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NIPY
NIPY is not only the name of the Neuroimaging in Python community, but also a python project for analysis of structural and functionalneuroimaging data.
NIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered at NEUROIMAGING IN PYTHON NiBabel ¶. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, CIFTI-2, MINC1, MINC2, AFNI BRIK/HEAD, MGH and ECAT as well as Philips PAR/REC. We can read and write FreeSurfer geometry, annotation and morphometry files.DIPY
Dipy is a free and open source software project focusing on diffusion magnetic resonance imaging (dMRI) analysis.NIPYPE
Nipype provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a singleworkflow.
NIPY.ORG
Getting Help. One of the main tenets of our community is that we encourage inquisitiveness. Ask questions and share your experiences! Asking people for help and asking questions about technical matters can be intimidating, especially if you haven’t done that before.NIBABEL - NIPY.ORG
nibabel Doc Github Nibabel aims to provide read/write access to some common neuroimaging file formats. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, MINC1, MINC2, MGH and ECAT as well as Philips PAR/REC. NEUROIMAGING IN PYTHON nibabel.processing.adapt_affine(affine, n_dim) ¶. Adapt input / output dimensions of spatial affine for n_dims. Adapts a spatial (4, 4) affine that is being applied to an image with fewer than 3 spatial dimensions, or more than 3 dimensions. If there are more than three dimensions, assume an identity transformation for these dimensions. NIWIDGETS - NIPY.ORG niwidgets Doc Github niwidgets provides you with interactive widgets for jupyter notebooks to plot neuroimaging data. Niwidgets allows you to: Interactively slice NIPY.ORGPROJECTSHELPCONDUCTCONTRIBUTENIPYPOPEYE nipy.org. Welcome to NIPY. We are a community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data. You can find us on github, as well as social media . We welcome contributions and ask that you read about our standards of conduct.NIPY
NIPY is not only the name of the Neuroimaging in Python community, but also a python project for analysis of structural and functionalneuroimaging data.
NIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered at NEUROIMAGING IN PYTHON NiBabel ¶. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, CIFTI-2, MINC1, MINC2, AFNI BRIK/HEAD, MGH and ECAT as well as Philips PAR/REC. We can read and write FreeSurfer geometry, annotation and morphometry files.DIPY
Dipy is a free and open source software project focusing on diffusion magnetic resonance imaging (dMRI) analysis.NIPYPE
Nipype provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a singleworkflow.
NIPY.ORG
Getting Help. One of the main tenets of our community is that we encourage inquisitiveness. Ask questions and share your experiences! Asking people for help and asking questions about technical matters can be intimidating, especially if you haven’t done that before.NIBABEL - NIPY.ORG
nibabel Doc Github Nibabel aims to provide read/write access to some common neuroimaging file formats. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, MINC1, MINC2, MGH and ECAT as well as Philips PAR/REC. NEUROIMAGING IN PYTHON nibabel.processing.adapt_affine(affine, n_dim) ¶. Adapt input / output dimensions of spatial affine for n_dims. Adapts a spatial (4, 4) affine that is being applied to an image with fewer than 3 spatial dimensions, or more than 3 dimensions. If there are more than three dimensions, assume an identity transformation for these dimensions. NIWIDGETS - NIPY.ORG niwidgets Doc Github niwidgets provides you with interactive widgets for jupyter notebooks to plot neuroimaging data. Niwidgets allows you to: Interactively sliceNIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered atNIPY.ORG
Code of Conduct. The NIPY community is a community of practice devoted to the use of the Python programming language in the analysis ofneuroimaging data.
NITIME - NIPY.ORG
Nitime Doc Github Nitime is a library for time-series analysis of neuroscience data. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact andNILEARN - NIPY.ORG
Nilearn is a Python module for fast and easy statistical learning onneuroimaging data.
SDM - NIPY.ORG
Scitran SDM Doc Github SciTran SDM delivers efficient and robust archiving, organization, and sharing of scientific data We have developed the system around neuroimaging data, but our goal is to build a system that is flexible enough to accommodate all types of scientific data – from paper-and-pencil tests to genomics data.MNE - NIPY.ORG
MNE Doc Github MNE is a software package for processing magnetoencephalography (MEG) and electroencephalography (EEG) data. The MNE software computes cortically-constrained L2 minimum-norm current estimates and associated dynamic statistical parametric maps from MEG and EEG data, optionally constrained by fMRI. NEUROIMAGING IN PYTHON The anatomical image to be used as a background. If None is given, nipy tries to find a T1 template.PYMVPA - NIPY.ORG
PyMVPA Doc Github PyMVPA is a Python package intended to ease statistical learning analyses of large datasets. PyMVPA is a Python package intended to ease statistical learning analyses of largedatasets.
