mirror of https://github.com/pyodide/pyodide.git
588 lines
18 KiB
Python
588 lines
18 KiB
Python
import base64
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import pathlib
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import textwrap
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from functools import reduce
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import pytest
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REFERENCE_IMAGES_PATH = pathlib.Path(__file__).parent / "reference-images"
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DECORATORS = [
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pytest.mark.xfail_browsers(node="No supported matplotlib backends on node"),
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pytest.mark.skip_refcount_check,
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pytest.mark.skip_pyproxy_check,
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]
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def matplotlib_test_decorator(f):
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return reduce(lambda x, g: g(x), DECORATORS, f)
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def run_with_resolve(selenium, code):
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selenium.run_js(
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f"""
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try {{
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let promise = new Promise((resolve) => self.resolve = resolve);
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pyodide.runPython({code!r});
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await promise;
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}} finally {{
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delete self.resolve;
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}}
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"""
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)
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def patch_font_loading_and_dpi(target_font=""):
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"""Monkey-patches font loading and dpi to allow testing"""
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return textwrap.dedent(
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f"""from matplotlib.backends.html5_canvas_backend import RendererHTMLCanvas
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from matplotlib.backends.html5_canvas_backend import FigureCanvasHTMLCanvas
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FigureCanvasHTMLCanvas.get_dpi_ratio = lambda self, context: 2.0
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load_font_into_web = RendererHTMLCanvas.load_font_into_web
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def load_font_into_web_wrapper(self, loaded_font, font_url, orig_function=load_font_into_web):
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fontface = orig_function(self, loaded_font, font_url)
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target_font = {target_font!r}
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if not target_font or target_font == fontface.family:
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try:
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from js import resolve
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resolve()
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except Exception as e:
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raise ValueError("unable to resolve") from e
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RendererHTMLCanvas.load_font_into_web = load_font_into_web_wrapper
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"""
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)
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def save_canvas_data(selenium, output_path):
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canvas_data = selenium.run(
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"""
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import base64
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canvas = plt.gcf().canvas.get_element("canvas")
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canvas_data = canvas.toDataURL("image/png")[21:]
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canvas_data
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"""
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)
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canvas_png = base64.b64decode(canvas_data)
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output_path.write_bytes(canvas_png)
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def compare_with_reference_image(selenium, reference_image):
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reference_image_encoded = base64.b64encode(reference_image.read_bytes())
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deviation = selenium.run(
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f"""
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import io
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import base64
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import numpy as np
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from PIL import Image
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canvas_data = plt.gcf().canvas.get_pixel_data()
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ref_data = np.asarray(Image.open(io.BytesIO(base64.b64decode({reference_image_encoded!r}))))
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deviation = np.mean(np.abs(canvas_data - ref_data))
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float(deviation)
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"""
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)
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# Note: uncomment this line if you want to save the output canvas image (for comparison).
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# save_canvas_data(selenium, reference_image.with_name(f"output-{reference_image.name}"))
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return deviation == 0.0
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@matplotlib_test_decorator
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def test_matplotlib(selenium):
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selenium.load_package("matplotlib")
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selenium.run(
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"""
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from matplotlib import pyplot as plt
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plt.figure()
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plt.plot([1,2,3])
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plt.show()
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"""
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)
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@matplotlib_test_decorator
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def test_svg(selenium):
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selenium.load_package("matplotlib")
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content = selenium.run(
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"""
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from matplotlib import pyplot as plt
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import io
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plt.figure()
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x = plt.plot([1,2,3])
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fd = io.BytesIO()
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plt.savefig(fd, format='svg')
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fd.getvalue().decode('utf8')
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"""
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)
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assert len(content) == 14998
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assert content.startswith("<?xml")
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@matplotlib_test_decorator
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def test_pdf(selenium):
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selenium.load_package("matplotlib")
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selenium.run(
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"""
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from matplotlib import pyplot as plt
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plt.figure()
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x = plt.plot([1,2,3])
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import io
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fd = io.BytesIO()
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plt.savefig(fd, format='pdf')
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"""
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)
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def test_font_manager(selenium):
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"""
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Comparing vendored fontlist.json version with the one built
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by font_manager.py.
