TEST

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[sourcery-ai[bot]]

Sourcery Code Quality Report

❌  Merging this PR will decrease code quality in the affected files by 0.03%.

Quality metrics	Before	After	Change
Complexity	3.98 ⭐	3.97 ⭐	-0.01 👍
Method Length	215.71 ⛔	215.00 ⛔	-0.71 👍
Working memory	11.77 😞	11.79 😞	0.02 👎
Quality	51.42% 🙂	51.39% 🙂	-0.03% 👎

Other metrics	Before	After	Change
Lines	14345	16264	1919

Changed files	Quality Before	Quality After	Quality Change
setup.py	66.82% 🙂	66.82% 🙂	0.00%
examples/00_tutorials/plot_3d_and_4d_niimg.py	69.80% 🙂	69.80% 🙂	0.00%
examples/00_tutorials/plot_decoding_tutorial.py	40.11% 😞	40.11% 😞	0.00%
examples/00_tutorials/plot_nilearn_101.py	84.09% ⭐	84.09% ⭐	0.00%
examples/00_tutorials/plot_python_101.py	91.06% ⭐	91.06% ⭐	0.00%
examples/00_tutorials/plot_single_subject_single_run.py	39.84% 😞	39.84% 😞	0.00%
examples/01_plotting/plot_atlas.py	83.28% ⭐	83.28% ⭐	0.00%
examples/01_plotting/plot_carpet.py	49.87% 😞	49.87% 😞	0.00%
examples/01_plotting/plot_colormaps.py	48.95% 😞	48.95% 😞	0.00%
examples/01_plotting/plot_dim_plotting.py	79.20% ⭐	79.20% ⭐	0.00%
examples/01_plotting/plot_haxby_masks.py	55.38% 🙂	55.38% 🙂	0.00%
examples/01_plotting/plot_multiscale_parcellations.py	82.19% ⭐	82.19% ⭐	0.00%
examples/01_plotting/plot_overlay.py	72.98% 🙂	72.98% 🙂	0.00%
examples/01_plotting/plot_prob_atlas.py	50.98% 🙂	50.90% 🙂	-0.08% 👎
examples/01_plotting/plot_visualization.py	66.39% 🙂	66.39% 🙂	0.00%
examples/01_plotting/plot_visualize_megatrawls_netmats.py	87.65% ⭐	87.65% ⭐	0.00%
examples/02_decoding/plot_haxby_anova_svm.py	54.70% 🙂	54.70% 🙂	0.00%
examples/02_decoding/plot_haxby_different_estimators.py	30.15% 😞	30.15% 😞	0.00%
examples/02_decoding/plot_haxby_full_analysis.py	37.67% 😞	37.66% 😞	-0.01% 👎
examples/02_decoding/plot_haxby_glm_decoding.py	40.01% 😞	40.01% 😞	0.00%
examples/02_decoding/plot_haxby_grid_search.py	33.56% 😞	33.56% 😞	0.00%
examples/02_decoding/plot_haxby_multiclass.py	45.53% 😞	45.53% 😞	0.00%
examples/02_decoding/plot_haxby_searchlight.py	44.54% 😞	44.54% 😞	0.00%
examples/02_decoding/plot_haxby_stimuli.py	61.20% 🙂	61.20% 🙂	0.00%
examples/02_decoding/plot_miyawaki_encoding.py	48.46% 😞	48.45% 😞	-0.01% 👎
examples/02_decoding/plot_miyawaki_reconstruction.py	49.48% 😞	49.48% 😞	0.00%
examples/02_decoding/plot_oasis_vbm.py	39.20% 😞	39.20% 😞	0.00%
examples/02_decoding/plot_oasis_vbm_space_net.py	54.98% 🙂	54.98% 🙂	0.00%
examples/02_decoding/plot_simulated_data.py	45.06% 😞	45.04% 😞	-0.02% 👎
examples/03_connectivity/plot_atlas_comparison.py	67.32% 🙂	67.32% 🙂	0.00%
examples/03_connectivity/plot_compare_decomposition.py	50.42% 🙂	50.42% 🙂	0.00%
examples/03_connectivity/plot_data_driven_parcellations.py	36.39% 😞	36.40% 😞	0.01% 👍
examples/03_connectivity/plot_extract_regions_dictlearning_maps.py	43.04% 😞	43.04% 😞	0.00%
examples/03_connectivity/plot_inverse_covariance_connectome.py	63.09% 🙂	63.09% 🙂	0.00%
examples/03_connectivity/plot_multi_subject_connectome.py	59.92% 🙂	59.92% 🙂	0.00%
examples/03_connectivity/plot_probabilistic_atlas_extraction.py	64.16% 🙂	64.16% 🙂	0.00%
examples/03_connectivity/plot_seed_to_voxel_correlation.py	53.64% 🙂	53.64% 🙂	0.00%
examples/03_connectivity/plot_signal_extraction.py	43.20% 😞	43.20% 😞	0.00%
examples/03_connectivity/plot_simulated_connectome.py	37.70% 😞	37.70% 😞	0.00%
