daducci · ErickHernandezGutierrez · Mar 14, 2020 · Mar 14, 2020 · Mar 14, 2020 · Mar 24, 2020
diff --git a/.gitattributes b/.gitattributes
@@ -1 +1,4 @@
 extras/* linguist-vendored
+
+# Never modify line endings of our bash scripts
+*.sh -lf
diff --git a/.gitignore b/.gitignore
@@ -15,4 +15,7 @@ __pycache__/
 *.cpp
 dist/
 
-trk2dictionary.c
+trk2dictionary.c
+
+# Never modify line endings of our bash scripts
+*.sh -lf
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,7 +1,14 @@
-
 # Change Log
 All notable changes to COMMIT will be documented in this file.
 
+## [1.5.0] - 2021-01-04
+
+### Changed
+- setup.py: Add compilation for .cu files
+
+### Added
+- GPU acceleration with CUDA for faster model fitting
+
 ## [1.4.5] - 2020-12-29
 
 ### Fixed

diff --git a/LICENSE b/LICENSE
@@ -1,33 +1,33 @@
-Unless otherwise specified by LICENSE.txt files in individual
-directories, or within individual files or functions, all code is:
-
-Copyright (c) 2008-2020, COMMIT developers
-All rights reserved.
-
-Redistribution and use in source and binary forms, with or without
-modification, are permitted provided that the following conditions are
-met:
-
-    * Redistributions of source code must retain the above copyright
-       notice, this list of conditions and the following disclaimer.
-
-    * Redistributions in binary form must reproduce the above
-       copyright notice, this list of conditions and the following
-       disclaimer in the documentation and/or other materials provided
-       with the distribution.
-
-    * Neither the name of the COMMIT developers nor the names of any
-       contributors may be used to endorse or promote products derived
-       from this software without specific prior written permission.
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
-A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
-OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
-SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
-LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
-DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
-THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
-(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
-OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+Unless otherwise specified by LICENSE.txt files in individual
+directories, or within individual files or functions, all code is:
+
+Copyright (c) 2008-2020, COMMIT developers
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+    * Redistributions of source code must retain the above copyright
+       notice, this list of conditions and the following disclaimer.
+
+    * Redistributions in binary form must reproduce the above
+       copyright notice, this list of conditions and the following
+       disclaimer in the documentation and/or other materials provided
+       with the distribution.
+
+    * Neither the name of the COMMIT developers nor the names of any
+       contributors may be used to endorse or promote products derived
+       from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/MANIFEST.in b/MANIFEST.in
@@ -1,7 +1,7 @@
-include README.md
-include LICENSE
-
-recursive-include commit *.h
-recursive-include commit *.cpp
-recursive-include commit *.pyx
+include README.md
+include LICENSE
+
+recursive-include commit *.h
+recursive-include commit *.cpp
+recursive-include commit *.pyx
 recursive-include commit *.c
diff --git a/README.md b/README.md
@@ -1,30 +1,30 @@
-# COMMIT
-
-The reconstructions recovered with existing tractography algorithms are *not really quantitative* even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic micro-structural features of the tissue, such as axonal density and diameter, by using multi-compartment models. COMMIT implements a novel framework to **re-establish the link between tractography and tissue micro-structure**.
-
-Starting from an input set of candidate fiber-tracts, which can be estimated using standard fiber-tracking techniques, COMMIT models the diffusion MRI signal in each voxel of the image as a *linear combination* of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, COMMIT seeks for the effective contribution of each of them such that they globally fit the measured signal at best.
-
-These weights can be easily estimated by solving a convenient **global convex optimization problem** and using efficient algorithms. Results clearly demonstrated the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically-plausible assessment of the structural connectivity in the brain.
-
-
-## Main features
-
-- Accepts and works with **any input tractogram** (i.e. set of fiber tracts).
-- Can easily implement and consider **any multi-compartment model** available in the literature: possibility to account for restricted, hindered as well as isotropic contributions into the signal forward model.
-- Very efficient: the core of the algorithm is implemented in C++ and using **multi-threading programming** for efficient parallel computation.
-- **Low memory** consumption using optimized sparse data structures, e.g. it can easily run on a standard laptop with 8GB RAM a full-brain tractogram from the HCP data (1M fibers, 3 shells, 1.25 mm^3 resolution).
-- **Soon**: **GPU implementation** for even faster model fitting.
-
-
-## Documentation
-
-More information/documentation, as well as a series of tutorials, can be found in the [wiki pages](https://github.com/daducci/COMMIT/wiki/Home).
-
-### Installation
-
-To install COMMIT, refer to the [installation guide](https://github.com/daducci/COMMIT/wiki/Installation).
-
-### Getting started
-
-To get started with the COMMIT framework, have a look at [this tutorial](https://github.com/daducci/COMMIT/wiki/Getting-started), which will guide you through the main steps of the processing.
-
+# COMMIT
+
+The reconstructions recovered with existing tractography algorithms are *not really quantitative* even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic micro-structural features of the tissue, such as axonal density and diameter, by using multi-compartment models. COMMIT implements a novel framework to **re-establish the link between tractography and tissue micro-structure**.
+
+Starting from an input set of candidate fiber-tracts, which can be estimated using standard fiber-tracking techniques, COMMIT models the diffusion MRI signal in each voxel of the image as a *linear combination* of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, COMMIT seeks for the effective contribution of each of them such that they globally fit the measured signal at best.
+
+These weights can be easily estimated by solving a convenient **global convex optimization problem** and using efficient algorithms. Results clearly demonstrated the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically-plausible assessment of the structural connectivity in the brain.
+
+
+## Main features
+
+- Accepts and works with **any input tractogram** (i.e. set of fiber tracts).
+- Can easily implement and consider **any multi-compartment model** available in the literature: possibility to account for restricted, hindered as well as isotropic contributions into the signal forward model.
+- Very efficient: the core of the algorithm is implemented in C++ and using **multi-threading programming** for efficient parallel computation.
+- **Low memory** consumption using optimized sparse data structures, e.g. it can easily run on a standard laptop with 8GB RAM a full-brain tractogram from the HCP data (1M fibers, 3 shells, 1.25 mm^3 resolution).
+- **Soon**: **GPU implementation** for even faster model fitting.
+
+
+## Documentation
+
+More information/documentation, as well as a series of tutorials, can be found in the [wiki pages](https://github.com/daducci/COMMIT/wiki/Home).
+
+### Installation
+
+To install COMMIT, refer to the [installation guide](https://github.com/daducci/COMMIT/wiki/Installation).
+
+### Getting started
+
+To get started with the COMMIT framework, have a look at [this tutorial](https://github.com/daducci/COMMIT/wiki/Getting-started), which will guide you through the main steps of the processing.
+