Merge branch 'release/v0.3.5'

Author: EtienneCmb

.travis.yml

@@ -2,50 +2,48 @@ language: python
 dist: trusty
 python:
   - "3.6"
-before_script:
-  - "export DISPLAY=:99.0"
-  - "sh -e /etc/init.d/xvfb start"
-  - sleep 3 # give xvfb some time to start
+before_install:
+  # Fix screen resolution to 1280x1024x16 :
+  - "/sbin/start-stop-daemon --start --quiet --pidfile /tmp/custom_xvfb_99.pid --make-pidfile --background --exec /usr/bin/Xvfb -- :99 -ac -screen 0 1280x1024x16"
 install:
   - pushd $PWD
   # ------------------- PYTHON ENVIRONNEMENT -------------------
   # Deactivate travis environnement :
   - deactivate
-  # We do this conditionally because it saves us some downloading if the
-  # version is the same.
-  - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
-      wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O miniconda.sh;
-    else
-      wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
-    fi
+  # Miniconda installation :
+  - wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
   - bash miniconda.sh -b -p $HOME/miniconda
   - export PATH="$HOME/miniconda/bin:$PATH"
   - hash -r
   - conda config --set always_yes yes --set changeps1 no
   - conda update -q conda
-  # Useful for debugging any issues with conda
   - conda info -a
 
-  # Replace dep1 dep2 ... with your dependencies
+  # Install dependencies :
   - conda create -q -n testenv python=$TRAVIS_PYTHON_VERSION numpy scipy matplotlib pip
   - source activate testenv
-  - pip install mne
-  - pip install nibabel
-  - pip install setuptools
-  - pip install nose
-  - pip install PyOpenGL PyOpenGL_accelerate
-  - pip install codecov
-  - pip install pytest pytest-cov
+  - pip install mne nibabel setuptools PyOpenGL PyOpenGL_accelerate codecov pytest pytest-cov
   # ------------------- VISPY -------------------
   - cd ../
+  # Install the developper version of VisPy :
   - pip install -e git+https://github.com/vispy/vispy#egg=vispy-dev
   - cd visbrain/
   # ------------------- VISBRAIN -------------------
   - pip install -e .
-script: bash build_install.sh
+before_script:
+  - "export DISPLAY=:99.0"
+  - "sh -e /etc/init.d/xvfb start"
+  - sleep 3 # give xvfb some time to start
+script: py.test --cov --verbose
 cache:
   apt: true
 notifications:
     email: false
 after_success:
   - codecov
+
+# screenshot tests are really slow on travis... but installing image librairies
+# does't fix it.
+# before_install:
+#   - sudo apt-get -qq install libfreetype6-dev libjpeg-turbo-progs
+# sudo: required

MANIFEST.in

@@ -13,3 +13,6 @@ include visbrain/sleep/sleep_icon.svg
 include visbrain/topo/topo_icon.svg
 include visbrain/colorbar/colorbar_icon.svg
 include visbrain/figure/figure_icon.svg
+
+# Add url path :
+include visbrain/data_url.txt

README.rst

@@ -3,6 +3,9 @@
 .. image:: https://travis-ci.org/EtienneCmb/visbrain.svg?branch=master
     :target: https://travis-ci.org/EtienneCmb/visbrain
 
+.. image:: https://ci.appveyor.com/api/projects/status/fdxhhmpagms1so8l?svg=true
+    :target: https://ci.appveyor.com/project/EtienneCmb/visbrain/branch/master
+
 .. image:: https://codecov.io/gh/EtienneCmb/visbrain/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/EtienneCmb/visbrain
 

appveyor.yml

@@ -0,0 +1,33 @@
+build: false
+
+environment:
+  matrix:
+    - PYTHON_VERSION: 3.6
+      MINICONDA: C:\Miniconda36-x64
+
+init:
+  - "ECHO %PYTHON_VERSION% %MINICONDA%"
+
+install:
+  - ps: iex ((new-object net.webclient).DownloadString('https://raw.githubusercontent.com/appveyor/ci/master/scripts/enable-desktop.ps1'))
+  # - ps: $screen_resolution = '1280x800'; iex ((new-object net.webclient).DownloadString('https://raw.githubusercontent.com/appveyor/ci/master/scripts/enable-desktop.ps1'))
+  # ------------------- PYTHON ENVIRONNEMENT -------------------
+  - "set PATH=%MINICONDA%;%MINICONDA%\\Scripts;%PATH%"
+  - conda config --set always_yes yes --set changeps1 no
+  - conda update -q conda
+  - conda info -a
+  - "conda create -q -n testenv python=%PYTHON_VERSION% numpy scipy matplotlib pip"
+  # Activate testing environnement :
+  - activate testenv
+  # Install dependencies :
+  - pip install mne nibabel setuptools PyOpenGL PyOpenGL_accelerate pytest pytest-cov
+  # ------------------- VISPY -------------------
+  - cd ../
+  - pip install -e git+https://github.com/vispy/vispy#egg=vispy-dev
+  - ls
+  - cd visbrain/
+  # ------------------- VISBRAIN -------------------
+  - pip install -e .
+
+test_script:
+  - py.test --cov --verbose