NEUROIMAGING IN PYTHON If str, one of {‘ascending’, ‘descending’}. If array-like, then the order in which the slices were collected in time. For instance, the following represents an ascending contiguous sequence:NAPARI NIBABEL
napari-nibabel Doc Github A plugin for the napari image viewer to view and annotate neuroimaging data. napari is a fast, interactive, multi-dimensional image viewer for Python. It's designed for browsing, annotating, and analyzing large multi-dimensional images. NIPY.ORGPROJECTSHELPCONDUCTCONTRIBUTENIPYPOPEYE nipy.org. Welcome to NIPY. We are a community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data. You can find us on github, as well as social media . We welcome contributions and ask that you read about our standards of conduct.NIPY
NIPY is not only the name of the Neuroimaging in Python community, but also a python project for analysis of structural and functionalneuroimaging data.
NIPY.ORG
Code of Conduct. The NIPY community is a community of practice devoted to the use of the Python programming language in the analysis ofneuroimaging data.
DIPY
Dipy is a free and open source software project focusing on diffusion magnetic resonance imaging (dMRI) analysis. NEUROIMAGING IN PYTHON NiBabel ¶. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, CIFTI-2, MINC1, MINC2, AFNI BRIK/HEAD, MGH and ECAT as well as Philips PAR/REC. We can read and write FreeSurfer geometry, annotation and morphometry files.NIPY.ORG
Getting Help. One of the main tenets of our community is that we encourage inquisitiveness. Ask questions and share your experiences! Asking people for help and asking questions about technical matters can be intimidating, especially if you haven’t done that before.NIBABEL - NIPY.ORG
nibabel Doc Github Nibabel aims to provide read/write access to some common neuroimaging file formats. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, MINC1, MINC2, MGH and ECAT as well as Philips PAR/REC. NIWIDGETS - NIPY.ORG niwidgets Doc Github niwidgets provides you with interactive widgets for jupyter notebooks to plot neuroimaging data. Niwidgets allows you to: Interactively slice NEUROIMAGING IN PYTHON Affine of the new voxel grid or transform object pointing to the new voxel coordinate grid. If a 3x3 ndarray is given, it is considered to be the rotation part of the affine, and the best possible bounding box is calculated, in this case, the shape argument is not used. NEUROIMAGING IN PYTHON Module: algorithms.utils.pca ¶ This module provides a class for principal components analysis (PCA). PCA is an orthonormal, linear transform (i.e., a rotation) that maps the data to a new coordinate system such that the maximal variability of the data lies on the first coordinate (or the first principal component), the second greatest variability is projected onto the second coordinate, and NIPY.ORGPROJECTSHELPCONDUCTCONTRIBUTENIPYPOPEYE nipy.org. Welcome to NIPY. We are a community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data. You can find us on github, as well as social media . We welcome contributions and ask that you read about our standards of conduct.NIPY
NIPY is not only the name of the Neuroimaging in Python community, but also a python project for analysis of structural and functionalneuroimaging data.
NIPY.ORG
Code of Conduct. The NIPY community is a community of practice devoted to the use of the Python programming language in the analysis ofneuroimaging data.
