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.

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

Improvements to pearsonr docstring #8

Merged
merged 1 commit into from
Jan 18, 2024
Merged

Improvements to pearsonr docstring #8

Changes from all commits
Commits
Show all changes
1 commit
Select commit
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: 14 additions & 13 deletions lib/iris/analysis/stats.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@ def pearsonr(

Parameters
----------
cube_a, cube_b : cubes
cube_a, cube_b : :class:`iris.cube.Cube`
Cubes between which the correlation will be calculated. The cubes
should either be the same shape and have the same dimension coordinates
or one cube should be broadcastable to the other. Broadcasting rules
Expand All @@ -37,21 +37,22 @@ def pearsonr(
names are provided then correlation will be calculated over all common
cube dimensions.
weights : :class:`numpy.ndarray`, optional
Weights array of same shape as (the smaller of) cube_a and cube_b. Note
that latitude/longitude area weights can be calculated using
Weights array of same shape as (the smaller of) `cube_a` and `cube_b`.
Note that latitude/longitude area weights can be calculated using
:func:`iris.analysis.cartography.area_weights`.
mdtol : float, default=1.0
Tolerance of missing data. The missing data fraction is calculated
based on the number of grid cells masked in both cube_a and cube_b. If
this fraction exceed mdtol, the returned value in the corresponding
cell is masked. mdtol=0 means no missing data is tolerated while
mdtol=1 means the resulting element will be masked if and only if all
contributing elements are masked in cube_a or cube_b. Defaults to 1.
based on the number of grid cells masked in both `cube_a` and `cube_b`.
If this fraction exceed `mdtol`, the returned value in the
corresponding cell is masked. `mdtol` =0 means no missing data is
tolerated while `mdtol` =1 means the resulting element will be masked
if and only if all contributing elements are masked in `cube_a` or
`cube_b`.
common_mask : bool, default=False
If True, applies a common mask to cube_a and cube_b so only cells which
are unmasked in both cubes contribute to the calculation. If False, the
variance for each cube is calculated from all available cells. Defaults
to False.
If ``True``, applies a common mask to cube_a and cube_b so only cells
which are unmasked in both cubes contribute to the calculation. If
``False``, the variance for each cube is calculated from all available
cells.

Returns
-------
Expand All @@ -61,7 +62,7 @@ def pearsonr(
cubes.

For example providing two time/altitude/latitude/longitude cubes and
corr_coords of 'latitude' and 'longitude' will result in a
`corr_coords` of 'latitude' and 'longitude' will result in a
time/altitude cube describing the latitude/longitude (i.e. pattern)
correlation at each time/altitude point.

Expand Down