Files

731 lines
24 KiB
Python

import datetime
import decimal
import io
from pathlib import Path
import string
import numpy as np
import pytest
import matplotlib as mpl
from matplotlib import (
pyplot as plt, rcParams, font_manager as fm
)
from matplotlib.cbook import _get_data_path
from matplotlib.ft2font import FT2Font
from matplotlib.backends._backend_pdf_ps import get_glyphs_subset, font_as_file
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib.patches import Rectangle
from matplotlib.testing import _gen_multi_font_text, _has_tex_package
from matplotlib.testing.decorators import check_figures_equal, image_comparison
from matplotlib.testing._markers import needs_usetex
@image_comparison(['pdf_use14corefonts.pdf'], style='_classic_test')
def test_use14corefonts():
rcParams['pdf.use14corefonts'] = True
rcParams['font.family'] = 'sans-serif'
rcParams['font.size'] = 8
rcParams['font.sans-serif'] = ['Helvetica']
rcParams['pdf.compression'] = 0
text = '''A three-line text positioned just above a blue line
and containing some French characters and the euro symbol:
"Merci pépé pour les 10 €"'''
fig, ax = plt.subplots()
ax.set_title('Test PDF backend with option use14corefonts=True')
ax.text(0.5, 0.5, text, horizontalalignment='center',
verticalalignment='bottom',
fontsize=14)
ax.axhline(0.5, linewidth=0.5)
def test_multipage_pagecount():
with PdfPages(io.BytesIO()) as pdf:
assert pdf.get_pagecount() == 0
fig, ax = plt.subplots()
ax.plot([1, 2, 3])
fig.savefig(pdf, format="pdf")
assert pdf.get_pagecount() == 1
pdf.savefig()
assert pdf.get_pagecount() == 2
def test_multipage_properfinalize():
pdfio = io.BytesIO()
with PdfPages(pdfio) as pdf:
for i in range(10):
fig, ax = plt.subplots()
ax.set_title('This is a long title')
fig.savefig(pdf, format="pdf")
s = pdfio.getvalue()
assert s.count(b'startxref') == 1
assert len(s) < 40000
def test_multipage_keep_empty(tmp_path):
# An empty pdf deletes itself afterwards.
fn = tmp_path / "a.pdf"
with PdfPages(fn) as pdf:
pass
assert not fn.exists()
# Test pdf files with content, they should never be deleted.
fn = tmp_path / "b.pdf"
with PdfPages(fn) as pdf:
pdf.savefig(plt.figure())
assert fn.exists()
def test_composite_image():
# Test that figures can be saved with and without combining multiple images
# (on a single set of axes) into a single composite image.
X, Y = np.meshgrid(np.arange(-5, 5, 1), np.arange(-5, 5, 1))
Z = np.sin(Y ** 2)
fig, ax = plt.subplots()
ax.set_xlim(0, 3)
ax.imshow(Z, extent=[0, 1, 0, 1])
ax.imshow(Z[::-1], extent=[2, 3, 0, 1])
plt.rcParams['image.composite_image'] = True
with PdfPages(io.BytesIO()) as pdf:
fig.savefig(pdf, format="pdf")
assert len(pdf._file._images) == 1
plt.rcParams['image.composite_image'] = False
with PdfPages(io.BytesIO()) as pdf:
fig.savefig(pdf, format="pdf")
assert len(pdf._file._images) == 2
def test_indexed_image():
# An image with low color count should compress to a palette-indexed format.
pikepdf = pytest.importorskip('pikepdf')
data = np.zeros((256, 1, 3), dtype=np.uint8)
data[:, 0, 0] = np.arange(256) # Maximum unique colours for an indexed image.