DIPY
Dipy is a free and open source software project focusing on diffusion magnetic resonance imaging (dMRI) analysis. NEUROIMAGING IN PYTHON NiBabel ¶. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, CIFTI-2, MINC1, MINC2, AFNI BRIK/HEAD, MGH and ECAT as well as Philips PAR/REC. We can read and write FreeSurfer geometry, annotation and morphometry files.NIPY.ORG
Getting Help. One of the main tenets of our community is that we encourage inquisitiveness. Ask questions and share your experiences! Asking people for help and asking questions about technical matters can be intimidating, especially if you haven’t done that before.NIBABEL - NIPY.ORG
nibabel Doc Github Nibabel aims to provide read/write access to some common neuroimaging file formats. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, MINC1, MINC2, MGH and ECAT as well as Philips PAR/REC. NIWIDGETS - NIPY.ORG niwidgets Doc Github niwidgets provides you with interactive widgets for jupyter notebooks to plot neuroimaging data. Niwidgets allows you to: Interactively slice NEUROIMAGING IN PYTHON Affine of the new voxel grid or transform object pointing to the new voxel coordinate grid. If a 3x3 ndarray is given, it is considered to be the rotation part of the affine, and the best possible bounding box is calculated, in this case, the shape argument is not used. NEUROIMAGING IN PYTHON Module: algorithms.utils.pca ¶ This module provides a class for principal components analysis (PCA). PCA is an orthonormal, linear transform (i.e., a rotation) that maps the data to a new coordinate system such that the maximal variability of the data lies on the first coordinate (or the first principal component), the second greatest variability is projected onto the second coordinate, andNIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered atNIPY.ORG
Getting Help. One of the main tenets of our community is that we encourage inquisitiveness. Ask questions and share your experiences! Asking people for help and asking questions about technical matters can be intimidating, especially if you haven’t done that before.MNE - NIPY.ORG
MNE Doc Github MNE is a software package for processing magnetoencephalography (MEG) and electroencephalography (EEG) data. The MNE software computes cortically-constrained L2 minimum-norm current estimates and associated dynamic statistical parametric maps from MEG and EEG data, optionally constrained by fMRI. NEUROIMAGING IN PYTHON to_img : nipy-like image. To image. from_bins : integer. Number of histogram bins to represent the from image. to_bins : integer. Number of histogram bins to represent the to image. from_mask : array-like. Mask to apply to the from image. to_mask : array-like. Mask to apply to the to image. similarity : str or callable. Cost-function for assessing image similarity. NEUROIMAGING IN PYTHON The anatomical image to be used as a background. If None is given, nipy tries to find a T1 template. NEUROIMAGING IN PYTHON Affine of the new voxel grid or transform object pointing to the new voxel coordinate grid. If a 3x3 ndarray is given, it is considered to be the rotation part of the affine, and the best possible bounding box is calculated, in this case, the shape argument is not used. NEUROIMAGING IN PYTHON If str, one of {‘ascending’, ‘descending’}. If array-like, then the order in which the slices were collected in time. For instance, the following represents an ascending contiguous sequence: NEUROIMAGING IN PYTHON threshold=0., float, threshold value above which peaks are considered. nn=18, int, number of neighbours of the topological spatial model. order_th=0, int, threshold on topological order to validate the peaks NEUROIMAGING IN PYTHON Module: algorithms.utils.pca ¶ This module provides a class for principal components analysis (PCA). PCA is an orthonormal, linear transform (i.e., a rotation) that maps the data to a new coordinate system such that the maximal variability of the data lies on the first coordinate (or the first principal component), the second greatest variability is projected onto the second coordinate, and NEUROIMAGING IN PYTHON the map between the (linear parameters (in the design matrix) and the nonlinear parameters (theta)) and the predicted data. f accepts the design matrix and the parameters (theta) as input, and returns the predicted data at that design. NIPY.ORGPROJECTSHELPCONDUCTCONTRIBUTENIPYPOPEYE nipy.org. Welcome to NIPY. We are a community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data. You can find us on github, as well as social media .We welcome contributions and ask that you read about our standards of conduct.You are also invited to ask for help.. Our community includes the following projects:NIPY
NIPY is not only the name of the Neuroimaging in Python community, but also a python project for analysis of structural and functionalneuroimaging data.
NEUROIMAGING IN PYTHON NiBabel¶. Read / write access to some common neuroimaging file formats. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, CIFTI-2, MINC1, MINC2, AFNI BRIK/HEAD, MGH and ECAT as well as Philips PAR/REC. We can read and write FreeSurfer geometry, annotation and morphometryNIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered at NEUROIMAGING IN PYTHON Unlike mri_convert--conform, this command does not:. Transform data to range Cast to unsigned eight-bit integer. Parameters from_img object. Object having attributes dataobj, affine, header and shape.If out_class is not None, img.__class__ should be able to construct an image from data, affine and header.. out_shape sequence, optional. The shape of the output volume.DIPY
Dipy is a free and open source software project focusing on diffusion magnetic resonance imaging (dMRI) analysis.NIPY.ORG
Getting Help. One of the main tenets of our community is that we encourage inquisitiveness. Ask questions and share your experiences! Asking people for help and asking questions about technical matters can be intimidating, especially if you haven’t done that before.NILEARN - NIPY.ORG
Nilearn is a Python module for fast and easy statistical learning onneuroimaging data.
