Skip to content

Skipped flaky part of test_time #25894

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 3 commits into from
Mar 27, 2019
Merged
Changes from 1 commit
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
27 changes: 27 additions & 0 deletions pandas/tests/plotting/test_datetimelike.py
Original file line number Diff line number Diff line change
Expand Up @@ -1104,6 +1104,33 @@ def test_time(self):
xp = time(h, m, s).strftime('%H:%M')
assert xp == rs

@pytest.mark.slow
@pytest.mark.skip(reason="Unreliable test")
def test_time_change_xlim(self):
t = datetime(1, 1, 1, 3, 30, 0)
deltas = np.random.randint(1, 20, 3).cumsum()
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I believe the random ints for deltas are what can cause the failures.

Copy link
Member

@gfyoung gfyoung Mar 27, 2019

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Potentially, though probably best to investigate after this PR.

ts = np.array([(t + timedelta(minutes=int(x))).time() for x in deltas])
df = DataFrame({'a': np.random.randn(len(ts)),
'b': np.random.randn(len(ts))},
index=ts)
fig, ax = self.plt.subplots()
df.plot(ax=ax)

# verify tick labels
fig.canvas.draw()
ticks = ax.get_xticks()
labels = ax.get_xticklabels()
for t, l in zip(ticks, labels):
m, s = divmod(int(t), 60)
h, m = divmod(m, 60)
rs = l.get_text()
if len(rs) > 0:
if s != 0:
xp = time(h, m, s).strftime('%H:%M:%S')
else:
xp = time(h, m, s).strftime('%H:%M')
assert xp == rs

# change xlim
ax.set_xlim('1:30', '5:00')

Expand Down