Merge remote-tracking branch 'upstream/master' into sklearn-ica

.gitattributes

@@ -0,0 +1 @@
+tedana/_version.py export-subst

.github/release-drafter.yml

@@ -0,0 +1,7 @@
+template: |
+  ## Release Notes
+
+  
+  ## Changes
+
+  $CHANGES

.pytest_cache/v/cache/lastfailed

@@ -1,3 +1,4 @@
 {
-  "tedana/tests/test_t2smap.py::test_outputs": true
+  "tedana/tests/test_t2smap.py::test_outputs": true,
+  "tedana/tests/test_tedana.py::test_outputs": true
 }

.travis.yml

@@ -3,6 +3,7 @@ sudo: false
 
 python:
     - 3.6
+    - 3.7-dev
 
 matrix:
   include:
@@ -18,9 +19,11 @@ before_install:
     - pip install --upgrade virtualenv
     - if [ "${STYLE}" == "1" ]; then
       pip install "flake8<3.0" flake8-putty;
+      else
+      pip install pytest;
       fi
     - if [ "${COVERAGE}" == "1" ]; then
-      pip install coverage coveralls codecov pytest pytest-cov;
+      pip install coverage coveralls codecov pytest-cov;
       fi
 
 script:
@@ -30,6 +33,8 @@ script:
       else
           if [ "${COVERAGE}" == "1" ]; then
               TEST_ARGS="--cov-report term-missing --cov=tedana";
+          else
+              TEST_ARGS="";
           fi
           py.test --ignore=tedana/tests/test_tedana.py ${TEST_ARGS} tedana;
       fi

.zenodo.json

@@ -0,0 +1,40 @@
+{
+  "creators": [
+    {
+      "name": "DuPre, Elizabeth",
+      "affiliation": "Montreal Neurological Institute, McGill University",
+      "orcid": "0000-0003-1358-196X"
+    },
+    {
+      "name": "Salo, Taylor",
+      "affiliation": "Florida International University",
+      "orcid": "0000-0001-9813-3167"
+    },
+    {
+      "name": "Markello, Ross",
+      "affiliation": "Montreal Neurological Institute, McGill University",
+      "orcid": "0000-0003-1057-1336"
+    },
+    {
+      "name": "Kundu, Prantik",
+      "affiliation": "Mount Sinai Hospital",
+      "orcid": "0000-0001-9367-3068"
+    },
+    {
+      "name": "Whitaker, Kirstie",
+      "affiliation": "Alan Turing Institute; Cambridge University",
+      "orcid": "0000-0001-8498-4059"
+    },
+    {
+      "name": "Handwerker, Dan",
+      "affiliation": "National Institutes of Health",
+      "orcid": "0000-0001-7261-4042"
+    }
+  ],
+  "keywords": [
+    "neuroimaging",
+    "fMRI"
+  ],
+  "license": "lgpl-2.1",
+  "upload_type": "software"
+}

MANIFEST.in

@@ -0,0 +1,2 @@
+include versioneer.py
+include tedana/_version.py

README.md

@@ -1,63 +1,76 @@
-# tedana
+# tedana: TE Dependent ANAlysis
 
-`TE`-`de`pendent `ana`lysis (_tedana_) is a Python module for denoising multi-echo functional magnetic resonance imaging (fMRI) data.
+The ``tedana`` package is part of the ME-ICA pipeline, performing TE-dependent
+analysis of multi-echo functional magnetic resonance imaging (fMRI) data.
+``TE``-``de``pendent ``ana``lysis (``tedana``) is a Python module for denoising
+multi-echo functional magnetic resonance imaging (fMRI) data.
 
+[![Latest Version](https://img.shields.io/pypi/v/tedana.svg)](https://pypi.python.org/pypi/tedana/)
+[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/tedana.svg)](https://pypi.python.org/pypi/tedana/)
+[![DOI](https://zenodo.org/badge/110845855.svg)](https://zenodo.org/badge/latestdoi/110845855)
+[![License](https://img.shields.io/badge/License-LGPL%202.0-blue.svg)](https://opensource.org/licenses/LGPL-2.1)
 [![CircleCI](https://circleci.com/gh/ME-ICA/tedana.svg?style=shield)](https://circleci.com/gh/ME-ICA/tedana)
 [![Documentation Status](https://readthedocs.org/projects/tedana/badge/?version=latest)](http://tedana.readthedocs.io/en/latest/?badge=latest)
 [![Codecov](https://codecov.io/gh/me-ica/tedana/branch/master/graph/badge.svg)](https://codecov.io/gh/me-ica/tedana)
-[![License](https://img.shields.io/badge/License-LGPL%202.0-blue.svg)](https://opensource.org/licenses/LGPL-2.1)
 [![Join the chat at https://gitter.im/ME-ICA/tedana](https://badges.gitter.im/ME-ICA/tedana.svg)](https://gitter.im/ME-ICA/tedana?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
-[![DOI](https://zenodo.org/badge/110845855.svg)](https://zenodo.org/badge/latestdoi/110845855)
-
-   ![](https://user-images.githubusercontent.com/7406227/40031156-57b7cbb8-57bc-11e8-8c51-5b29f2e86a48.png)
-
 