SDM - NIPY.ORG
Scitran SDM Doc Github SciTran SDM delivers efficient and robust archiving, organization, and sharing of scientific data We have developed the system around neuroimaging data, but our goal is to build a system that is flexible enough to accommodate all types of scientific data – from paper-and-pencil tests to genomics data. NEUROIMAGING IN PYTHON If str, one of {‘ascending’, ‘descending’}. If array-like, then the order in which the slices were collected in time. For instance, the following represents an ascending contiguous sequence: NIPY.ORGPROJECTSHELPCONDUCTCONTRIBUTENIPYPOPEYE nipy.org. Welcome to NIPY. We are a community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data. You can find us on github, as well as social media .We welcome contributions and ask that you read about our standards of conduct.You are also invited to ask for help.. Our community includes the following projects:NIPY
NIPY is not only the name of the Neuroimaging in Python community, but also a python project for analysis of structural and functionalneuroimaging data.
NEUROIMAGING IN PYTHON NiBabel¶. Read / write access to some common neuroimaging file formats. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, CIFTI-2, MINC1, MINC2, AFNI BRIK/HEAD, MGH and ECAT as well as Philips PAR/REC. We can read and write FreeSurfer geometry, annotation and morphometryNIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered at NEUROIMAGING IN PYTHON Unlike mri_convert--conform, this command does not:. Transform data to range Cast to unsigned eight-bit integer. Parameters from_img object. Object having attributes dataobj, affine, header and shape.If out_class is not None, img.__class__ should be able to construct an image from data, affine and header.. out_shape sequence, optional. The shape of the output volume.DIPY
Dipy is a free and open source software project focusing on diffusion magnetic resonance imaging (dMRI) analysis.NIPY.ORG
Getting Help. One of the main tenets of our community is that we encourage inquisitiveness. Ask questions and share your experiences! Asking people for help and asking questions about technical matters can be intimidating, especially if you haven’t done that before.NILEARN - NIPY.ORG
Nilearn is a Python module for fast and easy statistical learning onneuroimaging data.
SDM - NIPY.ORG
Scitran SDM Doc Github SciTran SDM delivers efficient and robust archiving, organization, and sharing of scientific data We have developed the system around neuroimaging data, but our goal is to build a system that is flexible enough to accommodate all types of scientific data – from paper-and-pencil tests to genomics data. NEUROIMAGING IN PYTHON If str, one of {‘ascending’, ‘descending’}. If array-like, then the order in which the slices were collected in time. For instance, the following represents an ascending contiguous sequence:SDM - NIPY.ORG
Scitran SDM Doc Github SciTran SDM delivers efficient and robust archiving, organization, and sharing of scientific data We have developed the system around neuroimaging data, but our goal is to build a system that is flexible enough to accommodate all types of scientific data – from paper-and-pencil tests to genomics data.NILEARN - NIPY.ORG
Nilearn is a Python module for fast and easy statistical learning onneuroimaging data.
NEUROIMAGING IN PYTHON Test files¶. We like test modules to import their testing functions and classes from the module in which they are defined. For example, we might want to use the assert_true, assert_equal functions defined by nose, the assert_array_equal, assert_almost_equal functions defined by numpy, and the funcfile, anatfile variables from nipy: NEUROIMAGING IN PYTHON The anatomical image to be used as a background. If None is given, nipy tries to find a T1 template. NEUROIMAGING IN PYTHON If str, one of {‘ascending’, ‘descending’}. If array-like, then the order in which the slices were collected in time. For instance, the following represents an ascending contiguous sequence: NEUROIMAGING IN PYTHON ECcone ¶ class nipy.algorithms.statistics.rft.ECcone (mu=, dfd=inf, search=, product=) ¶. Bases: nipy.algorithms.statistics.rft.IntrinsicVolumes EC approximation to supremum distribution of var==1 Gaussian process. A class that takes the intrinsic volumes of a set and gives the EC approximation to the supremum distribution of a unit variance Gaussian process with theseintrinsic
NEUROIMAGING IN PYTHON nipy.labs.datasets.volumes.volume_field.VolumeField.values_in_world¶ VolumeField.values_in_world (x, y, z, interpolation=None) ¶ Return the values of the data at the world-space positions given by x, y, zNAPARI NIBABEL
napari-nibabel Doc Github A plugin for the napari image viewer to view and annotate neuroimaging data. napari is a fast, interactive, multi-dimensional image viewer for Python. It's designed for browsing, annotating, and analyzing large multi-dimensional images. NEUROIMAGING IN PYTHON IMM ¶ class nipy.algorithms.clustering.imm.IMM (alpha=0.5, dim=1) ¶. Bases: nipy.algorithms.clustering.bgmm.BGMM The class implements Infinite Gaussian Mixture model or Dirichlet Proces Mixture Model. This simply a generalization of Bayesian Gaussian Mixture Models with an unknown number of classes. NEUROIMAGING IN PYTHON nipy.labs.datasets.transforms.affine_utils.get_bounds (shape, affine) Return the world-space bounds occupied by an array given an affine. nipy.labs.datasets.transforms.affine_utils.to_matrix_vector (transform) ¶ Split a transform into it’s matrix and vectorcomponents.