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If you try to update Matplotlib and this test fails, try to
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update fontlist.json.
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"""
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selenium.load_package("matplotlib")
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selenium.run(
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"""
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from matplotlib import font_manager as fm
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import os
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import json
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# get fontlist form file
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fontist_file = os.path.join(os.path.dirname(fm.__file__), 'fontlist.json')
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with open(fontist_file) as f:
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fontlist_vendor = json.loads(f.read())
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# get fontlist from build
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fontlist_built = json.loads(json.dumps(fm.FontManager(), cls=fm._JSONEncoder))
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# reodering list to compare
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for list in ('afmlist', 'ttflist'):
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for fontlist in (fontlist_vendor, fontlist_built):
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fontlist[list].sort(key=lambda x: x['fname'])
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"""
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)
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assert selenium.run("fontlist_built == fontlist_vendor")
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@matplotlib_test_decorator
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def test_rendering(selenium_standalone):
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selenium = selenium_standalone
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selenium.load_package("matplotlib")
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selenium.set_script_timeout(60)
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run_with_resolve(
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selenium,
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f"""
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{patch_font_loading_and_dpi()}
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import matplotlib
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matplotlib.use("module://matplotlib.backends.html5_canvas_backend")
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import numpy as np
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from matplotlib import pyplot as plt
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t = np.arange(0.0, 2.0, 0.01)
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s = 1 + np.sin(2 * np.pi * t)
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plt.figure()
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plt.plot(t, s, linewidth=1.0, marker=11)
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plt.plot(t, t)
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plt.grid(True)
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plt.show()
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""",
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)
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assert compare_with_reference_image(
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selenium, REFERENCE_IMAGES_PATH / f"canvas-{selenium.browser}.png"
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)
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@matplotlib_test_decorator
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def test_draw_image(selenium_standalone):
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selenium = selenium_standalone
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selenium.load_package("matplotlib")
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selenium.set_script_timeout(60)
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run_with_resolve(
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selenium,
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f"""
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{patch_font_loading_and_dpi()}
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import matplotlib
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matplotlib.use("module://matplotlib.backends.html5_canvas_backend")
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import numpy as np
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import matplotlib.cm as cm
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import matplotlib.pyplot as plt
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import matplotlib.cbook as cbook
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from matplotlib.path import Path
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from matplotlib.patches import PathPatch
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delta = 0.025
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x = y = np.arange(-3.0, 3.0, delta)
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X, Y = np.meshgrid(x, y)
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Z1 = np.exp(-X**2 - Y**2)
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Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
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Z = (Z1 - Z2) * 2
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plt.figure()
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plt.imshow(Z, interpolation='bilinear', cmap=cm.RdYlGn,
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origin='lower', extent=[-3, 3, -3, 3],
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vmax=abs(Z).max(), vmin=-abs(Z).max())
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plt.show()
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""",
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)
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assert compare_with_reference_image(
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selenium, REFERENCE_IMAGES_PATH / f"canvas-image-{selenium.browser}.png"
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)
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@matplotlib_test_decorator
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def test_draw_image_affine_transform(selenium_standalone):
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selenium = selenium_standalone
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selenium.load_package("matplotlib")
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selenium.set_script_timeout(60)
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run_with_resolve(
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selenium,
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f"""
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{patch_font_loading_and_dpi()}
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import matplotlib
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matplotlib.use("module://matplotlib.backends.html5_canvas_backend")
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.transforms as mtransforms
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def get_image():
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delta = 0.25
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x = y = np.arange(-3.0, 3.0, delta)
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X, Y = np.meshgrid(x, y)
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Z1 = np.exp(-X**2 - Y**2)
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Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
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Z = (Z1 - Z2)
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return Z
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def do_plot(ax, Z, transform):
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im = ax.imshow(Z, interpolation='none',
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origin='lower',
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extent=[-2, 4, -3, 2], clip_on=True)
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trans_data = transform + ax.transData
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im.set_transform(trans_data)
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# display intended extent of the image
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x1, x2, y1, y2 = im.get_extent()
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ax.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "y--",
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transform=trans_data)
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ax.set_xlim(-5, 5)
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ax.set_ylim(-4, 4)
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# prepare image and figure
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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
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Z = get_image()
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# image rotation
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do_plot(ax1, Z, mtransforms.Affine2D().rotate_deg(30))
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# image skew
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do_plot(ax2, Z, mtransforms.Affine2D().skew_deg(30, 15))
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# scale and reflection
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do_plot(ax3, Z, mtransforms.Affine2D().scale(-1, .5))
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# everything and a translation
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do_plot(ax4, Z, mtransforms.Affine2D().
