Skip to content

Use integer bins for integer data in HistogramWidget #244

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.

Sign up for GitHub

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 9 commits into from
Jan 15, 2024
Merged

Use integer bins for integer data in HistogramWidget #244

Changes from 1 commit
Commits
Show all changes
9 commits
Select commit Hold shift + click to select a range
99a3fc0
Set np.linspace dtype based on image dtype for the HistogramWidget
p-j-smith Jan 11, 2024
2fea1b0
update changelog
p-j-smith Jan 11, 2024
c59f1e2
ensure histograms of integer data have equal bin width
p-j-smith Jan 11, 2024
75bfe52
make linters happy
p-j-smith Jan 11, 2024
7b48bc3
convert bins array to list to make mypy happy
p-j-smith Jan 11, 2024
71f6716
Fix integer step size
dstansby Jan 13, 2024
166d776
Use integer bins for unisnged int data
p-j-smith Jan 15, 2024
1412149
ensure histogram bin step size is always a positive integer
p-j-smith Jan 15, 2024
610f19c
Ensure step size is at least 1
p-j-smith Jan 15, 2024
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
Prev Previous commit
Next Next commit
Fix integer step size
  • Loading branch information
@dstansby
dstansby committed Jan 13, 2024
commit 71f671662a70a746343762f9449ea66af9436ea8
2 changes: 1 addition & 1 deletion src/napari_matplotlib/histogram.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,7 @@ def draw(self) -> None:
# whole cube into memory.
if data.dtype.kind == "i":
# Make sure integer data types have integer sized bins
step = (np.max(data) - np.min(data)) // 100
step = 1 + (np.max(data) - np.min(data)) // 100
bins = np.arange(np.min(data), np.max(data) + step, step)
else:
bins = np.linspace(np.min(data), np.max(data), 100)
Expand Down