.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/02_decoding/plot_haxby_full_analysis.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 Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_02_decoding_plot_haxby_full_analysis.py: ROI-based decoding analysis in Haxby et al. dataset =================================================== In this script we reproduce the data analysis conducted by :footcite:t:`Haxby2001`. Specifically, we look at decoding accuracy for different objects in three different masks: the full ventral stream (mask_vt), the house selective areas (mask_house) and the face selective areas (mask_face), that have been defined via a standard GLM-based analysis. .. include:: ../../../examples/masker_note.rst .. GENERATED FROM PYTHON SOURCE LINES 16-21 .. code-block:: Python # Fetch data using nilearn dataset fetcher from nilearn import datasets from nilearn.plotting import show .. GENERATED FROM PYTHON SOURCE LINES 22-24 Load and prepare the data ------------------------- .. GENERATED FROM PYTHON SOURCE LINES 24-62 .. code-block:: Python # by default we fetch 2nd subject data for analysis haxby_dataset = datasets.fetch_haxby() func_filename = haxby_dataset.func[0] # Print basic information on the dataset print( "First subject anatomical nifti image (3D) located is " f"at: {haxby_dataset.anat[0]}" ) print( "First subject functional nifti image (4D) is located " f"at: {func_filename}" ) # load labels import pandas as pd # Load nilearn NiftiMasker, the practical masking and unmasking tool from nilearn.maskers import NiftiMasker labels = pd.read_csv(haxby_dataset.session_target[0], sep=" ") stimuli = labels["labels"] # identify resting state labels in order to be able to remove them task_mask = stimuli != "rest" # find names of remaining active labels categories = stimuli[task_mask].unique() # extract tags indicating to which acquisition run a tag belongs run_labels = labels["chunks"][task_mask] # apply the task_mask to fMRI data (func_filename) from nilearn.image import index_img task_data = index_img(func_filename, task_mask) .. rst-class:: sphx-glr-script-out .. code-block:: none First subject anatomical nifti image (3D) located is at: /home/himanshu/nilearn_data/haxby2001/subj2/anat.nii.gz First subject functional nifti image (4D) is located at: /home/himanshu/nilearn_data/haxby2001/subj2/bold.nii.gz .. GENERATED FROM PYTHON SOURCE LINES 63-68 Decoding on the different masks ------------------------------- The classifier used here is a support vector classifier (svc). We use class:`nilearn.decoding.Decoder` and specify the classifier. .. GENERATED FROM PYTHON SOURCE LINES 68-77 .. code-block:: Python import numpy as np # Make a data splitting object for cross validation from sklearn.model_selection import LeaveOneGroupOut from nilearn.decoding import Decoder cv = LeaveOneGroupOut() .. GENERATED FROM PYTHON SOURCE LINES 78-79 We use :class:`nilearn.decoding.Decoder` to estimate a baseline. .. GENERATED FROM PYTHON SOURCE LINES 79-127 .. code-block:: Python mask_names = ["mask_vt", "mask_face", "mask_house"] mask_scores = {} mask_chance_scores = {} for mask_name in mask_names: print(f"Working on {mask_name}") # For decoding, standardizing is often very important mask_filename = haxby_dataset[mask_name][0] masker = NiftiMasker(mask_img=mask_filename, standardize="zscore_sample") mask_scores[mask_name] = {} mask_chance_scores[mask_name] = {} for category in categories: print(f"Processing {mask_name} {category}") classification_target = stimuli[task_mask] == category # Specify the classifier to the decoder object. # With the decoder we can input the masker directly. # We are using the svc_l1 here because it is intra subject. decoder = Decoder( estimator="svc_l1", cv=cv, mask=masker, scoring="roc_auc", standardize="zscore_sample", ) decoder.fit(task_data, classification_target, groups=run_labels) mask_scores[mask_name][category] = decoder.cv_scores_[1] mean = np.mean(mask_scores[mask_name][category]) std = np.std(mask_scores[mask_name][category]) print(f"Scores: {mean:1.2f} +- {std:1.2f}") dummy_classifier = Decoder( estimator="dummy_classifier", cv=cv, mask=masker, scoring="roc_auc", standardize="zscore_sample", ) dummy_classifier.fit( task_data, classification_target, groups=run_labels ) mask_chance_scores[mask_name][category] = dummy_classifier.cv_scores_[ 1 ] .. rst-class:: sphx-glr-script-out .. code-block:: none Working on mask_vt Processing mask_vt scissors /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Scores: 0.92 +- 0.05 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Processing mask_vt face /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Scores: 0.98 +- 0.03 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Processing mask_vt cat /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Scores: 0.96 +- 0.04 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Processing mask_vt shoe /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Scores: 0.92 +- 0.07 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Processing mask_vt house /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Scores: 1.00 +- 0.00 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Processing mask_vt scrambledpix /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Scores: 0.99 +- 0.01 