rcParams['pdf.compression'] = True
fig = plt.figure()
fig.figimage(data, resize=True)
buf = io.BytesIO()
fig.savefig(buf, format='pdf', dpi='figure')
with pikepdf.Pdf.open(buf) as pdf:
page, = pdf.pages
image, = page.images.values()
pdf_image = pikepdf.PdfImage(image)
assert pdf_image.indexed
pil_image = pdf_image.as_pil_image()
rgb = np.asarray(pil_image.convert('RGB'))
np.testing.assert_array_equal(data, rgb)
def test_savefig_metadata(monkeypatch):
pikepdf = pytest.importorskip('pikepdf')
monkeypatch.setenv('SOURCE_DATE_EPOCH', '0')
fig, ax = plt.subplots()
ax.plot(range(5))
md = {
'Author': 'me',
'Title': 'Multipage PDF',
'Subject': 'Test page',
'Keywords': 'test,pdf,multipage',
'ModDate': datetime.datetime(
1968, 8, 1, tzinfo=datetime.timezone(datetime.timedelta(0))),
'Trapped': 'True'
}
buf = io.BytesIO()
fig.savefig(buf, metadata=md, format='pdf')
with pikepdf.Pdf.open(buf) as pdf:
info = {k: str(v) for k, v in pdf.docinfo.items()}
assert info == {
'/Author': 'me',
'/CreationDate': 'D:19700101000000Z',
'/Creator': f'Matplotlib v{mpl.__version__}, https://matplotlib.org',
'/Keywords': 'test,pdf,multipage',
'/ModDate': 'D:19680801000000Z',
'/Producer': f'Matplotlib pdf backend v{mpl.__version__}',
'/Subject': 'Test page',
'/Title': 'Multipage PDF',
'/Trapped': '/True',
}
def test_invalid_metadata():
fig, ax = plt.subplots()
with pytest.warns(UserWarning,
match="Unknown infodict keyword: 'foobar'."):
fig.savefig(io.BytesIO(), format='pdf', metadata={'foobar': 'invalid'})
with pytest.warns(UserWarning,
match='not an instance of datetime.datetime.'):
fig.savefig(io.BytesIO(), format='pdf',
metadata={'ModDate': '1968-08-01'})
with pytest.warns(UserWarning,
match='not one of {"True", "False", "Unknown"}'):
fig.savefig(io.BytesIO(), format='pdf', metadata={'Trapped': 'foo'})
with pytest.warns(UserWarning, match='not an instance of str.'):
fig.savefig(io.BytesIO(), format='pdf', metadata={'Title': 1234})
def test_multipage_metadata(monkeypatch):
pikepdf = pytest.importorskip('pikepdf')
monkeypatch.setenv('SOURCE_DATE_EPOCH', '0')
fig, ax = plt.subplots()
ax.plot(range(5))
md = {
'Author': 'me',
'Title': 'Multipage PDF',
'Subject': 'Test page',
'Keywords': 'test,pdf,multipage',
'ModDate': datetime.datetime(
1968, 8, 1, tzinfo=datetime.timezone(datetime.timedelta(0))),
'Trapped': 'True'
}
buf = io.BytesIO()
with PdfPages(buf, metadata=md) as pdf:
pdf.savefig(fig)
pdf.savefig(fig)
with pikepdf.Pdf.open(buf) as pdf:
info = {k: str(v) for k, v in pdf.docinfo.items()}
assert info == {
'/Author': 'me',
'/CreationDate': 'D:19700101000000Z',
'/Creator': f'Matplotlib v{mpl.__version__}, https://matplotlib.org',
'/Keywords': 'test,pdf,multipage',
'/ModDate': 'D:19680801000000Z',
'/Producer': f'Matplotlib pdf backend v{mpl.__version__}',
'/Subject': 'Test page',
'/Title': 'Multipage PDF',
'/Trapped': '/True',
}
def test_text_urls():
pikepdf = pytest.importorskip('pikepdf')
test_url = 'https://test_text_urls.matplotlib.org/'
fig = plt.figure(figsize=(2, 1))
fig.text(0.1, 0.1, 'test plain 123', url=f'{test_url}plain')
fig.text(0.1, 0.4, 'test mathtext $123$', url=f'{test_url}mathtext')
with io.BytesIO() as fd:
fig.savefig(fd, format='pdf')
with pikepdf.Pdf.open(fd) as pdf:
