.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/07_advanced/plot_localizer_mass_univariate_methods.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. or to run this example in your browser via JupyterLite or Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_07_advanced_plot_localizer_mass_univariate_methods.py: Massively univariate analysis of a motor task from the Localizer dataset ======================================================================== This example shows the results obtained in a massively univariate analysis performed at the inter-subject level with various methods. We use the [left button press (auditory cue)] task from the Localizer dataset and seek association between the contrast values and a variate that measures the speed of pseudo-word reading. No confounding variate is included in the model. 1. A standard :term:`ANOVA` is performed. Data smoothed at 5 :term:`voxels` :term:`FWHM` are used. 2. A permuted Ordinary Least Squares algorithm is run at each :term:`voxel`. Data smoothed at 5 :term:`voxels` :term:`FWHM` are used. .. GENERATED FROM PYTHON SOURCE LINES 18-23 .. code-block:: Python from nilearn._utils.helpers import check_matplotlib check_matplotlib() .. GENERATED FROM PYTHON SOURCE LINES 24-30 .. code-block:: Python import numpy as np from nilearn import datasets from nilearn.maskers import NiftiMasker from nilearn.mass_univariate import permuted_ols .. GENERATED FROM PYTHON SOURCE LINES 31-32 Load Localizer contrast .. GENERATED FROM PYTHON SOURCE LINES 32-55 .. code-block:: Python n_samples = 94 localizer_dataset = datasets.fetch_localizer_contrasts( ["left button press (auditory cue)"], n_subjects=n_samples, ) # print basic information on the dataset print( "First contrast nifti image (3D) is located " f"at: {localizer_dataset.cmaps[0]}" ) tested_var = localizer_dataset.ext_vars["pseudo"] # Quality check / Remove subjects with bad tested variate mask_quality_check = np.where(np.logical_not(np.isnan(tested_var)))[0] n_samples = mask_quality_check.size contrast_map_filenames = [ localizer_dataset.cmaps[i] for i in mask_quality_check ] tested_var = tested_var[mask_quality_check].to_numpy().reshape((-1, 1)) print(f"Actual number of subjects after quality check: {int(n_samples)}") .. rst-class:: sphx-glr-script-out .. code-block:: none [fetch_localizer_contrasts] Dataset directory found: /home/runner/nilearn_data/brainomics_localizer First contrast nifti image (3D) is located at: /home/runner/nilearn_data/brainomics_localizer/brainomics_data/S01/cmaps_LeftAuditoryClick.nii.gz Actual number of subjects after quality check: 89 .. GENERATED FROM PYTHON SOURCE LINES 56-57 Mask data .. GENERATED FROM PYTHON SOURCE LINES 57-63 .. code-block:: Python nifti_masker = NiftiMasker( smoothing_fwhm=5, memory="nilearn_cache", memory_level=1, verbose=1 ) fmri_masked = nifti_masker.fit_transform(contrast_map_filenames) .. rst-class:: sphx-glr-script-out .. code-block:: none \[NiftiMasker.wrapped] Loading data from ['/home/runner/nilearn_data/brainomics_ localizer/brainomics_data/S01/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nil earn_data/brainomics_localizer/brainomics_data/S02/cmaps_LeftAuditoryClick.nii.g z', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S03/cmaps_Le ftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainom ics_data/S04/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainom ics_localizer/brainomics_data/S05/cmaps_LeftAuditoryClick.nii.gz', '/home/runner /nilearn_data/brainomics_localizer/brainomics_data/S06/cmaps_LeftAuditoryClick.n ii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S07/cmap s_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/bra inomics_data/S08/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/bra inomics_localizer/brainomics_data/S09/cmaps_LeftAuditoryClick.nii.gz', '/home/ru nner/nilearn_data/brainomics_localizer/brainomics_data/S10/cmaps_LeftAuditoryCli ck.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S11/ cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer /brainomics_data/S12/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data /brainomics_localizer/brainomics_data/S13/cmaps_LeftAuditoryClick.nii.gz', '/hom e/runner/nilearn_data/brainomics_localizer/brainomics_data/S14/cmaps_LeftAuditor yClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/ S16/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_local izer/brainomics_data/S17/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_ data/brainomics_localizer/brainomics_data/S18/cmaps_LeftAuditoryClick.nii.gz', ' /home/runner/nilearn_data/brainomics_localizer/brainomics_data/S19/cmaps_LeftAud itoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_d ata/S20/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_l ocalizer/brainomics_data/S21/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nile arn_data/brainomics_localizer/brainomics_data/S22/cmaps_LeftAuditoryClick.nii.gz ', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S23/cmaps_Lef tAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomi cs_data/S24/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomi cs_localizer/brainomics_data/S25/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/ nilearn_data/brainomics_localizer/brainomics_data/S26/cmaps_LeftAuditoryClick.ni i.