8000 nproc=1 · nipype/pydra-tutorial@e4a9a54 · GitHub
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nproc=1
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‎notebooks/7_twolevel_glm_nilearn.md

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@@ -5,7 +5,7 @@ jupytext:
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extension: .md
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format_name: myst
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format_version: 0.13
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jupytext_version: 1.14.1
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jupytext_version: 1.13.8
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kernelspec:
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display_name: Python 3 (ipykernel)
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language: python
@@ -240,7 +240,7 @@ def firstlevel_estimation(subj_id, run_id, subj_imgs, subj_masks, smoothing_fwhm
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# fit the (fixed-effects) firstlevel model with three runs simultaneously
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run_img = subj_imgs[run_id-1]
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img = load_img(run_img)
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img_data = get_data(run_img)[::2,::2,::2]
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img_data = get_data(run_img)[::3,::3,::3]
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new_img = nib.Nifti1Image(img_data, img.affine)
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run_mask = subj_masks[run_id-1]
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first_level_model = FirstLevelModel(mask_img=run_mask, smoothing_fwhm=smoothing_fwhm)
@@ -800,7 +800,7 @@ wf.set_output(
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from pydra import Submitter
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with Submitter(plugin='cf', n_procs=2) as submitter:
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with Submitter(plugin='cf', n_procs=1) as submitter:
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submitter(wf)
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results = wf.result()

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