annots = pdf.pages[0].Annots
# Iteration over Annots must occur within the context manager,
# otherwise it may fail depending on the pdf structure.
for y, fragment in [('0.1', 'plain'), ('0.4', 'mathtext')]:
annot = next(
(a for a in annots if a.A.URI == f'{test_url}{fragment}'),
None)
assert annot is not None
assert getattr(annot, 'QuadPoints', None) is None
# Positions in points (72 per inch.)
assert annot.Rect[1] == decimal.Decimal(y) * 72
def test_text_rotated_urls():
pikepdf = pytest.importorskip('pikepdf')
test_url = 'https://test_text_urls.matplotlib.org/'
fig = plt.figure(figsize=(1, 1))
fig.text(0.1, 0.1, 'N', rotation=45, url=f'{test_url}')
with io.BytesIO() as fd:
fig.savefig(fd, format='pdf')
with pikepdf.Pdf.open(fd) as pdf:
annots = pdf.pages[0].Annots
# Iteration over Annots must occur within the context manager,
# otherwise it may fail depending on the pdf structure.
annot = next(
(a for a in annots if a.A.URI == f'{test_url}'),
None)
assert annot is not None
assert getattr(annot, 'QuadPoints', None) is not None
# Positions in points (72 per inch)
assert annot.Rect[0] == \
annot.QuadPoints[6] - decimal.Decimal('0.00001')
@needs_usetex
def test_text_urls_tex():
pikepdf = pytest.importorskip('pikepdf')
test_url = 'https://test_text_urls.matplotlib.org/'
fig = plt.figure(figsize=(2, 1))
fig.text(0.1, 0.7, 'test tex $123$', usetex=True, url=f'{test_url}tex')
with io.BytesIO() as fd:
fig.savefig(fd, format='pdf')
with pikepdf.Pdf.open(fd) as pdf:
annots = pdf.pages[0].Annots
# Iteration over Annots must occur within the context manager,
# otherwise it may fail depending on the pdf structure.
annot = next(
(a for a in annots if a.A.URI == f'{test_url}tex'),
None)
assert annot is not None
# Positions in points (72 per inch.)
assert annot.Rect[1] == decimal.Decimal('0.7') * 72
def test_pdfpages_fspath(tmp_path):
with PdfPages(tmp_path / 'unused.pdf') as pdf:
pdf.savefig(plt.figure())
@image_comparison(['hatching_legend.pdf'], style='mpl20')
def test_hatching_legend(text_placeholders):
"""Test for correct hatching on patches in legend"""
fig = plt.figure(figsize=(1, 2))
a = Rectangle([0, 0], 0, 0, facecolor="green", hatch="XXXX")
b = Rectangle([0, 0], 0, 0, facecolor="blue", hatch="XXXX")
# Verify that hatches in PDFs work after empty labels. See
# https://github.com/matplotlib/matplotlib/issues/4469
fig.legend([a, b, a, b], ["", "", "", ""])
@image_comparison(['grayscale_alpha.pdf'], style='_classic_test')
def test_grayscale_alpha():
"""Masking images with NaN did not work for grayscale images"""
x, y = np.ogrid[-2:2:.1, -2:2:.1]
dd = np.exp(-(x**2 + y**2))
dd[dd < .1] = np.nan
fig, ax = plt.subplots()
ax.imshow(dd, interpolation='none', cmap='gray_r')
ax.set_xticks([])
ax.set_yticks([])
@mpl.style.context('default')
@check_figures_equal(extensions=["pdf", "eps"])
def test_pdf_eps_savefig_when_color_is_none(fig_test, fig_ref):
ax_test = fig_test.add_subplot()
ax_test.set_axis_off()
ax_test.plot(np.sin(np.linspace(-5, 5, 100)), "v", c="none")
ax_ref = fig_ref.add_subplot()
ax_ref.set_axis_off()
@needs_usetex
def test_failing_latex():
"""Test failing latex subprocess call"""
plt.xlabel("$22_2_2$", usetex=True) # This fails with "Double subscript"
with pytest.raises(RuntimeError):
plt.savefig(io.BytesIO(), format="pdf")
def test_empty_rasterized():
