8000 Add SigmaClippedStats class by larrybradley · Pull Request #17221 · astropy/astropy · GitHub
[go: up one dir, main page]
Skip to content

Add SigmaClippedStats class #17221

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
larrybradley merged 10 commits into from
Oct 23, 2024
Merged

Add SigmaClippedStats class #17221

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
10 commits
Select commit Hold shift + click to select a range
8f75d8a
Add SigmaClippedStats class
larrybradley Oct 21, 2024
c2c177a
Add var method and nanvar function
larrybradley Oct 21, 2024
b58ef52
Add biweight_location and biweight_scale methods
larrybradley Oct 21, 2024
61b0cb6
Add mode and mad_std methods
larrybradley Oct 21, 2024
cc7ab21
Add nanmin/nanmax functions; add min, max, and sum to SigmaClippedStats
larrybradley Oct 22, 2024
7302e1d
Use SigmaClippedStats in sigma_clipped_stats
larrybradley Oct 21, 2024
2d79e17
Add SigmaClippedStats to the stats narrative docs
larrybradley Oct 21, 2024
0cdbe8d
Add SigmaClippedStats tests
larrybradley Oct 21, 2024
fc7631a
Add changelog entry
larrybradley Oct 21, 2024
58efcac
Add whats new entry
larrybradley Oct 22, 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
18 changes: 17 additions & 1 deletion astropy/stats/nanfunctions.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -77,7 +77,11 @@ def _apply_bottleneck(

result = function(array, axis=axis, **kwargs)
if isinstance(array, Quantity):
return array.__array_wrap__(result)
if function is bottleneck.nanvar:
result = array._result_as_quantity(result, array.unit**2, None)
else:
result = array.__array_wrap__(result)
return result
elif isinstance(result, float):
# For compatibility with numpy, always return a numpy scalar.
return np.float64(result)
Expand All @@ -86,16 +90,22 @@ def _apply_bottleneck(

bn_funcs = dict(
nansum=functools.partial(_apply_bottleneck, bottleneck.nansum),
nanmin=functools.partial(_apply_bottleneck, bottleneck.nanmin),
nanmax=functools.partial(_apply_bottleneck, bottleneck.nanmax),
nanmean=functools.partial(_apply_bottleneck, bottleneck.nanmean),
nanmedian=functools.partial(_apply_bottleneck, bottleneck.nanmedian),
nanstd=functools.partial(_apply_bottleneck, bottleneck.nanstd),
nanvar=functools.partial(_apply_bottleneck, bottleneck.nanvar),
)

np_funcs = dict(
nansum=np.nansum,
nanmin=np.nanmin,
nanmax=np.nanmax,
nanmean=np.nanmean,
nanmedian=np.nanmedian,
nanstd=np.nanstd,
nanvar=np.nanvar,
)

def _dtype_dispatch(func_name):
Expand All @@ -115,15 +125,21 @@ def wrapped(*args, **kwargs):
return wrapped

nansum = _dtype_dispatch("nansum")
nanmin = _dtype_dispatch("nanmin")
nanmax = _dtype_dispatch("nanmax")
nanmean = _dtype_dispatch("nanmean")
nanmedian = _dtype_dispatch("nanmedian")
nanstd = _dtype_dispatch("nanstd")
nanvar = _dtype_dispatch("nanvar")

else:
nansum = np.nansum
nanmin = np.nanmin
nanmax = np.nanmax
nanmean = np.nanmean
nanmedian = np.nanmedian
nanstd = np.nanstd
nanvar = np.nanvar


def nanmadstd(
Expand Down
Loading
0