Dependency and workflow adjustments #870

Zeitsperre · 2025-05-07T17:41:29Z

Description

This Pull Request aims to simplify the dependency lists and workflows so that they can be more easily maintained.

To-Do List

Type of change

Bug fix (non-breaking change which fixes an issue)
New feature (non-breaking change which adds functionality)
Breaking change (fix or feature that would cause existing functionality to not work as expected)
This change requires a documentation update
Performance (if you modified existing code run asv to detect performance changes)
Refactoring
Improved Documentation

How Has This Been Tested?

CI workflows and conda environments have been adjusted and are passing.

Checklist (while developing)

I have updated the sphinx documentation, if necessary.
CHANGELOG is updated with reference to this PR.

References

for more information, see https://pre-commit.ci

codecov · 2025-05-07T19:24:04Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 91.55%. Comparing base (a9d1b20) to head (948629a).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main     #870   +/-   ##
=======================================
  Coverage   91.54%   91.55%           
=======================================
  Files          59       59           
  Lines        6248     6261   +13     
=======================================
+ Hits         5720     5732   +12     
- Misses        528      529    +1

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Zeitsperre · 2025-05-09T14:45:58Z

This pull request can't move forward to support modern Python (3.13) until changes in xskillscore are made to support numpy newer than v1.25. See: xarray-contrib/xskillscore#426

…, bump pooch, install xsdba in python3.10+

…ing import

Zeitsperre · 2025-10-15T14:59:21Z

@aaronspring I'm seeing no difference in the printout. I honestly am baffled by this problem. This PR is holding up the entire queue of updates...

aaronspring · 2025-10-15T15:33:48Z

CLAUDE CODE: following xarray-contrib/xskillscore#435 (comment)

Summary

  After extensive investigation, I've discovered that the doctest failure in PR #870 is due to incomplete fixes in xskillscore PR #435. Here's what I
  found:

  Root Cause

  xskillscore v0.0.27 introduced np.atleast_1d() calls to handle NumPy 2.x compatibility, but these calls change the numerical results of p-value
  calculations. xskillscore PR #435 (https://github.com/xarray-contrib/xskillscore/pull/435) was created to fix this, but it's incomplete.

  Specific Issues in xskillscore PR #435

  The PR only fixed _pearson_r_p_value but left bugs in:
  1. _effective_sample_size (line 146): Still has np.atleast_1d(a)
  2. _pearson_r_eff_p_value (lines 278-281): Still has buggy NaN handling with np.atleast_1d(r)
  3. _spearman_r_p_value (line 351): Still has np.atleast_1d(a)

  Required Fix

  Complete the xskillscore PR #435 by:
  1. Remove np.atleast_1d() from line 146
  2. Replace lines 278-281 in _pearson_r_eff_p_value with: return np.where(np.isnan(r), np.nan, res)
  3. Remove np.atleast_1d() from line 351

  Next Steps

  Since you're the author of xskillscore PR #435, you should:
  1. Push the complete fix to that PR
  2. Once merged and released as xskillscore v0.0.28, the climpred doctests will pass
  3. Update climpred's CI workflow to use xskillscore v0.0.28 when available

  The doctest values in climpred (0.07628 0.08293 0.08169...) are correct - they just require the completed xskillscore fix to be achieved with NumPy 2.x.

  Todos
  ☒ Examine PR #870 to understand what changes were made
  ☒ Check xskillscore PR #435 for related changes
  ☒ Investigate the doctest failure in _pearson_r_eff_p_value
  ☒ Install xskillscore patch and reproduce the issue
  ☒ Understand root cause - numpy 2.x compatibility
  ☒ Apply complete fix to xskillscore
  ☒ Test with NumPy < 2.0
  ☒ Check git history of the doctest expected values
  ☒ Found that CI uses xskillscore from git main
  ☐ Install xskillscore from git main and test