# Check that empty figures that are rasterised save to pdf files fine
fig, ax = plt.subplots()
ax.plot([], [], rasterized=True)
fig.savefig(io.BytesIO(), format="pdf")
@image_comparison(['kerning.pdf'], style='mpl20')
def test_kerning():
fig = plt.figure()
s = "AVAVAVAVAVAVAVAV€AAVV"
fig.text(0, .25, s, size=5)
fig.text(0, .75, s, size=20)
def test_glyphs_subset():
fpath = str(_get_data_path("fonts/ttf/DejaVuSerif.ttf"))
chars = "these should be subsetted! 1234567890"
# non-subsetted FT2Font
nosubfont = FT2Font(fpath)
nosubfont.set_text(chars)
nosubcmap = nosubfont.get_charmap()
# subsetted FT2Font
glyph_indices = {nosubcmap[ord(c)] for c in chars}
with get_glyphs_subset(fm.FontPath(fpath, 0), glyph_indices) as subset:
subfont = FT2Font(font_as_file(subset))
subfont.set_text(chars)
subcmap = subfont.get_charmap()
# all unique chars must be available in subsetted font
assert {*chars} == {chr(key) for key in subcmap}
# subsetted font's charmap should have less entries
assert len(subcmap) < len(nosubcmap)
# since both objects are assigned same characters
assert subfont.get_num_glyphs() == nosubfont.get_num_glyphs()
@image_comparison(["multi_font_type3.pdf"], style='mpl20')
def test_multi_font_type3():
fonts, test_str = _gen_multi_font_text()
plt.rc('font', family=fonts, size=16)
plt.rc('pdf', fonttype=3)
fig = plt.figure(figsize=(8, 6))
fig.text(0.5, 0.5, test_str,
horizontalalignment='center', verticalalignment='center')
@image_comparison(["multi_font_type42.pdf"], style='mpl20')
def test_multi_font_type42():
fonts, test_str = _gen_multi_font_text()
plt.rc('font', family=fonts, size=16)
plt.rc('pdf', fonttype=42)
fig = plt.figure(figsize=(8, 6))
fig.text(0.5, 0.5, test_str,
horizontalalignment='center', verticalalignment='center')
@image_comparison(['ttc_type3.pdf'], style='mpl20')
def test_ttc_type3():
fp = fm.FontProperties(family=['WenQuanYi Zen Hei'])
if Path(fm.findfont(fp)).name != 'wqy-zenhei.ttc':
pytest.skip('Font wqy-zenhei.ttc may be missing')
fonts = ['WenQuanYi Zen Hei', 'WenQuanYi Zen Hei Mono']
plt.rc('font', size=16)
plt.rc('pdf', fonttype=3)
figs = plt.figure(figsize=(7, len(fonts) / 2)).subfigures(len(fonts))
for font, fig in zip(fonts, figs):
fig.text(0.5, 0.5, f'{font}: {string.ascii_uppercase}', font=font,
horizontalalignment='center', verticalalignment='center')
@image_comparison(['ttc_type42.pdf'], style='mpl20')
def test_ttc_type42():
fp = fm.FontProperties(family=['WenQuanYi Zen Hei'])
if Path(fm.findfont(fp)).name != 'wqy-zenhei.ttc':
pytest.skip('Font wqy-zenhei.ttc may be missing')
fonts = ['WenQuanYi Zen Hei', 'WenQuanYi Zen Hei Mono']
plt.rc('font', size=16)
plt.rc('pdf', fonttype=42)
figs = plt.figure(figsize=(7, len(fonts) / 2)).subfigures(len(fonts))
for font, fig in zip(fonts, figs):
fig.text(0.5, 0.5, f'{font}: {string.ascii_uppercase}', font=font,
horizontalalignment='center', verticalalignment='center')
@pytest.mark.parametrize('family_name, file_name',
[("Noto Sans", "NotoSans-Regular.otf"),
("FreeMono", "FreeMono.otf")])
def test_otf_font_smoke(family_name, file_name):
# checks that there's no segfault
fp = fm.FontProperties(family=[family_name])
if Path(fm.findfont(fp)).name != file_name:
pytest.skip(f"Font {family_name} may be missing")
plt.rc('font', family=[family_name], size=27)
fig = plt.figure()
fig.text(0.15, 0.475, "Привет мир!")