build_install.sh

@@ -82,9 +82,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '0.3.4'
+version = '0.3.5'
 # The full version, including alpha/beta/rc tags.
-release = '0.3.4'
+release = '0.3.5'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

docs/conf.py

@@ -89,7 +89,18 @@ First, you will need to create a Figure objects with the files to load, titles,
 * :ref:`colorbar_to_axis` : add a colorbar to a specific axis
 * :ref:`shared_colorbar` : add a shared colorbar
 
-.. autoclass:: visbrain.figure.figure.Figure
+.. currentmodule:: visbrain.figure.figure
+
+.. autoclass:: Figure
+
+    .. rubric:: Methods
+
+    .. autosummary::
+        ~Figure.show
+        ~Figure.save
+        ~Figure.colorbar_to_axis
+        ~Figure.shared_colorbar
+
 
 Methods
 ^^^^^^^
@@ -99,24 +110,24 @@ Methods
 show
 ~~~~
 
-.. automethod:: visbrain.figure.Figure.show
+.. automethod:: Figure.show
 
 .. _save:
 
 save
 ~~~~
-.. automethod:: visbrain.figure.Figure.save
+.. automethod:: Figure.save
 
 .. _colorbar_to_axis:
 
 colorbar_to_axis
 ~~~~~~~~~~~~~~~~
 
-.. automethod:: visbrain.figure.Figure.colorbar_to_axis
+.. automethod:: Figure.colorbar_to_axis
 
 .. _shared_colorbar:
 
 shared_colorbar
 ~~~~~~~~~~~~~~~
 
-.. automethod:: visbrain.figure.Figure.shared_colorbar
+.. automethod:: Figure.shared_colorbar

docs/figure.rst

@@ -1,6 +1,9 @@
 .. image:: https://travis-ci.org/EtienneCmb/visbrain.svg?branch=master
     :target: https://travis-ci.org/EtienneCmb/visbrain
 
+.. image:: https://ci.appveyor.com/api/projects/status/fdxhhmpagms1so8l?svg=true
+    :target: https://ci.appveyor.com/project/EtienneCmb/visbrain/branch/master
+
 .. image:: https://codecov.io/gh/EtienneCmb/visbrain/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/EtienneCmb/visbrain
 
@@ -69,14 +72,14 @@ Finally, install Visbrain :
 
 .. code-block:: shell
 
-    pip install visbain
+    pip install visbrain
 
 Develop mode
 ============
 
 .. code-block:: shell
 
-    git clone git@github.com:EtienneCmb/visbrain.git visbrain/
+    git clone https://github.com/EtienneCmb/visbrain.git visbrain/
     cd visbrain/
     pip install -r requirements.txt
     python setup.py develop 

docs/index.rst

@@ -24,6 +24,7 @@ Main features
 
 * **Display topographic map**
     * Find coordinates according to channel names
+    * Add connectivity edges
     * Support multiple coordinate systems
     * Highly controllable colorbar
 * **Grid representation**

docs/picture/picsignal/ex_2d_signal.png

@@ -8,17 +8,17 @@
 
 .. image:: ../../picture/picbrain/ex_crossec_and_volume.png
 """
-import os
 from visbrain import Brain
-from visbrain.io import read_nifti
+from visbrain.io import read_nifti, download_file
 
 """Import the volume and the associated affine transformation
 """
-volume_name = 'GG-853-WM-0.7mm'
-path_to_nifti = os.getenv("HOME")
-file_nifti = 'GG-853-WM-0.7mm.nii.gz'
-path = os.path.join(path_to_nifti, file_nifti)
-data, header, tf = read_nifti(path)
+volume_name = 'GG-853-WM-0.7mm.nii.gz'
+
+"""Download the file. 
+"""
+download_file(volume_name)
+data, header, tf = read_nifti(volume_name)
 
 vb = Brain()
 

docs/picture/picsignal/ex_3d_signal.png

@@ -16,14 +16,14 @@
 
 from visbrain import Brain
 from visbrain.utils import (add_brain_template, remove_brain_template)
+from visbrain.io import download_file
 
+"""Download the brain template. Use either 'WhiteMatter', 'Inflated' or
+'Sphere'
 """
-Define path to the template and load it. By default, the path is set to
-~/home/Templates/ so you have to adapt it.
-"""
-path_to_file = os.path.join(*(os.getenv("HOME"), 'Templates',
-                              'WhiteMatter.npz'))
-mat = np.load(path_to_file)
+template = 'WhiteMatter'
+download_file(template + '.npz')
+mat = np.load(template + '.npz')
 