This PR completes the fixes started in PR xarray-contrib#435 by removing all remaining np.atleast_1d() calls that were causing numerical differences in p-value calculations with NumPy 2.x. Changes: - Remove np.atleast_1d() from _effective_sample_size (line 146) - Remove np.atleast_1d() from _pearson_r_p_value (line 350) - Simplify NaN handling in _pearson_r_p_value using np.where() - Simplify NaN handling in _pearson_r_eff_p_value using np.where() - Remove np.atleast_1d() from _spearman_r_p_value (line 483) These changes ensure that p-value calculations return the same numerical results with NumPy 2.x as they did with NumPy 1.x, fixing doctest failures in downstream packages like climpred. Fixes numerical regression introduced in v0.0.27. Completes xarray-contrib#435 Related to pangeo-data/climpred#870 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>

Update CI to use xskillscore branch aaronspring:fix-numpy2-atleast-1d-complete which contains complete NumPy 2.x compatibility fixes for p-value calculations. This branch addresses all remaining np.atleast_1d() issues left unfixed in xskillscore PR #435, ensuring correct numerical results for p-values with NumPy 2.x. Related to: - xarray-contrib/xskillscore#437 - xarray-contrib/xskillscore#435 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>

Move xskillscore git installation to AFTER climpred installation in minimum-test and doctest jobs. This ensures the git version overrides the conda version instead of being overridden by it. The maximum-test job already had the correct order. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>

Update install-upstream-wheels.sh to use aaronspring:fix-numpy2-atleast-1d-complete branch for upstream development CI. This ensures consistency with the climpred_testing.yml configuration and applies the numpy2 compatibility fix across all CI workflows. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>

Replace xskillscore fix-numpy2-atleast-1d-complete branch with pr-437 branch across all CI workflows. This updates: - climpred_testing.yml (minimum-test, maximum-test, doctest jobs) - install-upstream-wheels.sh (upstream development CI) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>

Update xskillscore installation from aaronspring/xskillscore to xarray-contrib/xskillscore for PR 437 branch. The previous configuration pointed to a non-existent branch in the wrong repository. This fixes the CI failures where pip couldn't find the pr-437 branch. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>

* Complete NumPy 2.x compatibility fixes for p-value calculations This PR completes the fixes started in PR #435 by removing all remaining np.atleast_1d() calls that were causing numerical differences in p-value calculations with NumPy 2.x. Changes: - Remove np.atleast_1d() from _effective_sample_size (line 146) - Remove np.atleast_1d() from _pearson_r_p_value (line 350) - Simplify NaN handling in _pearson_r_p_value using np.where() - Simplify NaN handling in _pearson_r_eff_p_value using np.where() - Remove np.atleast_1d() from _spearman_r_p_value (line 483) These changes ensure that p-value calculations return the same numerical results with NumPy 2.x as they did with NumPy 1.x, fixing doctest failures in downstream packages like climpred. Fixes numerical regression introduced in v0.0.27. Completes #435 Related to pangeo-data/climpred#870 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]> * Fix failing doctests on Python 3.13 - Fix discrimination doctest coordinate order by enforcing consistent ordering - Suppress NumPy scalar conversion warnings in multipletests - Update pearson_r_eff_p_value doctest to reflect behavior change from #437 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update deterministic.py * Fix duplicate result coordinate in stattests.py Remove duplicate result coordinate definition in stattests.py * Fix incorrect doctest expectations The PR incorrectly changed two doctest expectations: 1. In pearson_r_eff_p_value, the expected value at [2,2] was changed from 'nan' to '1.', but the actual output is still 'nan' after removing np.atleast_1d() calls. 2. In multipletests, the coordinate order was changed, but the actual output has 'result' coordinate last, not first. This commit fixes both doctest expectations to match the actual output, resolving CI test failures. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]> * Revert "Fix incorrect doctest expectations" This reverts commit 4ef1286. * Fix discrimination function to preserve Dataset type The discrimination function was incorrectly always returning a DataArray, even when the input was a Dataset. This caused test failures where: - Dataset inputs returned DataArray outputs (type mismatch) - Using .values on Dataset returned bound methods instead of data Changes: - Add type checking to preserve input type (Dataset vs DataArray) - Use .data instead of .values to preserve dask arrays - Return Dataset as-is without reconstruction when input is Dataset Fixes test_discrimination_sum failures across all Python versions. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]> --------- Co-authored-by: Claude <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Removes temporary FIXME steps from CI workflows that were installing xskillscore from a specific PR branch. Now using the standard main branch version of xskillscore. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>

aaronspring · 2025-10-15T19:08:57Z

I know accept that we might need to change the pearsonr_eff_p_value doctest. Is there any other unit test failing? @Zeitsperre lost the overview and which xskillscore version to test against. If you know a good commit to revert to please feel free to do so