fig.savefig(io.BytesIO(), format="pdf")
@image_comparison(["truetype-conversion.pdf"], style='mpl20')
# mpltest.ttf does not have "l"/"p" glyphs so we get a warning when trying to
# get the font extents.
def test_truetype_conversion(recwarn):
mpl.rcParams['pdf.fonttype'] = 3
fig, ax = plt.subplots()
ax.text(0, 0, "ABCDE",
font=Path(__file__).parent / "data/mpltest.ttf", fontsize=72)
ax.set_xticks([])
ax.set_yticks([])
@pytest.mark.skipif(not _has_tex_package("heuristica"),
reason="LaTeX lacks heuristica package")
@image_comparison(["font-heuristica.pdf"], style='_classic_test')
def test_font_heuristica():
# Heuristica uses the callothersubr operator for some glyphs
mpl.rcParams['text.latex.preamble'] = '\n'.join((
r'\usepackage{heuristica}',
r'\usepackage[T1]{fontenc}',
r'\usepackage[utf8]{inputenc}'
))
fig, ax = plt.subplots()
ax.text(0.1, 0.1, r"BHTem fi ffl 1234", usetex=True, fontsize=50)
ax.set_xticks([])
ax.set_yticks([])
@pytest.mark.skipif(not _has_tex_package("DejaVuSans"),
reason="LaTeX lacks DejaVuSans package")
@image_comparison(["font-dejavusans.pdf"], style='_classic_test')
def test_font_dejavusans():
# DejaVuSans uses the seac operator to compose characters with diacritics
mpl.rcParams['text.latex.preamble'] = '\n'.join((
r'\usepackage{DejaVuSans}',
r'\usepackage[T1]{fontenc}',
r'\usepackage[utf8]{inputenc}'
))
fig, ax = plt.subplots()
ax.text(0.1, 0.1, r"\textsf{ñäö ABCDabcd}", usetex=True, fontsize=50)
ax.text(0.1, 0.3, r"\textsf{fi ffl 1234}", usetex=True, fontsize=50)
ax.set_xticks([])
ax.set_yticks([])
@pytest.mark.skipif(not _has_tex_package("charter"),
reason="LaTeX lacks charter package")
@image_comparison(["font-bitstream-charter.pdf"], style='_classic_test')
def test_font_bitstream_charter():
mpl.rcParams['text.latex.preamble'] = '\n'.join((
r'\usepackage{charter}',
r'\usepackage[T1]{fontenc}',
r'\usepackage[utf8]{inputenc}'
))
fig, ax = plt.subplots()
ax.text(0.1, 0.1, r"åüš ABCDabcd", usetex=True, fontsize=50)
ax.text(0.1, 0.3, r"fi ffl 1234", usetex=True, fontsize=50)
ax.set_xticks([])
ax.set_yticks([])
def test_scatter_offaxis_colored_pdf_size():
"""
Test that off-axis scatter plots with per-point colors don't bloat PDFs.