 ## About
 
-`tedana` originally came about as a part of the [`ME-ICA`](https://github.com/me-ica/me-ica) pipeline.
-The ME-ICA pipeline orignially performed both pre-processing and TE-dependent analysis of multi-echo fMRI data; however, `tedana` now assumes that you're working with data which has been previously preprocessed.
-If you're in need of a pre-processing pipeline, we recommend [`fmriprep`](https://github.com/poldracklab/fmriprep/) which has been tested for compatibility with multi-echo fMRI data and `tedana`.
-
-### Why Multi-Echo?
-
-Multi-echo fMRI data is obtained by acquiring multiple TEs (commonly called [echo times](http://mriquestions.com/tr-and-te.html)) for each MRI volume during data collection.
-While fMRI signal contains important neural information (termed the blood oxygen-level dependent, or [BOLD signal](http://www.fil.ion.ucl.ac.uk/spm/course/slides10-zurich/Kerstin_BOLD.pdf)), it also contains "noise" (termed non-BOLD signal) caused by things like participant motion and changes in breathing.
-Because the BOLD signal is known to decay at a set rate, collecting multiple echos allows us to assess whether components of the fMRI signal are BOLD- or non-BOLD.
-For a comprehensive review, see [Kundu et al. (2017), _NeuroImage_](https://paperpile.com/shared/eH3PPu).
-
-In `tedana`, we take the time series from all the collected TEs, combine them, and decompose the resulting data into components that can be classified as BOLD or non-BOLD. This is performed in a series of steps including:
+``tedana`` originally came about as a part of the [ME-ICA](https://github.com/me-ica/me-ica) pipeline.
+The ME-ICA pipeline originally performed both pre-processing and TE-dependent
+analysis of multi-echo fMRI data; however, ``tedana`` now assumes that you're
+working with data which has been previously preprocessed.
 
-* Principal components analysis
-* Independent components analysis
-* Component classification
+![http://tedana.readthedocs.io/](https://user-images.githubusercontent.com/7406227/40031156-57b7cbb8-57bc-11e8-8c51-5b29f2e86a48.png)
 
 More information and documentation can be found at https://tedana.readthedocs.io/.
 
 ## Installation
 
 You'll need to set up a working development environment to use `tedana`.
-To set up a local environment, the following packages will need to be installed:
+To set up a local environment, you will need Python >=3.6 and the following packages will need to be installed:
 
-mdp  
-nilearn  
-nibabel>=2.1.0  
-numpy  
-scikit-learn  
-scipy
+[mdp](https://pypi.org/project/MDP/)  
+[numpy](http://www.numpy.org/)   
+[scikit-learn](http://scikit-learn.org/stable/)   
+[scipy](https://www.scipy.org/)    
+[nilearn](https://nilearn.github.io/)     
+[nibabel>=2.1.0](http://nipy.org/nibabel/)      
 
 You can then install `tedana` with
 
+```bash
+pip install tedana
 ```
+
+### Creating a miniconda environment for use with `tedana`
+In using `tedana`, you can optionally configure [a conda environment](https://conda.io/docs/user-guide/tasks/manage-environments.html).
+
+We recommend using [miniconda3](https://conda.io/miniconda.html).
+After installation, you can use the following commands to create an environment for `tedana`:
+
+```bash
+conda create -n ENVIRONMENT_NAME python=3 pip mdp numpy scikit-learn scipy nilearn nibabel
+source activate ENVIRONMENT_NAME
 pip install tedana
 ```
 
+`tedana` will then be available in your path.
+This will also allow any previously existing tedana installations to remain untouched.
+
+To exit this conda environment, use
+
+```bash
+source deactivate
+```
+
 ## Getting involved
 
-We :yellow_heart: new contributors !
+We :yellow_heart: new contributors!
 To get started, check out [our contributing guidelines](https://github.com/ME-ICA/tedana/blob/master/CONTRIBUTING.md).
 