NIPY.ORGPROJECTSHELPCONDUCTCONTRIBUTENIPYPOPEYE nipy.org. Welcome to NIPY. We are a community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data. You can find us on github, as well as social media . We welcome contributions and ask that you read about our standards of conduct.NIPY
NIPY is not only the name of the Neuroimaging in Python community, but also a python project for analysis of structural and functionalneuroimaging data.
NIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered atNIPYPE
Nipype provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a singleworkflow.
DIPY
Dipy is a free and open source software project focusing on diffusion magnetic resonance imaging (dMRI) analysis. NEUROIMAGING IN PYTHON nibabel.processing.adapt_affine(affine, n_dim) ¶. Adapt input / output dimensions of spatial affine for n_dims. Adapts a spatial (4, 4) affine that is being applied to an image with fewer than 3 spatial dimensions, or more than 3 dimensions. If there are more than three dimensions, assume an identity transformation for these dimensions.NILEARN - NIPY.ORG
Nilearn is a Python module for fast and easy statistical learning onneuroimaging data.
NIWIDGETS - NIPY.ORG niwidgets Doc Github niwidgets provides you with interactive widgets for jupyter notebooks to plot neuroimaging data. Niwidgets allows you to: Interactively slicePOPEYE - NIPY.ORG
popeye Doc Github Popeye is a library for estimation of population receptive fields (pRF), accelerated with Cython and multiprocessing. A population receptive field (pRF) is a quantitative model of the cumulative response of the population of cells contained within asingle fMRI voxel.
NEUROIMAGING IN PYTHON If str, one of {‘ascending’, ‘descending’}. If array-like, then the order in which the slices were collected in time. For instance, the following represents an ascending contiguous sequence: NIPY.ORGPROJECTSHELPCONDUCTCONTRIBUTENIPYPOPEYE nipy.org. Welcome to NIPY. We are a community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data. You can find us on github, as well as social media . We welcome contributions and ask that you read about our standards of conduct.NIPY
NIPY is not only the name of the Neuroimaging in Python community, but also a python project for analysis of structural and functionalneuroimaging data.
NIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered atNIPYPE
Nipype provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a singleworkflow.
DIPY
Dipy is a free and open source software project focusing on diffusion magnetic resonance imaging (dMRI) analysis. NEUROIMAGING IN PYTHON nibabel.processing.adapt_affine(affine, n_dim) ¶. Adapt input / output dimensions of spatial affine for n_dims. Adapts a spatial (4, 4) affine that is being applied to an image with fewer than 3 spatial dimensions, or more than 3 dimensions. If there are more than three dimensions, assume an identity transformation for these dimensions.NILEARN - NIPY.ORG
Nilearn is a Python module for fast and easy statistical learning onneuroimaging data.
NIWIDGETS - NIPY.ORG niwidgets Doc Github niwidgets provides you with interactive widgets for jupyter notebooks to plot neuroimaging data. Niwidgets allows you to: Interactively slicePOPEYE - NIPY.ORG
popeye Doc Github Popeye is a library for estimation of population receptive fields (pRF), accelerated with Cython and multiprocessing. A population receptive field (pRF) is a quantitative model of the cumulative response of the population of cells contained within asingle fMRI voxel.
