ai-content-maker/.venv/Lib/site-packages/matplotlib/tests/test_pickle.py

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2024-05-03 04:18:51 +03:00
from io import BytesIO
import ast
import pickle
import pickletools
import numpy as np
import pytest
import matplotlib as mpl
from matplotlib import cm
from matplotlib.testing import subprocess_run_helper
from matplotlib.testing.decorators import check_figures_equal
from matplotlib.dates import rrulewrapper
from matplotlib.lines import VertexSelector
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
import matplotlib.figure as mfigure
from mpl_toolkits.axes_grid1 import parasite_axes # type: ignore
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)
def _generate_complete_test_figure(fig_ref):
fig_ref.set_size_inches((10, 6))
plt.figure(fig_ref)
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.ylabel("hello")
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.ylabel("hello\nworld!")
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)
plt.legend(draggable=True)
fig_ref.align_ylabels() # Test handling of _align_label_groups Groupers.
@mpl.style.context("default")
@check_figures_equal(extensions=["png"])
def test_complete(fig_test, fig_ref):
_generate_complete_test_figure(fig_ref)
# plotting is done, now test its pickle-ability
pkl = pickle.dumps(fig_ref, pickle.HIGHEST_PROTOCOL)
# FigureCanvasAgg is picklable and GUI canvases are generally not, but there should
# be no reference to the canvas in the pickle stream in either case. In order to
# keep the test independent of GUI toolkits, run it with Agg and check that there's
# no reference to FigureCanvasAgg in the pickle stream.
assert "FigureCanvasAgg" not in [arg for op, arg, pos in pickletools.genops(pkl)]
loaded = pickle.loads(pkl)
loaded.canvas.draw()
fig_test.set_size_inches(loaded.get_size_inches())
fig_test.figimage(loaded.canvas.renderer.buffer_rgba())
plt.close(loaded)
def _pickle_load_subprocess():
import os
import pickle
path = os.environ['PICKLE_FILE_PATH']
with open(path, 'rb') as blob:
fig = pickle.load(blob)
print(str(pickle.dumps(fig)))
@mpl.style.context("default")
@check_figures_equal(extensions=['png'])
def test_pickle_load_from_subprocess(fig_test, fig_ref, tmp_path):
_generate_complete_test_figure(fig_ref)
fp = tmp_path / 'sinus.pickle'
assert not fp.exists()
with fp.open('wb') as file:
pickle.dump(fig_ref, file, pickle.HIGHEST_PROTOCOL)
assert fp.exists()
proc = subprocess_run_helper(
_pickle_load_subprocess,
timeout=60,
extra_env={'PICKLE_FILE_PATH': str(fp), 'MPLBACKEND': 'Agg'}
)
loaded_fig = pickle.loads(ast.literal_eval(proc.stdout))
loaded_fig.canvas.draw()
fig_test.set_size_inches(loaded_fig.get_size_inches())
fig_test.figimage(loaded_fig.canvas.renderer.buffer_rgba())
plt.close(loaded_fig)
def test_gcf():
fig = plt.figure("a label")
buf = BytesIO()
pickle.dump(fig, buf, pickle.HIGHEST_PROTOCOL)
plt.close("all")
assert plt._pylab_helpers.Gcf.figs == {} # No figures must be left.
fig = pickle.loads(buf.getbuffer())
assert plt._pylab_helpers.Gcf.figs != {} # A manager is there again.
assert fig.get_label() == "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(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)
def test_inset_and_secondary():
fig, ax = plt.subplots()
ax.inset_axes([.1, .1, .3, .3])
ax.secondary_xaxis("top", functions=(np.square, np.sqrt))
pickle.loads(pickle.dumps(fig))
@pytest.mark.parametrize("cmap", cm._colormaps.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
def test_mpl_toolkits():
ax = parasite_axes.host_axes([0, 0, 1, 1])
assert type(pickle.loads(pickle.dumps(ax))) == parasite_axes.HostAxes
def test_standard_norm():
assert type(pickle.loads(pickle.dumps(mpl.colors.LogNorm()))) \
== mpl.colors.LogNorm
def test_dynamic_norm():
logit_norm_instance = mpl.colors.make_norm_from_scale(
mpl.scale.LogitScale, mpl.colors.Normalize)()
assert type(pickle.loads(pickle.dumps(logit_norm_instance))) \
== type(logit_norm_instance)
def test_vertexselector():
line, = plt.plot([0, 1], picker=True)
pickle.loads(pickle.dumps(VertexSelector(line)))
def test_cycler():
ax = plt.figure().add_subplot()
ax.set_prop_cycle(c=["c", "m", "y", "k"])
ax.plot([1, 2])
ax = pickle.loads(pickle.dumps(ax))
l, = ax.plot([3, 4])
assert l.get_color() == "m"