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Processing mask_vt bottle /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Scores: 0.89 +- 0.08 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Processing mask_vt chair /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Scores: 0.93 +- 0.04 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( Working on mask_face Processing mask_face scissors /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Scores: 0.70 +- 0.16 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Processing mask_face face /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Scores: 0.90 +- 0.06 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Processing mask_face cat /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Scores: 0.76 +- 0.12 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Processing mask_face shoe /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Scores: 0.73 +- 0.17 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Processing mask_face house /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Scores: 0.71 +- 0.16 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Processing mask_face scrambledpix /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Scores: 0.87 +- 0.09 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Processing mask_face bottle /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Scores: 0.68 +- 0.17 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Processing mask_face chair /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Scores: 0.63 +- 0.10 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:760: UserWarning: After clustering and screening, the decoding model will be trained only on 30 features. Consider raising clustering_percentile or screening_percentile parameters. warnings.warn( Working on mask_house Processing mask_house scissors /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Scores: 0.83 +- 0.08 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Processing mask_house face /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Scores: 0.90 +- 0.07 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Processing mask_house cat /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Scores: 0.86 +- 0.09 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Processing mask_house shoe /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Scores: 0.82 +- 0.12 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Processing mask_house house /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Scores: 1.00 +- 0.00 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Processing mask_house scrambledpix /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Scores: 0.96 +- 0.05 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Processing mask_house bottle /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Scores: 0.86 +- 0.10 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Processing mask_house chair /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( Scores: 0.90 +- 0.10 /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/image/resampling.py:492: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( /home/himanshu/Desktop/nilearn_work/nilearn/nilearn/decoding/decoder.py:742: UserWarning: Brain mask is smaller than .5% of the volume human brain. This object is probably not tuned to be used on such data. selector = check_feature_screening( .. GENERATED FROM PYTHON SOURCE LINES 128-130 We make a simple bar plot to summarize the results -------------------------------------------------- .. GENERATED FROM PYTHON SOURCE LINES 130-168 .. code-block:: Python import matplotlib.pyplot as plt plt.figure() tick_position = np.arange(len(categories)) plt.xticks(tick_position, categories, rotation=45) for color, mask_name in zip("rgb", mask_names): score_means = [ np.mean(mask_scores[mask_name][category]) for category in categories ] plt.bar( tick_position, score_means, label=mask_name, width=0.25, color=color ) score_chance = [ np.mean(mask_chance_scores[mask_name][category]) for category in categories ] plt.bar( tick_position, score_chance, width=0.25, edgecolor="k", facecolor="none", ) tick_position = tick_position + 0.2 plt.ylabel("Classification accuracy (AUC score)") plt.xlabel("Visual stimuli category") plt.ylim(0.3, 1) plt.legend(loc="lower right") plt.title("Category-specific classification accuracy for different masks") plt.tight_layout() show() .. image-sg:: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_full_analysis_001.png :alt: Category-specific classification accuracy for different masks :srcset: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_full_analysis_001.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 169-173 References ---------- .. footbibliography:: .. rst-class:: sphx-glr-timing **Total running time of the script:** (5 minutes 23.048 seconds) **Estimated memory usage:** 1368 MB .. _sphx_glr_download_auto_examples_02_decoding_plot_haxby_full_analysis.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/0.10.4?urlpath=lab/tree/notebooks/auto_examples/02_decoding/plot_haxby_full_analysis.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_haxby_full_analysis.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_haxby_full_analysis.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_