NEUROIMAGING IN PYTHON If str, one of {‘ascending’, ‘descending’}. If array-like, then the order in which the slices were collected in time. For instance, the following represents an ascending contiguous sequence:NIPY.ORG
Infrastructure and workflow. Let's first look at the infrastructure and workflow of the site. Github:The site is a repo under the nipy organization on github.This means that contribution to it goes by way of forking the repo and doing a pull request (PR).; Github pages: We also use hosting on github pages, which only means that the site lives on a branch called gh-pages that gets rendered at NEUROIMAGING IN PYTHON NiBabel ¶. This package provides read +/- write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, CIFTI-2, MINC1, MINC2, AFNI BRIK/HEAD, MGH and ECAT as well as Philips PAR/REC. We can read and write FreeSurfer geometry, annotation and morphometry files. NEUROIMAGING IN PYTHON Background¶. DICOM files in particular have a lot of information in them that we might want to carry with the image. There are other image file types like Minc or Nrrd that have information we’d like to support but can’t with standard nifti.. One obvious place toNILEARN - NIPY.ORG
Nilearn is a Python module for fast and easy statistical learning onneuroimaging data.
SDM - NIPY.ORG
Scitran SDM Doc Github SciTran SDM delivers efficient and robust archiving, organization, and sharing of scientific data We have developed the system around neuroimaging data, but our goal is to build a system that is flexible enough to accommodate all types of scientific data – from paper-and-pencil tests to genomics data. NEUROIMAGING IN PYTHON Roadmap¶. The roadmap is intended for larger, fundamental changes to the project that are likely to take months or years of developer time. Smaller-scoped items will continue to be tracked on our issue tracker. NEUROIMAGING IN PYTHON BIAP1 - Towards immutable images¶ Author. Matthew Brett. Status. Rejected. Type. Standards. Created. 2011-03-23 NEUROIMAGING IN PYTHON If str, one of {‘ascending’, ‘descending’}. If array-like, then the order in which the slices were collected in time. For instance, the following represents an ascending contiguous sequence: NEUROIMAGING IN PYTHON T is the number of time points (arr.shape). S is the number of slices (arr.shape). v is the shape of a volume (rollimg(arr, time_axis).shape). d2 is the volume of squared differences between voxels at time point t and time point t+1 results has keys: ‘volume_mean_diff2’ : (T-1,) array array containing the mean (over voxels in volume) of the squared difference NEUROIMAGING IN PYTHON Module: algorithms.utils.pca ¶ This module provides a class for principal components analysis (PCA). PCA is an orthonormal, linear transform (i.e., a rotation) that maps the data to a new coordinate system such that the maximal variability of the data lies on the first coordinate (or the first principal component), the second greatest variability is projected onto the second coordinate, andHome Projects __
Analysis Pipeline Management nipype Computational Anatomydipy mindboggle
File I/O and Data Management nibabel Scitran SDMFunctional MRI
Nipy Nitime
popeye Machine LearningNilearn PyMVPA
Human Electrophysiology MNE Data Visualisation napari-nibabel niwidgetsBlog
Help Conduct Workshops Contribute version 1.1.0NIPY.ORG
Welcome to NIPY. We are a community of practicedevoted to the
use of the Python programming language in the analysis of neuroimaging data. You can find us on github , as well associal media
. We welcome contributions and ask that you read about our standards of conduct . You are also invited to ask for help. Our community includes the following projects: ANALYSIS PIPELINE MANAGEMENT* _ _ __
nipype
- Provides a uniform interface to existing neuroimaging software. COMPUTATIONAL ANATOMY* _ _ __ dipy
- Focuses on diffusion magnetic resonance imaging (dMRI) analysis.* _ _ __
mindboggle
- Improves the accuracy, precision, and consistency of labeling & morphometry of brain imaging data. FILE I/O AND DATA MANAGEMENT* _ _ __
nibabel -
Read / write common neuroimaging file formats.* _ _ __
Scitran SDM -
Delivers efficient and robust archiving, organization, and sharing ofscientific data.
FUNCTIONAL MRI
* _ _ __ Nipy
- Analysis of structural and functionalneuroimaging data.
* _ _ __
Nitime - Time-series analysis ofneuroscience data.
* _ _ __
popeye
- Population receptive field estimationMACHINE LEARNING
* _ _ __
Nilearn -
Fast and easy statistical learning on neuroimaging data.* _ _ __
PyMVPA - Eases statistical learning analyses of large neuroimaging datasets. HUMAN ELECTROPHYSIOLOGY* _ _ __
MNE
- Processes magnetoencephalography (MEG) and electroencephalography (EEG) data.DATA VISUALISATION
* _ _ __
napari-nibabel - A plugin for the napari image viewer to view and annotate neuroimaging data* _ _ __
niwidgets
- Provides interactive plots forvolumetric images.
2015-2021 nipy
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