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rotate_deg(30).skew_deg(30, 15).scale(-1, .5).translate(.5, -1))
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plt.show()
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""",
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)
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assert compare_with_reference_image(
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selenium, REFERENCE_IMAGES_PATH / f"canvas-image-affine-{selenium.browser}.png"
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)
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@matplotlib_test_decorator
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def test_draw_text_rotated(selenium_standalone):
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selenium = selenium_standalone
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selenium.load_package("matplotlib")
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selenium.set_script_timeout(60)
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run_with_resolve(
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selenium,
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f"""
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{patch_font_loading_and_dpi()}
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import os
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os.environ["TESTING_MATPLOTLIB"] = "1"
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import matplotlib
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matplotlib.use("module://matplotlib.backends.html5_canvas_backend")
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import matplotlib.pyplot as plt
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from matplotlib.dates import (
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YEARLY, DateFormatter,
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rrulewrapper, RRuleLocator,
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drange)
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import numpy as np
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import datetime
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# tick every 5th easter
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np.random.seed(42)
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rule = rrulewrapper(YEARLY, byeaster=1, interval=5)
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loc = RRuleLocator(rule)
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formatter = DateFormatter('%m/%d/%y')
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date1 = datetime.date(1952, 1, 1)
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date2 = datetime.date(2004, 4, 12)
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delta = datetime.timedelta(days=100)
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dates = drange(date1, date2, delta)
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s = np.random.rand(len(dates)) # make up some random y values
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fig, ax = plt.subplots()
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plt.plot_date(dates, s)
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ax.xaxis.set_major_locator(loc)
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ax.xaxis.set_major_formatter(formatter)
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labels = ax.get_xticklabels()
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plt.setp(labels, rotation=30, fontsize=10)
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plt.show()
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""",
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)
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assert compare_with_reference_image(
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selenium, REFERENCE_IMAGES_PATH / f"canvas-text-rotated-{selenium.browser}.png"
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)
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@matplotlib_test_decorator
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def test_draw_math_text(selenium_standalone):
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selenium = selenium_standalone
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selenium.load_package("matplotlib")
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selenium.set_script_timeout(60)
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run_with_resolve(
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selenium,
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f"""
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{patch_font_loading_and_dpi()}
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"""
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+ r"""
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import os
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os.environ["TESTING_MATPLOTLIB"] = "1"
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import matplotlib
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matplotlib.use("module://matplotlib.backends.html5_canvas_backend")
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from js import window
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window.testingMatplotlib = True
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import matplotlib.pyplot as plt
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import sys
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import re
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# Selection of features following