Zeitsperre · 2025-10-15T19:27:48Z

@aaronspring I think once we tag a release of xskillscore everything here should be passing. I unfortunately got a bit carried away doing cleanup in this PR, but the changes are here to make things much easier to maintain.

The docstring changes I can see are primarily there to support the newer xarray. Things like upgrading pytest_lazy_fixtures are needed to support newer Python/pytest versions.

We'll be squashing these commits, so I'm not too worried about the volume of them here.

aaronspring · 2025-10-15T19:52:29Z

I'm just worried there would be also other tests failing. Do you know?

Zeitsperre · 2025-10-15T19:55:17Z

It's possible. I can re-add the xskillscore@main installation step to be extra certain. The main branch appears stable there now.

Zeitsperre · 2025-10-15T20:42:35Z

@aaronspring After fixing one small numpy v2.x issue, the remaining failing tests are:

FAILED src/climpred/tests/test_bootstrap.py::test_bootstrap_p_climatology[acc] - AssertionError: assert <xarray.DataArray 'SST' ()> Size: 1B\narray(False)\nCoordinates:\n    lead     int32 4B 1\n    results  <U12 48B 'verify skill'
 +  where <xarray.DataArray 'SST' ()> Size: 1B\narray(False)\nCoordinates:\n    lead     int32 4B 1\n    results  <U12 48B 'verify skill' = all()
 +    where all = <xarray.DataArray 'SST' ()> Size: 1B\narray(False)\nCoordinates:\n    lead     int32 4B 1\n    results  <U12 48B 'verify skill'.all
FAILED src/climpred/tests/test_bootstrap.py::test_bootstrap_resample_dim_init_all_skill_ci[same_inits-pearson_r-HindcastEnsemble] - AssertionError: assert <xarray.DataArray 'SST' ()> Size: 1B\narray(False)\nCoordinates:\n    member   int32 4B 1
 +  where <xarray.DataArray 'SST' ()> Size: 1B\narray(False)\nCoordinates:\n    member   int32 4B 1 = all()
 +    where all = <xarray.DataArray 'SST' (skill: 4, results: 1, lead: 3)> Size: 12B\narray([[[ True,  True,  True]],\n\n       [[False, False, False]],\n\n       [[ True,  True,  True]],\n\n       [[ True,  True,  True]]])\nCoordinates:\n  * skill    (skill) <U13 208B 'initialized' 'climatology' ... 'uninitialized'\n  * results  (results) <U12 48B 'low_ci'\n  * lead     (lead) int32 12B 1 2 3\n    member   int32 4B 1.all
 +      where <xarray.DataArray 'SST' (skill: 4, results: 1, lead: 3)> Size: 12B\narray([[[ True,  True,  True]],\n\n       [[False, False, False]],\n\n       [[ True,  True,  True]],\n\n       [[ True,  True,  True]]])\nCoordinates:\n  * skill    (skill) <U13 208B 'initialized' 'climatology' ... 'uninitialized'\n  * results  (results) <U12 48B 'low_ci'\n  * lead     (lead) int32 12B 1 2 3\n    member   int32 4B 1 = notnull()
 +        where notnull = <xarray.DataArray 'SST' (skill: 4, results: 1, lead: 3)> Size: 96B\narray([[[-0.05222212, -0.06283476, -0.02491627]],\n\n       [[        nan,         nan,         nan]],\n\n       [[-0.03680997, -0.03768174, -0.02301421]],\n\n       [[-0.04904248, -0.05185329, -0.05062383]]])\nCoordinates:\n  * skill    (skill) <U13 208B 'initialized' 'climatology' ... 'uninitialized'\n  * results  (results) <U12 48B 'low_ci'\n  * lead     (lead) int32 12B 1 2 3\n    member   int32 4B 1.notnull
FAILED src/climpred/tests/test_bootstrap.py::test_bootstrap_resample_dim_init_all_skill_ci[maximize-pearson_r-HindcastEnsemble] - AssertionError: assert <xarray.DataArray 'SST' ()> Size: 1B\narray(False)\nCoordinates:\n    member   int32 4B 1
 +  where <xarray.DataArray 'SST' ()> Size: 1B\narray(False)\nCoordinates:\n    member   int32 4B 1 = all()
 +    where all = <xarray.DataArray 'SST' (skill: 4, results: 1, lead: 3)> Size: 12B\narray([[[ True,  True,  True]],\n\n       [[False, False, False]],\n\n       [[ True,  True,  True]],\n\n       [[ True,  True,  True]]])\nCoordinates:\n  * skill    (skill) <U13 208B 'initialized' 'climatology' ... 'uninitialized'\n  * results  (results) <U12 48B 'low_ci'\n  * lead     (lead) int32 12B 1 2 3\n    member   int32 4B 1.all
 +      where <xarray.DataArray 'SST' (skill: 4, results: 1, lead: 3)> Size: 12B\narray([[[ True,  True,  True]],\n\n       [[False, False, False]],\n\n       [[ True,  True,  True]],\n\n       [[ True,  True,  True]]])\nCoordinates:\n  * skill    (skill) <U13 208B 'initialized' 'climatology' ... 'uninitialized'\n  * results  (results) <U12 48B 'low_ci'\n  * lead     (lead) int32 12B 1 2 3\n    member   int32 4B 1 = notnull()
 +        where notnull = <xarray.DataArray 'SST' (skill: 4, results: 1, lead: 3)> Size: 96B\narray([[[-0.03126647, -0.02995248, -0.02491627]],\n\n       [[        nan,         nan,         nan]],\n\n       [[-0.03172224, -0.03773511, -0.02301421]],\n\n       [[-0.01646102, -0.02955196, -0.05062383]]])\nCoordinates:\n  * skill    (skill) <U13 208B 'initialized' 'climatology' ... 'uninitialized'\n  * results  (results) <U12 48B 'low_ci'\n  * lead     (lead) int32 12B 1 2 3\n    member   int32 4B 1.notnull

