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Scitran Data travis_badge

TODO put some sort of warning that upgrading from this package BREAKS WORLDS, and does not replace nimsdata, rather scitran.data will install along side.

Data handling utilities.

Provides class and functions for parsing, identifying and writing scientific datasets. Currently, medical images (such as various flavors of MRI, dicoms, niftis, and some raw-files) are supported.

Also provides base classes that can be used to extend this package to cover additional data-domains.

Note that these utilites also have command-line interfaces, so you don't need a full NIMS instance to use them. E.g., you can run our image reconstruction pipeline.

How to use the documentation

Documentation is available as docstrings provided within the code, and additional narrative documentation.

Dependencies

development version is currently using the following:

package version
Pillow 2.6.1
numpy 1.9.2
nibabel 1.4.0dev
pydicom 0.9.9
dcmstack 0.7.0dev
pytz 2014.10
scipy 0.14.0
mne 0.9

installation on fresh ubuntu 14.04

  • install dependencies, had to chmod o+w /var/local to allow regular user to write; not ideal
    • python-dev is required to build numpy, and pillow.
    • python-virtualenv is required to make use of python virtual environment.
    • libjeg-dev is required for pillow JPEG support. Pillow must be compiled with JPEG support. See this stack overflow question for more information.
    • git is required to pip install from git repositories.
sudo apt-get update && sudo apt-get upgrade
sudo apt-get install python-dev python-virtualenv libjpeg-dev git
sudo ln -s /usr/lib/x86_64-linux-gnu/libjpeg.so /usr/lib
  • create and activate virtualenv
virtualenv data_env
source data_env/bin/bin/activate
  • install dependencies, these are VERY specific version. once these versions are available through pypi, these installation commands will change. (subject to change)
pip install numpy==1.9.0
pip install scipy==0.14
pip install git+https://github.com/scitran/[email protected]_value_vr_mismatch
pip install git+https://github.com/nipy/nibabel.git
pip install git+https://github.com/moloney/dcmstack.git@6d49fe01235c08ae63c76fa2f3943b49c9b9832d
pip install pillow
pip install pytz
pip install mne
  • install scitran data from github
pip install git+https://github.com/scitran/data.git

Basic Conversion

The software consists of the python package, scitran.data, with a single command line interface data.py.

NIMSData has a semi-standard input filetype, a tgz, that contains raw data and a json that indicates the raw data filetype, header data, and metadata corrections.

data.py expects at least 3 options, <input.tgz>, --parser <filetype>, --writer <filetype>.

The following shell command will take the dicom input input.tgz and convert it to nifti, outprefix.nii.gz.

data.py -p dicom input.tgz -w nifti outprefix.nii.gz

And the equivelant command in python.

import scitran.data as scidata
ds = scidata.parse('/path/to/input.gz', filetype='dicom')
ds.load_data()
scidata.write(ds, ds.data, 'outprefix', filetype='nifti')

For more information on using Scitran Data in bash, see CLI tutorial.

For more information on using Scitran Data in python see Python tutorial.

Developer Notes

To install scitran data from github in 'editable mode', in a directory of your choosing, provide the -e and --src <destination> arguments.

pip install -e git+https://github.com/scitran/data.git#egg=scitran.data --src ./

to run tests locally, you will need coverage and nose

pip install coverage nose

To generate the docs locally, you will need sphinx, and numpydoc.

pip install sphinx numpydoc

numpy 1.9 changes how numpy.unique() behaves when given an array of arrays. Pre 1.9, np.unique would return each unique array. Post 1.9, np.unique returns unique items from the arrays. dcmstack is compatible with numpy 1.9, but numpy throws some FutureWarnings. The current version of dcmstack (0.7.0dev) may not be compatible with future version of numpy.

run the following git config commands to enable a git filter for the branch name.

git config filter.brancher.smudge "./git_branch_filter.py smudge"
git config filter.brancher.clean "./git_branch_filter.py clean"

Combined with .gitattributes, the smudge and clean filters will replace 'branch=__BRANCH__' to indicate the current branch.

Testdata is not distributed with this package. Downloading/cloning the testdata is necessary to run tests locally. clone the testdata repository into scitran/data/test/testdata.

git clone https://github/com/scitran/testdata.git <path to clone of scitran-data>/scitran/data/test/testdata

Probing site data

To probe functionality, you can set the API to insecure mode in config.toml. The API can the directly be browsed at e.g. https://localhost:8443/api. Type in your email address, click Generate Custom Links, and then browse different tabs like /projects link. JSONView is a helpful Chrome plugin for this process.