Skip to content
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

Update coloredlogs requirement #939

Merged
merged 5 commits into from
Jul 9, 2024
Merged
Show file tree
Hide file tree
Changes from 3 commits
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
2 changes: 1 addition & 1 deletion .github/workflows/continuous-integration-workflow.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@ jobs:
strategy:
matrix:
python-version: ["3.8", "3.9", "3.10", "3.11"]
os: [ubuntu-latest] #, macos-latest, windows-latest]
os: [ubuntu-latest, macos-latest] #, macos-latest, windows-latest]
fail-fast: False
env:
CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -76,18 +76,18 @@ def wake_profile_ub_turbii(x):
y = (y0 + D[ii]) + (x - x0) * wake_slope
if isinstance(y, (float, np.float64, np.float32)):
if x < (x0 + 0.01):
y = -np.Inf
y = -np.inf
else:
y[x < x0 + 0.01] = -np.Inf
y[x < x0 + 0.01] = -np.inf
return y

def wake_profile_lb_turbii(x):
y = (y0 - D[ii]) - (x - x0) * wake_slope
if isinstance(y, (float, np.float64, np.float32)):
if x < (x0 + 0.01):
y = -np.Inf
y = -np.inf
else:
y[x < x0 + 0.01] = -np.Inf
y[x < x0 + 0.01] = -np.inf
return y

def determine_if_in_wake(xt, yt):
Expand Down
4 changes: 2 additions & 2 deletions setup.py
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
"attrs",
"pyyaml~=6.0",
"numexpr~=2.0",
"numpy~=1.20",
"numpy~=2.0",
Copy link
Contributor

Choose a reason for hiding this comment

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

Since numpy 2.0 is a very new release (June 16, 2024), it would be helpful for me (and I suspect many other users) to not yet require version 2.

Copy link
Collaborator Author

Choose a reason for hiding this comment

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

Makes sense, reverting but keeping the 2.0 improvements for a shorter hop later

"scipy~=1.1",

# tools
Expand All @@ -27,7 +27,7 @@
"shapely~=2.0",

# utilities
"coloredlogs~=10.0",
"coloredlogs~=15.0",
]

# What packages are optional?
Expand Down
Loading