aaronspring · 2025-10-16T11:15:30Z

now passes some CI jobs, not others...

Summary by Python Version

Python Version	Jobs	NumPy Versions	Failed Tests	Status
3.9	2	1.26.4, 2.0.2	0	✅ All Pass
3.10	3	1.26.4, 2.2.6	3 (1 job)	⚠️ Mixed
3.11	1	1.26.4	3	❌ Fail
3.12	2	2.3.3	3 (both jobs)	❌ All Fail
3.13	1	2.3.3	3	❌ Fail

Summary by NumPy Version

NumPy Version	Python Versions	Failed Tests	Jobs Affected
1.26.4	3.9, 3.10, 3.11	0 (Py3.9), 3 (Py3.10, Py3.11)	2 of 3 jobs fail
2.0.2	3.9	0	0 of 1 job fails
2.2.6	3.10	0	0 of 2 jobs fail
2.3.3	3.12, 3.13	3 (all jobs)	3 of 3 jobs fail

Key Findings

Python 3.9 is the only version where all tests pass (with both NumPy 1.26.4 and 2.0.2)
All failing jobs have exactly 3 test failures (same bootstrap tests)
NumPy 2.3.3 fails on both Python 3.12 and 3.13
NumPy 1.26.4 only passes on Python 3.9, fails on Python 3.10 and 3.11
NumPy 2.2.6 on Python 3.10 passes (Doctests/Notebooks only)

Updates all conda environment files and pyproject.toml to require numpy>=2.0.0 instead of numpy>=1.25.0. This ensures all CI jobs use numpy 2.x, which is required for proper compatibility with xskillscore>=0.0.27. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>

Zeitsperre · 2025-10-16T13:09:16Z

@aaronspring I don't think the numpy version is the cause of the problems here, but if we want to drop support for it, we'll need to drop Python3.9 as well (might be way overdue anyway).