Regression test for issue #2488. When scatter points with per-point colors
are completely outside the visible axes, the PDF backend should skip
writing those markers to significantly reduce file size.
"""
# Use John Hunter's birthday as random seed for reproducibility
rng = np.random.default_rng(19680801)
n_points = 1000
x = rng.random(n_points) * 10
y = rng.random(n_points) * 10
c = rng.random(n_points)
# Test 1: Scatter with per-point colors, all points OFF-AXIS
fig1, ax1 = plt.subplots()
ax1.scatter(x, y, c=c)
ax1.set_xlim(20, 30) # Move view completely away from data (x is 0-10)
ax1.set_ylim(20, 30) # Move view completely away from data (y is 0-10)
buf1 = io.BytesIO()
fig1.savefig(buf1, format='pdf')
size_offaxis_colored = buf1.tell()
plt.close(fig1)
# Test 2: Empty scatter (baseline - accounts for scatter call overhead)
fig2, ax2 = plt.subplots()
ax2.scatter([], []) # Empty scatter to match the axes structure
ax2.set_xlim(20, 30)
ax2.set_ylim(20, 30)
buf2 = io.BytesIO()
fig2.savefig(buf2, format='pdf')
size_empty = buf2.tell()
plt.close(fig2)
# Test 3: Scatter with visible markers (should be much larger)
fig3, ax3 = plt.subplots()
ax3.scatter(x + 20, y + 20, c=c) # Shift points to be visible
ax3.set_xlim(20, 30)
ax3.set_ylim(20, 30)
buf3 = io.BytesIO()
fig3.savefig(buf3, format='pdf')
size_visible = buf3.tell()
plt.close(fig3)
# The off-axis colored scatter should be close to empty size.
# Since the axes are identical, the difference should be minimal
# (just the scatter collection setup, no actual marker data).
# Use a tight tolerance since axes output is identical.
assert size_offaxis_colored < size_empty + 5_000, (
f"Off-axis colored scatter PDF ({size_offaxis_colored} bytes) is too large. "
f"Expected close to empty scatter size ({size_empty} bytes). "
f"Markers may not be properly skipped."
)
# The visible scatter should be significantly larger than both empty and
# off-axis, demonstrating the optimization is working.
assert size_visible > size_empty + 15_000, (
f"Visible scatter PDF ({size_visible} bytes) should be much larger "
f"than empty ({size_empty} bytes) to validate the test."
)
assert size_visible > size_offaxis_colored + 15_000, (
f"Visible scatter PDF ({size_visible} bytes) should be much larger "
f"than off-axis ({size_offaxis_colored} bytes) to validate optimization."
)
@check_figures_equal(extensions=["pdf"])
def test_scatter_offaxis_colored_visual(fig_test, fig_ref):
"""
Test that on-axis scatter with per-point colors still renders correctly.
Ensures the optimization for off-axis markers doesn't break normal
scatter rendering.
"""
rng = np.random.default_rng(19680801)
n_points = 100
x = rng.random(n_points) * 5
y = rng.random(n_points) * 5
c = rng.random(n_points)
# Test figure: scatter with clipping optimization
ax_test = fig_test.subplots()
ax_test.scatter(x, y, c=c, s=50)
ax_test.set_xlim(0, 10)
ax_test.set_ylim(0, 10)
# Reference figure: should look identical
ax_ref = fig_ref.subplots()
ax_ref.scatter(x, y, c=c, s=50)
ax_ref.set_xlim(0, 10)
ax_ref.set_ylim(0, 10)
@check_figures_equal(extensions=["pdf"])
def test_scatter_mixed_onoff_axis(fig_test, fig_ref):
"""
Test scatter with some points on-axis and some off-axis.
Ensures the optimization correctly handles the common case where only
some markers are outside the visible area.
