylab_helpers.Gcf.figs != {} assert fig.get_label() == 'Figure with a label?' def test_no_pyplot(): # tests pickle-ability of a figure not created with pyplot from matplotlib.backends.backend_pdf import FigureCanvasPdf fig = mfigure.Figure() _ = FigureCanvasPdf(fig) ax = fig.add_subplot(1, 1, 1) ax.plot([1, 2, 3], [1, 2, 3]) pickle.dump(fig, BytesIO(), pickle.HIGHEST_PROTOCOL) def test_renderer(): from matplotlib.backends.backend_agg import RendererAgg renderer = RendererAgg(10, 20, 30) pickle.dump(renderer, BytesIO()) def test_image(): # Prior to v1.4.0 the Image would cache data which was not picklable # once it had been drawn. from matplotlib.backends.backend_agg import new_figure_manager manager = new_figure_manager(1000) fig = manager.canvas.figure ax = fig.add_subplot(1, 1, 1) ax.imshow(np.arange(12).reshape(3, 4)) manager.canvas.draw() pickle.dump(fig, BytesIO()) def test_polar(): plt.subplot(111, polar=True) fig = plt.gcf() pf = pickle.dumps(fig) pickle.loads(pf) plt.draw() class TransformBlob: def __init__(self): self.identity = mtransforms.IdentityTransform() self.identity2 = mtransforms.IdentityTransform() # Force use of the more complex composition. self.composite = mtransforms.CompositeGenericTransform( self.identity, self.identity2) # Check parent -> child links of TransformWrapper. self.wrapper = mtransforms.TransformWrapper(self.composite) # Check child -> parent links of TransformWrapper. self.composite2 = mtransforms.CompositeGenericTransform( self.wrapper, self.identity) def test_transform(): obj = TransformBlob() pf = pickle.dumps(obj) del obj obj = pickle.loads(pf) # Check parent -> child links of TransformWrapper. assert obj.wrapper._child == obj.composite # Check child -> parent links of TransformWrapper. assert [v() for v in obj.wrapper._parents.values()] == [obj.composite2] # Check input and output dimensions are set as expected. assert obj.wrapper.input_dims == obj.composite.input_dims assert obj.wrapper.output_dims == obj.composite.output_dims def test_rrulewrapper(): r = rrulewrapper(2) try: pickle.loads(pickle.dumps(r)) except RecursionError: print('rrulewrapper pickling test failed') raise def test_shared(): fig, axs = plt.subplots(2, sharex=True) fig = pickle.loads(pickle.dumps(fig)) fig.axes[0].set_xlim(10, 20) assert fig.axes[1].get_xlim() == (10, 20) @pytest.mark.parametrize("cmap", cm._cmap_registry.values()) def test_cmap(cmap): pickle.dumps(cmap) def test_unpickle_canvas(): fig = mfigure.Figure() assert fig.canvas is not None out = BytesIO() pickle.dump(fig, out) out.seek(0) fig2 = pickle.load(out) assert fig2.canvas is not None