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# "Writing mathematical expressions" tutorial
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mathtext_titles = {
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0: "Header demo",
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1: "Subscripts and superscripts",
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2: "Fractions, binomials and stacked numbers",
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3: "Radicals",
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4: "Fonts",
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5: "Accents",
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6: "Greek, Hebrew",
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7: "Delimiters, functions and Symbols"}
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n_lines = len(mathtext_titles)
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# Randomly picked examples
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mathext_demos = {
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0: r"$W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = "
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r"U^{3\beta}_{\delta_1 \rho_1} + \frac{1}{8 \pi 2} "
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r"\int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 \left[\frac{ "
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r"U^{2\beta}_{\delta_1 \rho_1} - \alpha^\prime_2U^{1\beta}_"
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r"{\rho_1 \sigma_2} }{U^{0\beta}_{\rho_1 \sigma_2}}\right]$",
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1: r"$\alpha_i > \beta_i,\ "
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r"\alpha_{i+1}^j = {\rm sin}(2\pi f_j t_i) e^{-5 t_i/\tau},\ "
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r"\ldots$",
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2: r"$\frac{3}{4},\ \binom{3}{4},\ \genfrac{}{}{0}{}{3}{4},\ "
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r"\left(\frac{5 - \frac{1}{x}}{4}\right),\ \ldots$",
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3: r"$\sqrt{2},\ \sqrt[3]{x},\ \ldots$",
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4: r"$\mathrm{Roman}\ , \ \mathit{Italic}\ , \ \mathtt{Typewriter} \ "
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r"\mathrm{or}\ \mathcal{CALLIGRAPHY}$",
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5: r"$\acute a,\ \bar a,\ \breve a,\ \dot a,\ \ddot a, \ \grave a, \ "
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r"\hat a,\ \tilde a,\ \vec a,\ \widehat{xyz},\ \widetilde{xyz},\ "
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r"\ldots$",
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6: r"$\alpha,\ \beta,\ \chi,\ \delta,\ \lambda,\ \mu,\ "
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r"\Delta,\ \Gamma,\ \Omega,\ \Phi,\ \Pi,\ \Upsilon,\ \nabla,\ "
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r"\aleph,\ \beth,\ \daleth,\ \gimel,\ \ldots$",
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7: r"$\coprod,\ \int,\ \oint,\ \prod,\ \sum,\ "
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r"\log,\ \sin,\ \approx,\ \oplus,\ \star,\ \varpropto,\ "
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r"\infty,\ \partial,\ \Re,\ \leftrightsquigarrow, \ \ldots$"}
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def doall():
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# Colors used in mpl online documentation.
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mpl_blue_rvb = (191. / 255., 209. / 256., 212. / 255.)
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mpl_orange_rvb = (202. / 255., 121. / 256., 0. / 255.)
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mpl_grey_rvb = (51. / 255., 51. / 255., 51. / 255.)
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# Creating figure and axis.
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plt.figure(figsize=(6, 7))
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plt.axes([0.01, 0.01, 0.98, 0.90], facecolor="white", frameon=True)
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plt.gca().set_xlim(0., 1.)
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plt.gca().set_ylim(0., 1.)
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plt.gca().set_title("Matplotlib's math rendering engine",
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color=mpl_grey_rvb, fontsize=14, weight='bold')
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plt.gca().set_xticklabels("", visible=False)
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plt.gca().set_yticklabels("", visible=False)
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# Gap between lines in axes coords
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line_axesfrac = (1. / (n_lines))
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# Plotting header demonstration formula
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full_demo = mathext_demos[0]
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plt.annotate(full_demo,
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xy=(0.5, 1. - 0.59 * line_axesfrac),
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color=mpl_orange_rvb, ha='center', fontsize=20)
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# Plotting features demonstration formulae
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for i_line in range(1, n_lines):
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baseline = 1 - (i_line) * line_axesfrac