-Want to learn more about our plans for developing `tedana` ?
-Have a question, comment, or suggestion ?
-Open or comment on one of [our issues](https://github.com/ME-ICA/tedana/issues) !
+Want to learn more about our plans for developing ``tedana``?
+Have a question, comment, or suggestion?
+Open or comment on one of [our issues](https://github.com/ME-ICA/tedana/issues)!
 
-We ask that all contributions to `tedana` respect our [code of conduct](https://github.com/ME-ICA/tedana/blob/master/Code_of_Conduct.md).
+We ask that all contributions to ``tedana`` respect our [code of conduct](https://github.com/ME-ICA/tedana/blob/master/CODE_OF_CONDUCT.md).

docs/api.rst

@@ -1,6 +1,25 @@
 API
 ===
 
+:mod:`tedana.workflows`: Common workflows
+--------------------------------------------------
+
+.. automodule:: tedana.workflows
+   :no-members:
+   :no-inherited-members:
+
+.. autosummary:: tedana.workflows
+   :template: function.rst
+   :toctree: generated/
+
+   tedana.workflows.tedana_workflow
+   tedana.workflows.t2smap_workflow
+
+.. currentmodule:: tedana
+
+.. _calibration_ref:
+
+
 :mod:`tedana.model`: Modeling TE-dependence
 --------------------------------------------------
 
@@ -12,16 +31,11 @@ API
    :toctree: generated/
    :template: function.rst
 
-   tedana.model.fit_decay
-   tedana.model.fit_decay_ts
    tedana.model.fitmodels_direct
-   tedana.model.make_optcom
 
    :template: module.rst
 
-   tedana.model.monoexponential
    tedana.model.fit
-   tedana.model.combine
 
 .. currentmodule:: tedana
 
@@ -51,6 +65,51 @@ API
 .. _calibration_ref:
 
 
+:mod:`tedana.combine`: Combine time series
+--------------------------------------------------
+
+.. automodule:: tedana.combine
+   :no-members:
+   :no-inherited-members:
+
+.. autosummary:: tedana.combine
+   :toctree: generated/
+   :template: function.rst
+
+   tedana.combine.make_optcom
+
+   :template: module.rst
+
+   tedana.combine
+
+.. currentmodule:: tedana
+
+.. _calibration_ref:
+
+
+:mod:`tedana.decay`: Signal decay
+--------------------------------------------------
+
+.. automodule:: tedana.decay
+   :no-members:
+   :no-inherited-members:
+
+.. autosummary:: tedana.decay
+   :toctree: generated/
+   :template: function.rst
+
+   tedana.decay.fit_decay
+   tedana.decay.fit_decay_ts
+
+   :template: module.rst
+
+   tedana.decay
+
+.. currentmodule:: tedana
+
+.. _calibration_ref:
+
+
 :mod:`tedana.selection`: Component selection
 --------------------------------------------------
 
@@ -73,24 +132,40 @@ API
 .. _calibration_ref:
 
 
-:mod:`tedana.workflows`: Common workflows
+:mod:`tedana.io`: Reading and writing data
 --------------------------------------------------
 
-.. automodule:: tedana.workflows
+.. automodule:: tedana.io
    :no-members:
    :no-inherited-members:
 
-.. autosummary:: tedana.workflows
-   :template: function.rst
+.. autosummary:: tedana.io
    :toctree: generated/
 
-   tedana.workflows.tedana
-   tedana.workflows.t2smap
+   :template: function.rst
+
+   tedana.io.split_ts
+
+   tedana.io.ctabsel
+   tedana.io.filewrite
+   tedana.io.gscontrol_mmix
+   tedana.io.load_data
+   tedana.io.new_nii_like
+   tedana.io.write_split_ts
+   tedana.io.writect
+   tedana.io.writefeats
+   tedana.io.writeresults
+   tedana.io.writeresults_echoes
+
+   :template: module.rst
+
+   tedana.io
 
 .. currentmodule:: tedana
 
 .. _calibration_ref:
 
+
 :mod:`tedana.utils`: Utility functions
 --------------------------------------------------
 
@@ -100,10 +175,24 @@ API
 
 .. autosummary:: tedana.utils
    :toctree: generated/
+
+   :template: function.rst
+
+   tedana.utils.andb
+   tedana.utils.dice
+   tedana.utils.fitgaussian
+   tedana.utils.gaussian
+   tedana.utils.get_dtype
+   tedana.utils.getfbounds
+   tedana.utils.load_image
+   tedana.utils.make_adaptive_mask
+   tedana.utils.make_min_mask
+   tedana.utils.moments
+   tedana.utils.unmask
+
    :template: module.rst
 
-   tedana.utils.io
-   tedana.utils.utils
+   tedana.utils
 
 .. currentmodule:: tedana