examples/03_connectivity/plot_sphere_based_connectome.py	34.90% 😞	34.90% 😞	0.00%
examples/04_glm_first_level/plot_adhd_dmn.py	48.93% 😞	49.23% 😞	0.30% 👍
examples/04_glm_first_level/plot_bids_features.py	48.54% 😞	48.54% 😞	0.00%
examples/04_glm_first_level/plot_design_matrix.py	44.89% 😞	44.89% 😞	0.00%
examples/04_glm_first_level/plot_fir_model.py	49.73% 😞	49.79% 😞	0.06% 👍
examples/04_glm_first_level/plot_first_level_details.py	58.55% 🙂	58.58% 🙂	0.03% 👍
examples/04_glm_first_level/plot_predictions_residuals.py	38.08% 😞	38.09% 😞	0.01% 👍
examples/04_glm_first_level/plot_spm_multimodal_faces.py	40.98% 😞	41.07% 😞	0.09% 👍
examples/04_glm_first_level/plot_write_events_file.py	61.16% 🙂	61.16% 🙂	0.00%
examples/05_glm_second_level/plot_oasis.py	50.50% 🙂	50.50% 🙂	0.00%
examples/05_glm_second_level/plot_proportion_activated_voxels.py	69.83% 🙂	69.83% 🙂	0.00%
examples/05_glm_second_level/plot_second_level_association_test.py	49.85% 😞	49.95% 😞	0.10% 👍
examples/05_glm_second_level/plot_second_level_design_matrix.py	70.41% 🙂	70.41% 🙂	0.00%
examples/05_glm_second_level/plot_second_level_one_sample_test.py	41.52% 😞	41.52% 😞	0.00%
examples/05_glm_second_level/plot_second_level_two_sample_test.py	45.78% 😞	45.78% 😞	0.00%
examples/05_glm_second_level/plot_thresholding.py	56.38% 🙂	56.38% 🙂	0.00%
examples/06_manipulating_images/plot_affine_transformation.py	44.90% 😞	44.90% 😞	0.00%
examples/06_manipulating_images/plot_compare_mean_image.py	81.23% ⭐	81.23% ⭐	0.00%
examples/06_manipulating_images/plot_extract_regions_labels_image.py	74.67% 🙂	74.67% 🙂	0.00%
examples/06_manipulating_images/plot_extract_rois_smith_atlas.py	63.83% 🙂	63.83% 🙂	0.00%
examples/06_manipulating_images/plot_extract_rois_statistical_maps.py	67.55% 🙂	67.55% 🙂	0.00%
examples/06_manipulating_images/plot_mask_computation.py	48.34% 😞	48.34% 😞	0.00%
examples/06_manipulating_images/plot_nifti_labels_simple.py	65.65% 🙂	65.65% 🙂	0.00%
examples/06_manipulating_images/plot_nifti_simple.py	59.74% 🙂	59.74% 🙂	0.00%
examples/06_manipulating_images/plot_roi_extraction.py	36.87% 😞	36.87% 😞	0.00%
examples/06_manipulating_images/plot_smooth_mean_image.py	80.68% ⭐	80.68% ⭐	0.00%
examples/07_advanced/plot_advanced_decoding_scikit.py	38.46% 😞	38.45% 😞	-0.01% 👎
examples/07_advanced/plot_age_group_prediction_cross_val.py	49.66% 😞	49.66% 😞	0.00%
examples/07_advanced/plot_beta_series.py	47.23% 😞	47.23% 😞	0.00%
examples/07_advanced/plot_bids_analysis.py	49.34% 😞	49.34% 😞	0.00%
examples/07_advanced/plot_haxby_mass_univariate.py	40.17% 😞	40.17% 😞	0.00%
examples/07_advanced/plot_ica_neurovault.py	32.77% 😞	32.82% 😞	0.05% 👍
examples/07_advanced/plot_ica_resting_state.py	66.56% 🙂	66.56% 🙂	0.00%
examples/07_advanced/plot_localizer_mass_univariate_methods.py	46.40% 😞	46.40% 😞	0.00%
examples/07_advanced/plot_localizer_simple_analysis.py	56.63% 🙂	56.63% 🙂	0.00%
examples/07_advanced/plot_neurovault_meta_analysis.py	75.32% ⭐	75.32% ⭐	0.00%
maint_tools/show-python-packages-versions.py	85.99% ⭐	85.99% ⭐	0.00%
nilearn/image/__init__.py	62.81% 🙂	62.81% 🙂	0.00%
nilearn/image/image.py	57.01% 🙂	56.93% 🙂	-0.08% 👎
nilearn/image/resampling.py	28.56% 😞	28.51% 😞	-0.05% 👎
nilearn/image/tests/test_image.py	65.04% 🙂	64.96% 🙂	-0.08% 👎
nilearn/image/tests/test_resampling.py	61.73% 🙂	61.74% 🙂	0.01% 👍