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baseline_next = baseline - line_axesfrac
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title = mathtext_titles[i_line] + ":"
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fill_color = ['white', mpl_blue_rvb][i_line % 2]
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plt.fill_between([0., 1.], [baseline, baseline],
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[baseline_next, baseline_next],
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color=fill_color, alpha=0.5)
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plt.annotate(title,
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xy=(0.07, baseline - 0.3 * line_axesfrac),
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color=mpl_grey_rvb, weight='bold')
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demo = mathext_demos[i_line]
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plt.annotate(demo,
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xy=(0.05, baseline - 0.75 * line_axesfrac),
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color=mpl_grey_rvb, fontsize=16)
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for i in range(n_lines):
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s = mathext_demos[i]
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print(i, s)
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plt.show()
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doall()
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""",
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)
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assert compare_with_reference_image(
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selenium, REFERENCE_IMAGES_PATH / f"canvas-math-text-{selenium.browser}.png"
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)
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@matplotlib_test_decorator
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def test_custom_font_text(selenium_standalone):
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selenium = selenium_standalone
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selenium.load_package("matplotlib")
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selenium.set_script_timeout(60)
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run_with_resolve(
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selenium,
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f"""
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{patch_font_loading_and_dpi(target_font='cmsy10')}
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import matplotlib
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matplotlib.use("module://matplotlib.backends.html5_canvas_backend")
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import matplotlib.pyplot as plt
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import numpy as np
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f = {{'fontname': 'cmsy10'}}
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t = np.arange(0.0, 2.0, 0.01)
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s = 1 + np.sin(2 * np.pi * t)
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plt.figure()
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|
plt.title('A simple Sine Curve', **f)
|
|
plt.plot(t, s, linewidth=1.0, marker=11)
|
|
plt.plot(t, t)
|
|
plt.grid(True)
|
|
plt.show()
|
|
""",
|
|
)
|
|
|
|
assert compare_with_reference_image(
|
|
selenium,
|
|
REFERENCE_IMAGES_PATH / f"canvas-custom-font-text-{selenium.browser}.png",
|
|
)
|
|
|
|
|
|
@matplotlib_test_decorator
|
|
def test_zoom_on_polar_plot(selenium_standalone):
|
|
selenium = selenium_standalone
|
|
|
|
selenium.load_package("matplotlib")
|
|
selenium.set_script_timeout(60)
|
|
run_with_resolve(
|
|
selenium,
|
|
f"""
|
|
{patch_font_loading_and_dpi()}
|
|
import matplotlib
|
|
matplotlib.use("module://matplotlib.backends.html5_canvas_backend")
|
|
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
np.random.seed(42)
|
|
|
|
# Compute pie slices
|
|
N = 20
|
|
theta = np.linspace(0.0, 2 * np.pi, N, endpoint=False)
|
|
radii = 10 * np.random.rand(N)
|
|
width = np.pi / 4 * np.random.rand(N)
|
|
|
|
ax = plt.subplot(111, projection='polar')
|
|
bars = ax.bar(theta, radii, width=width, bottom=0.0)
|
|
|
|
# Use custom colors and opacity
|
|
for r, bar in zip(radii, bars):
|
|
bar.set_facecolor(plt.cm.viridis(r / 10.))
|
|
bar.set_alpha(0.5)
|
|
|
|
ax.set_rlim([0,5])
|
|
plt.show()
|
|
""",
|
|
)
|
|
|
|
assert compare_with_reference_image(
|
|
selenium, REFERENCE_IMAGES_PATH / f"canvas-polar-zoom-{selenium.browser}.png"
|
|
)
|
|
|
|
|
|
@matplotlib_test_decorator
|
|
def test_transparency(selenium_standalone):
|
|
selenium = selenium_standalone
|
|
|
|
selenium.load_package("matplotlib")
|
|
selenium.set_script_timeout(60)
|
|
run_with_resolve(
|
|
selenium,
|
|
f"""
|
|
{patch_font_loading_and_dpi()}
|
|
import matplotlib
|
|
matplotlib.use("module://matplotlib.backends.html5_canvas_backend")
|
|
import numpy as np
|
|
np.random.seed(19680801)
|
|
import matplotlib.pyplot as plt
|
|
|
|
fig, ax = plt.subplots()
|
|
for color in ['tab:blue', 'tab:orange', 'tab:green']:
|
|
n = 100
|
|
x, y = np.random.rand(2, n)
|
|
scale = 200.0 * np.random.rand(n)
|
|
ax.scatter(x, y, c=color, s=scale, label=color,
|
|
alpha=0.3, edgecolors='none')
|
|
|
|
ax.legend()
|
|
ax.grid(True)
|
|
|
|
plt.show()
|
|
""",
|
|
)
|
|
|
|
assert compare_with_reference_image(
|
|
selenium, REFERENCE_IMAGES_PATH / f"canvas-transparency-{selenium.browser}.png"
|
|
)
|