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S27/cmaps _LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brai nomics_data/S28/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brai nomics_localizer/brainomics_data/S29/cmaps_LeftAuditoryClick.nii.gz', '/home/run ner/nilearn_data/brainomics_localizer/brainomics_data/S30/cmaps_LeftAuditoryClic k.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S31/c maps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/ brainomics_data/S32/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/ brainomics_localizer/brainomics_data/S33/cmaps_LeftAuditoryClick.nii.gz', '/home /runner/nilearn_data/brainomics_localizer/brainomics_data/S34/cmaps_LeftAuditory Click.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S 35/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_locali zer/brainomics_data/S36/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_d ata/brainomics_localizer/brainomics_data/S37/cmaps_LeftAuditoryClick.nii.gz', '/ home/runner/nilearn_data/brainomics_localizer/brainomics_data/S39/cmaps_LeftAudi toryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_da ta/S40/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_lo calizer/brainomics_data/S41/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilea rn_data/brainomics_localizer/brainomics_data/S42/cmaps_LeftAuditoryClick.nii.gz' , '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S43/cmaps_Left AuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomic s_data/S44/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomic s_localizer/brainomics_data/S45/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/n ilearn_data/brainomics_localizer/brainomics_data/S46/cmaps_LeftAuditoryClick.nii .gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S47/cmaps_ LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brain omics_data/S48/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brain omics_localizer/brainomics_data/S49/cmaps_LeftAuditoryClick.nii.gz', '/home/runn er/nilearn_data/brainomics_localizer/brainomics_data/S50/cmaps_LeftAuditoryClick .nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S51/cm aps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/b rainomics_data/S52/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/b rainomics_localizer/brainomics_data/S53/cmaps_LeftAuditoryClick.nii.gz', '/home/ runner/nilearn_data/brainomics_localizer/brainomics_data/S54/cmaps_LeftAuditoryC lick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S5 5/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localiz er/brainomics_data/S56/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_da ta/brainomics_localizer/brainomics_data/S57/cmaps_LeftAuditoryClick.nii.gz', '/h ome/runner/nilearn_data/brainomics_localizer/brainomics_data/S58/cmaps_LeftAudit oryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_dat a/S59/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_loc alizer/brainomics_data/S60/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilear n_data/brainomics_localizer/brainomics_data/S61/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S63/cmaps_LeftA uditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics _data/S64/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics _localizer/brainomics_data/S65/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/ni learn_data/brainomics_localizer/brainomics_data/S66/cmaps_LeftAuditoryClick.nii. gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S67/cmaps_L eftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/braino mics_data/S68/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/braino mics_localizer/brainomics_data/S69/cmaps_LeftAuditoryClick.nii.gz', '/home/runne r/nilearn_data/brainomics_localizer/brainomics_data/S70/cmaps_LeftAuditoryClick. nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S71/cma ps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/br ainomics_data/S72/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/br