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mvdoc committed Apr 13, 2022
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2 changes: 1 addition & 1 deletion .buildinfo
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 9cad32f555da1c40107965e6987fd25e
config: 13b17c5c373045c1725623acad9b96b1
tags: 645f666f9bcd5a90fca523b33c5a78b7
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"name": "python",
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"name": "python",
"nbconvert_exporter": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"pygments_lexer": "ipython3",
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"name": "python",
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"name": "python",
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"name": "python",
"nbconvert_exporter": "python",
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"name": "python",
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"name": "python",
"nbconvert_exporter": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
"nbconvert_exporter": "python",
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"version": "3.9.12"
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# import subject into pycortex database
fmriprep.import_subj(subject_id, source_directory)

# We can use visualize the imported subject's T1-weighted image
# We can visualize the imported subject's T1-weighted image
anat_nifti = 'fmriprep/sub-001/anat/sub-001_T1w_preproc.nii.gz'
t1_image_path = op.join(source_directory, anat_nifti)

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"name": "python",
"nbconvert_exporter": "python",
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"version": "3.9.10"
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"name": "python",
"nbconvert_exporter": "python",
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"version": "3.9.10"
"version": "3.9.12"
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"name": "python",
"nbconvert_exporter": "python",
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"name": "python",
"nbconvert_exporter": "python",
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"version": "3.9.10"
"version": "3.9.12"
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"name": "python",
"nbconvert_exporter": "python",
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"version": "3.9.10"
"version": "3.9.12"
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"name": "python",
"nbconvert_exporter": "python",
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"version": "3.9.10"
"version": "3.9.12"
}
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.10"
"version": "3.9.12"
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"name": "python",
"nbconvert_exporter": "python",
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"version": "3.9.10"
"version": "3.9.12"
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.10"
"version": "3.9.12"
}
},
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.10"
"version": "3.9.12"
}
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},
"outputs": [],
"source": [
"import cortex\nfrom cortex import fmriprep\nfrom os import path as op\n\n# Location of the downloaded openfmri dataset\nsource_directory = '/derivatives/ds000164'\n# fmriprep subject name (without \"sub-\")\nsubject_id = '001' \n\n# import subject into pycortex database\nfmriprep.import_subj(subject_id, source_directory)\n\n# We can use visualize the imported subject's T1-weighted image\nanat_nifti = 'fmriprep/sub-001/anat/sub-001_T1w_preproc.nii.gz'\nt1_image_path = op.join(source_directory, anat_nifti)\n\n# Now we can make a volume using the built-in identity transform\nt1w_volume = cortex.Volume(t1_image_path, subject_id, 'identity')\n\n# And show the result.\nds = cortex.Dataset(t1w=t1w_volume)\ncortex.webgl.show(ds)"
"import cortex\nfrom cortex import fmriprep\nfrom os import path as op\n\n# Location of the downloaded openfmri dataset\nsource_directory = '/derivatives/ds000164'\n# fmriprep subject name (without \"sub-\")\nsubject_id = '001' \n\n# import subject into pycortex database\nfmriprep.import_subj(subject_id, source_directory)\n\n# We can visualize the imported subject's T1-weighted image\nanat_nifti = 'fmriprep/sub-001/anat/sub-001_T1w_preproc.nii.gz'\nt1_image_path = op.join(source_directory, anat_nifti)\n\n# Now we can make a volume using the built-in identity transform\nt1w_volume = cortex.Volume(t1_image_path, subject_id, 'identity')\n\n# And show the result.\nds = cortex.Dataset(t1w=t1w_volume)\ncortex.webgl.show(ds)"
]
}
],
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.10"
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"name": "python",
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"version": "3.9.12"
}
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"name": "python",
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"version": "3.9.12"
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"name": "python",
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"version": "3.9.12"
}
},
"nbformat": 4,
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