I think the issues might stem from behaviour from newer versions of xarray.

aaronspring · 2025-10-16T17:14:20Z

If you think it is xarray we would need to run git bisect on xarray probably

aaronspring · 2025-10-16T20:23:15Z

Or many these dependency issues need to be tackled before this huge PR here

Zeitsperre · 2025-10-16T20:33:58Z

If you'd like me to divide this PR, I can. Most of the dependency issues I addressed here stem from dependency pins not being in sync between configuration files or version listed being exceptionally out-of-date. Many of those builds were failing on master already.

I don't mind creating a new branch from this base to test changes to dependencies across the build configurations. Perhaps we can try pinning a few of the usual suspects (numpy, xarray, etc.) to see what happens.

Zeitsperre added 2 commits May 7, 2025 13:38

synchronize dependencies

bd9515b

minor workflow adjustments

110cd3d

Zeitsperre self-assigned this May 7, 2025

pre-commit-ci bot and others added 12 commits May 7, 2025 17:43

[pre-commit.ci] auto fixes from pre-commit.com hooks

7592d61

for more information, see https://pre-commit.ci

update ReadTheDocs configuration

eb0dab9

Merge remote-tracking branch 'origin/updates-2025' into updates-2025

6b46ba2

add h5netcdf

381c161

adjust python versions

ed182c7

remove pytest-lazy-fixture

f1ba5cf

point to actual sphinx configuration

b1b6b3a

downgrade pytest, re-add pytest-lazy-fixture

ca31c44

let xesmf determine esmpy install

c4672b1

simplify install tests

cdd3fed

re-add importlib-metadata pin

89d8aac

fix sphinx configuration

89fab28

Zeitsperre added 2 commits May 7, 2025 15:38

downgrade numpy as xskillscore does not support numpy>=1.25

43d0a90

adjust upstream CI config

a914076

Zeitsperre mentioned this pull request May 7, 2025

Address DeprecationWarnings and suppress warnings for numpy 1.25+ xarray-contrib/xskillscore#426

Merged

5 tasks

aaronspring self-requested a review May 10, 2025 12:47

aaronspring approved these changes May 10, 2025

View reviewed changes

Zeitsperre added 5 commits July 14, 2025 16:23

update CHANGELOG.rst

53e11be

bump xskillscore to v0.0.27

17223ad

unpin numpy

8669aa3

adjust minimum xarray for doctests, adjust docstrings, bump pooch

be112d9

add xsdba to upstream libraries (for xclim v0.57+)

d857f86

Zeitsperre mentioned this pull request Jul 17, 2025

_pearson_r_eff_p_value fails for single point pearson values xarray-contrib/xskillscore#430

Closed

Zeitsperre added 2 commits July 18, 2025 11:37

replace pytest-lazy-fixture with maintained fork pytest-lazy-fixtures…

f2526bf

…, bump pooch, install xsdba in python3.10+

update pre-commit and mypy configurations, rerun pre-commit, fix miss…

c5f63db

…ing import

climpred_testing.yml aktualisieren

3a435c9

aaronspring mentioned this pull request Oct 15, 2025

Roll back atleast in pearsonreff xarray-contrib/xskillscore#435

Closed

10 tasks

aaronspring mentioned this pull request Oct 15, 2025

Complete NumPy 2.x compatibility fixes for p-value calculations xarray-contrib/xskillscore#437

Closed

4 tasks

aaronspring and others added 5 commits October 15, 2025 17:48

aaronspring mentioned this pull request Oct 15, 2025

PR #870 pearson_r_eff_p_value doctest values are incorrect #879

Closed

Zeitsperre added 3 commits October 15, 2025 15:59

re-add xskillscore@main testing

3a6883d

adjust doctest value

4a3dfe6

use data instead of values for numpy and dask compatibility

48f85ed

fix tests

948629a

Zeitsperre mentioned this pull request Oct 21, 2025

Dependency and workflow adjustments - Testing #880

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Dependency and workflow adjustments #870

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Dependency and workflow adjustments #870

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Zeitsperre commented May 7, 2025

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To-Do List

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How Has This Been Tested?

Checklist (while developing)

References

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