ainomics_localizer/brainomics_data/S73/cmaps_LeftAuditoryClick.nii.gz', '/home/r unner/nilearn_data/brainomics_localizer/brainomics_data/S74/cmaps_LeftAuditoryCl ick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S75 /cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localize r/brainomics_data/S76/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_dat a/brainomics_localizer/brainomics_data/S77/cmaps_LeftAuditoryClick.nii.gz', '/ho me/runner/nilearn_data/brainomics_localizer/brainomics_data/S78/cmaps_LeftAudito ryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data /S79/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_loca lizer/brainomics_data/S80/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn _data/brainomics_localizer/brainomics_data/S82/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S83/cmaps_LeftAu ditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_ data/S84/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_ localizer/brainomics_data/S85/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nil earn_data/brainomics_localizer/brainomics_data/S86/cmaps_LeftAuditoryClick.nii.g z', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S88/cmaps_Le ftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainom ics_data/S89/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainom ics_localizer/brainomics_data/S90/cmaps_LeftAuditoryClick.nii.gz', '/home/runner /nilearn_data/brainomics_localizer/brainomics_data/S91/cmaps_LeftAuditoryClick.n ii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S92/cmap s_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/bra inomics_data/S93/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/bra inomics_localizer/brainomics_data/S94/cmaps_LeftAuditoryClick.nii.gz'] \[NiftiMasker.wrapped] Computing mask ________________________________________________________________________________ [Memory] Calling nilearn.masking.compute_background_mask... compute_background_mask([ '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S01/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S02/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S03/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S04/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S05/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S06/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S07/cmaps_LeftAu..., verbose=0) __________________________________________compute_background_mask - 0.4s, 0.0min \[NiftiMasker.wrapped] Resampling mask ________________________________________________________________________________ [Memory] Calling nilearn.image.resampling.resample_img... resample_img(, target_affine=None, target_shape=None, copy=False, interpolation='nearest') _____________________________________________________resample_img - 0.0s, 0.0min \[NiftiMasker.wrapped] Finished fit /home/runner/work/nilearn/nilearn/examples/07_advanced/plot_localizer_mass_univariate_methods.py:60: FutureWarning: boolean values for 'standardize' will be deprecated in nilearn 0.15.0. Use 'zscore_sample' instead of 'True' or use 'None' instead of 'False'. ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask([ '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S01/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S02/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S03/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S04/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S05/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S06/cmaps_LeftAuditoryClick.nii.gz', '/home/runner/nilearn_data/brainomics_localizer/brainomics_data/S07/cmaps_LeftAu..., , { 'clean_args': None, 'clean_kwargs': {}, 'cmap': 'gray', 'detrend': False, 'dtype': None, 'high_pass': None, 'high_variance_confounds': False, 'low_pass': None, 'reports': True, 'runs': None, 'smoothing_fwhm': 5, 'standardize': False, 'standardize_confounds': True, 't_r': None, 'target_affine': None, 'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None) \[NiftiMasker.wrapped] Loading data from \[NiftiMasker.wrapped] Smoothing images \[NiftiMasker.wrapped] Extracting region signals \[NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 1.0s, 0.0min .. GENERATED FROM PYTHON SOURCE LINES 64-65 Anova (parametric F-scores) .. GENERATED FROM PYTHON SOURCE LINES 65-76 .. code-block:: Python from sklearn.feature_selection import f_regression _, pvals_anova = f_regression(fmri_masked, tested_var.ravel(), center=True) pvals_anova *= fmri_masked.shape[1] pvals_anova[np.isnan(pvals_anova)] = 1 pvals_anova[pvals_anova > 1] = 1 neg_log_pvals_anova = -np.log10(pvals_anova) neg_log_pvals_anova_unmasked = nifti_masker.inverse_transform( neg_log_pvals_anova ) .. rst-class:: sphx-glr-script-out .. code-block:: none \[NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([-0., ..., -0.]), ) ___________________________________________________________unmask - 0.0s, 0.0min .. GENERATED FROM PYTHON SOURCE LINES 77-87 Perform massively univariate analysis with permuted OLS This method will produce both voxel-level FWE-corrected -log10 p-values and :term:`TFCE`-based FWE-corrected -log10 p-values. .. note:: :func:`~nilearn.mass_univariate.permuted_ols` can support a wide range of analysis designs, depending on the ``tested_var``. For example, if you wished to perform a one-sample test, you could simply provide an array of ones (e.g., ``np.ones(n_samples)``). .. GENERATED FROM PYTHON SOURCE LINES 87-105 .. code-block:: Python ols_outputs = permuted_ols( tested_var, # this is equivalent to the design matrix, in array form fmri_masked, model_intercept=True, masker=nifti_masker, tfce=True, n_perm=100, # 100 for the sake of time. Ideally, this should be 10000. verbose=1, # display progress bar n_jobs=2, # can be changed to use more CPUs ) neg_log_pvals_permuted_ols_unmasked = nifti_masker.inverse_transform( ols_outputs["logp_max_t"][0, :] # select first regressor ) neg_log_pvals_tfce_unmasked = nifti_masker.inverse_transform( ols_outputs["logp_max_tfce"][0, :] # select first regressor ) .. rst-class:: sphx-glr-script-out .. code-block:: none \[NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([[ 1.604273, ..., -0.864518]]), ) ___________________________________________________________unmask - 0.0s, 0.0min [Parallel(n_jobs=2)]: Using backend LokyBackend with 2 concurrent workers. [Parallel(n_jobs=2)]: Done 2 out of 2 | elapsed: 25.2s remaining: 0.0s [Parallel(n_jobs=2)]: Done 2 out of 2 | elapsed: 25.2s finished \[NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([-0., ..., -0.]), ) ___________________________________________________________unmask - 0.0s, 0.0min \[NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([ 0.026598, ..., -0. ]), ) ___________________________________________________________unmask - 0.0s, 0.0min .. GENERATED FROM PYTHON SOURCE LINES 106-107 Visualization .. GENERATED FROM PYTHON SOURCE LINES 107-155 .. code-block:: Python import matplotlib.pyplot as plt from nilearn import plotting from nilearn.image import get_data threshold = -np.log10(0.1) # 10% corrected vmax = max( np.amax(ols_outputs["logp_max_t"]), np.amax(neg_log_pvals_anova), np.amax(ols_outputs["logp_max_tfce"]), ) images_to_plot = { "Parametric Test\n(Bonferroni FWE)": neg_log_pvals_anova_unmasked, "Permutation Test\n(Max t-statistic FWE)": ( neg_log_pvals_permuted_ols_unmasked ), "Permutation Test\n(Max TFCE FWE)": neg_log_pvals_tfce_unmasked, } fig, axes = plt.subplots(figsize=(10, 4), ncols=3) for i_col, (title, img) in enumerate(images_to_plot.items()): ax = axes[i_col] n_detections = (get_data(img) > threshold).sum() new_title = f"{title}\n{n_detections} sig. voxels" plotting.plot_glass_brain( img, vmax=vmax, display_mode="z", threshold=threshold, vmin=threshold, cmap="inferno", figure=fig, axes=ax, ) ax.set_title(new_title) fig.suptitle( "Group left button press ($-\\log_{10}$ p-values)", y=1, fontsize=16, ) fig.subplots_adjust(top=0.75, wspace=0.5) plotting.show() .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_localizer_mass_univariate_methods_001.png :alt: Group left button press ($-\log_{10}$ p-values), Parametric Test (Bonferroni FWE) 3 sig. voxels, Permutation Test (Max t-statistic FWE) 8 sig. voxels, Permutation Test (Max TFCE FWE) 623 sig. voxels :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_localizer_mass_univariate_methods_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 32.662 seconds) **Estimated memory usage:** 410 MB .. _sphx_glr_download_auto_examples_07_advanced_plot_localizer_mass_univariate_methods.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/nilearn/nilearn/0.14.0?urlpath=lab/tree/notebooks/auto_examples/07_advanced/plot_localizer_mass_univariate_methods.ipynb :alt: Launch binder :width: 150 px .. container:: lite-badge .. image:: images/jupyterlite_badge_logo.svg :target: ../../lite/lab/index.html?path=auto_examples/07_advanced/plot_localizer_mass_univariate_methods.ipynb :alt: Launch JupyterLite :width: 150 px .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_localizer_mass_univariate_methods.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_localizer_mass_univariate_methods.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_localizer_mass_univariate_methods.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_