"""
rng = np.random.default_rng(19680801)
# Create points: half on-axis (0-5), half off-axis (15-20)
n_points = 50
x_on = rng.random(n_points) * 5
y_on = rng.random(n_points) * 5
x_off = rng.random(n_points) * 5 + 15
y_off = rng.random(n_points) * 5 + 15
x = np.concatenate([x_on, x_off])
y = np.concatenate([y_on, y_off])
c = rng.random(2 * n_points)
# Test figure: scatter with mixed points
ax_test = fig_test.subplots()
ax_test.scatter(x, y, c=c, s=50)
ax_test.set_xlim(0, 10)
ax_test.set_ylim(0, 10)
# Reference figure: only the on-axis points should be visible
ax_ref = fig_ref.subplots()
ax_ref.scatter(x_on, y_on, c=c[:n_points], s=50)
ax_ref.set_xlim(0, 10)
ax_ref.set_ylim(0, 10)
@check_figures_equal(extensions=["pdf"])
def test_scatter_large_markers_partial_clip(fig_test, fig_ref):
"""
Test that large markers are rendered when partially visible.
Addresses reviewer concern: markers with centers outside the canvas but
with edges extending into the visible area should still be rendered.
"""
# Create markers just outside the visible area
# Canvas is 0-10, markers at x=-0.5 and x=10.5
x = np.array([-0.5, 10.5, 5]) # left edge, right edge, center
y = np.array([5, 5, -0.5]) # center, center, bottom edge
c = np.array([0.2, 0.5, 0.8])
# Test figure: large markers (s=500 ≈ 11 points radius)
# Centers are outside, but marker edges extend into visible area
ax_test = fig_test.subplots()
ax_test.scatter(x, y, c=c, s=500)
ax_test.set_xlim(0, 10)
ax_test.set_ylim(0, 10)
# Reference figure: same plot (should render identically)
ax_ref = fig_ref.subplots()
ax_ref.scatter(x, y, c=c, s=500)
ax_ref.set_xlim(0, 10)
ax_ref.set_ylim(0, 10)
@check_figures_equal(extensions=["pdf"])
def test_scatter_logscale(fig_test, fig_ref):
"""
Test scatter optimization with logarithmic scales.
Ensures bounds checking works correctly in log-transformed coordinates.
"""
rng = np.random.default_rng(19680801)
# Create points across several orders of magnitude
n_points = 50
x = 10 ** (rng.random(n_points) * 4) # 1 to 10000
y = 10 ** (rng.random(n_points) * 4)
c = rng.random(n_points)
# Test figure: log scale with points mostly outside view
ax_test = fig_test.subplots()
ax_test.scatter(x, y, c=c, s=50)
ax_test.set_xscale('log')
ax_test.set_yscale('log')
ax_test.set_xlim(100, 1000) # Only show middle range
ax_test.set_ylim(100, 1000)
# Reference figure: should render identically
ax_ref = fig_ref.subplots()
ax_ref.scatter(x, y, c=c, s=50)
ax_ref.set_xscale('log')
ax_ref.set_yscale('log')
ax_ref.set_xlim(100, 1000)
ax_ref.set_ylim(100, 1000)
@check_figures_equal(extensions=["pdf"])
def test_scatter_polar(fig_test, fig_ref):
"""
Test scatter optimization with polar coordinates.
Ensures bounds checking works correctly in polar projections.
"""
rng = np.random.default_rng(19680801)
n_points = 50
theta = rng.random(n_points) * 2 * np.pi
r = rng.random(n_points) * 3
c = rng.random(n_points)
# Test figure: polar projection
ax_test = fig_test.subplots(subplot_kw={'projection': 'polar'})
ax_test.scatter(theta, r, c=c, s=50)
ax_test.set_ylim(0, 2) # Limit radial range
# Reference figure: should render identically
ax_ref = fig_ref.subplots(subplot_kw={'projection': 'polar'})
ax_ref.scatter(theta, r, c=c, s=50)
ax_ref.set_ylim(0, 2)