 """
 Get variables for defining a new template. Vertices are nodes connected by the
@@ -39,16 +39,16 @@
 Add the template to visbrain. After adding this template, it will always be
 accessible unless you use the remove_brain_template() function
 """
-add_brain_template('WhiteMatter', vert, faces, norm, lr_index)
+add_brain_template(template, vert, faces, norm, lr_index)
 
 """
 Open the interface and select the added template
 """
-vb = Brain(a_template='WhiteMatter')
+vb = Brain(a_template=template)
 print('Brain templates : ', vb.brain_list())
 vb.show()
 
 """
 Finally, and this is not a necessity, remove the template
 """
-remove_brain_template('WhiteMatter')
+remove_brain_template(template)

docs/picture/picsignal/ex_butterfly.png

@@ -9,19 +9,22 @@
 which is defined as the number of contributing sources per vertex.
 
 Download source's coordinates (xyz_sample.npz) :
-https://drive.google.com/open?id=0B6vtJiCQZUBvSFJvaTFSRDJvMEE
+https://www.dropbox.com/s/whogfxutyxoir1t/xyz_sample.npz?dl=1
 
 .. image:: ../../picture/picbrain/ex_sources.png
 """
-from visbrain import Brain
 import numpy as np
 
+from visbrain import Brain
+from visbrain.io import download_file
+
 # Define a empty dictionnary :
 kwargs = {}
 
 """
 Load the xyz coordinates and corresponding subject name
 """
+download_file('xyz_sample.npz')
 mat = np.load('xyz_sample.npz')
 kwargs['s_xyz'], subjects = mat['xyz'], mat['subjects']
 

docs/picture/picsignal/ex_custom_interface.png

@@ -6,20 +6,23 @@
 and connect them.
 
 Download source's coordinates (xyz_sample.npz) :
-https://drive.google.com/open?id=0B6vtJiCQZUBvSFJvaTFSRDJvMEE
+https://www.dropbox.com/s/whogfxutyxoir1t/xyz_sample.npz?dl=1
 
 .. image:: ../../picture/picbrain/ex_connectivity.png
 """
 from __future__ import print_function
 import numpy as np
+
 from visbrain import Brain
+from visbrain.io import download_file
 
 # Create an empty kwargs dictionnary :
 kwargs = {}
 
 # ____________________________ DATA ____________________________
 
 # Load the xyz coordinates and corresponding subject name :
+download_file('xyz_sample.npz')
 mat = np.load('xyz_sample.npz')
 s_xyz, subjects = mat['xyz'], mat['subjects']
 

docs/picture/pictopo/ex_connectivity.png

@@ -20,11 +20,14 @@
 import numpy as np
 
 from visbrain import Brain
+from visbrain.io import download_file
 
 # Load thalamus sources :
+download_file('thalamus.txt')
 s_xyz = np.loadtxt('thalamus.txt')
 # Load alpha power. In fact, the PX.npy contains the power across several time
 # windows. So we take the mean across time :
+download_file('Px.npy')
 s_data = np.load('Px.npy').mean(1) * 10e26
 
 # Define a Brain instance :

docs/topo.rst

@@ -6,14 +6,17 @@
 time-series can then be controlled from the GUI in the Sources/Time-series tab.
 
 Download source's coordinates (xyz_sample.npz) :
-https://drive.google.com/open?id=0B6vtJiCQZUBvSFJvaTFSRDJvMEE
+https://www.dropbox.com/s/whogfxutyxoir1t/xyz_sample.npz?dl=1
 
 .. image:: ../../picture/picbrain/ex_time_series.png
 """
-from visbrain import Brain
 import numpy as np
 
+from visbrain import Brain
+from visbrain.io import download_file
+
 # Load the xyz coordinates and corresponding subject name :
+download_file('xyz_sample.npz')
 s_xyz = np.load('xyz_sample.npz')['xyz']
 s_xyz = s_xyz[4::25, ...]
 s_text = [str(k) for k in range(s_xyz.shape[0])]

examples/brain/01_cross_sections_and_volume.py

@@ -6,15 +6,18 @@
 pictures can then be controlled from the GUI in the Sources/Pictures tab.
 
 Download source's coordinates (xyz_sample.npz) :
-https://drive.google.com/open?id=0B6vtJiCQZUBvSFJvaTFSRDJvMEE
+https://www.dropbox.com/s/whogfxutyxoir1t/xyz_sample.npz?dl=1
 
 .. image:: ../../picture/picbrain/ex_pictures.png
 """
-from visbrain import Brain
 import numpy as np
 
+from visbrain import Brain
+from visbrain.io import download_file
+
 kwargs = {}
 # Load the xyz coordinates and corresponding subject name :
+download_file('xyz_sample.npz')
 s_xyz = np.load('xyz_sample.npz')['xyz']
 s_xyz = s_xyz[4::10, ...]
 kwargs['s_text'] = [str(k) for k in range(s_xyz.shape[0])]