Here are some functions in these files that still need a tune-up:

File	Function	Complexity	Length	Working Memory	Quality	Recommendation
nilearn/image/resampling.py	resample_img	58 ⛔	910 ⛔	27 ⛔	3.40% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
nilearn/image/image.py	new_img_like	31 😞	253 ⛔	12 😞	27.14% 😞	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
nilearn/image/resampling.py	reorder_img	11 🙂	409 ⛔	16 ⛔	31.33% 😞	Try splitting into smaller methods. Extract out complex expressions
nilearn/image/image.py	_smooth_array	18 🙂	216 ⛔	11 😞	38.94% 😞	Try splitting into smaller methods. Extract out complex expressions
nilearn/image/image.py	clean_img	7 ⭐	197 😞	20 ⛔	39.46% 😞	Try splitting into smaller methods. Extract out complex expressions

Legend and Explanation

The emojis denote the absolute quality of the code:

• ⭐ excellent
• 🙂 good
• 😞 poor
• ⛔ very poor

The 👍 and 👎 indicate whether the quality has improved or gotten worse with this pull request.

---

Please see our documentation here for details on how these metrics are calculated.

We are actively working on this report - lots more documentation and extra metrics to come!

Help us improve this quality report!

[codecov-commenter]

Codecov Report

Merging #20 (f6c5ca1) into main (bf2eb51) will decrease coverage by 0.01%. The diff coverage is 93.23%.

:exclamation: Current head f6c5ca1 differs from pull request most recent head e893389. Consider uploading reports for the commit e893389 to get more accurate results

@@            Coverage Diff             @@
##             main      #20      +/-   ##
==========================================
- Coverage   91.01%   91.00%   -0.01%     
==========================================
  Files         133      133              
  Lines       15384    15378       -6     
  Branches     3212     3210       -2     
==========================================
- Hits        14001    13995       -6     
  Misses        819      819              
  Partials      564      564              

Impacted Files	Coverage Δ
nilearn/decoding/space_net_solvers.py	98.05% <ø> (ø)
nilearn/image/resampling.py	93.99% <89.28%> (ø)
nilearn/image/image.py	95.65% <94.91%> (-0.08%)	:arrow_down:
nilearn/decoding/decoder.py	95.97% <100.00%> (ø)
nilearn/decoding/searchlight.py	93.75% <100.00%> (ø)
nilearn/decoding/space_net.py	88.18% <100.00%> (ø)
nilearn/decomposition/_base.py	94.87% <100.00%> (ø)
nilearn/decomposition/_multi_pca.py	100.00% <100.00%> (ø)
nilearn/decomposition/canica.py	91.66% <100.00%> (ø)
nilearn/decomposition/dict_learning.py	89.06% <100.00%> (ø)
... and 1 more

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