Motion Clouds: Synthesis of random textures for motion perception (Leon et al. 2012)

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We describe a framework to generate random texture movies with controlled information content. In particular, these stimuli can be made closer to naturalistic textures compared to usual stimuli such as gratings and random-dot kinetograms. We simplified the definition to parametrically define these "Motion Clouds" around the most prevalent feature axis (mean and bandwith): direction, spatial frequency, orientation.
1 . Leon PS, Vanzetta I, Masson GS, Perrinet LU (2012) Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception. J Neurophysiol 107:3217-26 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Connectionist Network;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
Simulation Environment: Python;
Model Concept(s): Pattern Recognition; Temporal Pattern Generation; Spatio-temporal Activity Patterns; Parameter Fitting; Methods; Perceptual Categories; Noise Sensitivity; Envelope synthesis; Sensory processing; Motion Detection;
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= MotionClouds: installing and running the python scripts =
[[TagMotionClouds|MotionClouds]] are parameterized stimuli with controlled motion content and no spatial coherence.  They are precisely tuned in the frequency space.

 * A full description can be found in Paula S. Leon, Ivo Vanzetta, Guillaume S. Masson, Laurent U. Perrinet. Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception, URL . Journal of Neurophysiology, 107(11):3217--3226, 2012, see or .

== installing and running the python scripts ==
This package consists of:
 * {{{}}} : the API with all the math and display routines,
 * {{{test_*.py}}} : different types of stimuli are tested,
 * {{{experiment_*py}}} : different experiments.
 * {{{fig_*py}}} : different scripts used to generate wiki pages.
 * {{{figures}}} : resulting figures of tests and experiments (as set in the variable {{{MotionClouds.figpath}}}.
 * {{{Makefile}}} : a GNUmake file to edit files {{{make edit}}}, generate figures {{{make figures}}} or compile the documentation {{{make doc}}}.

== Installation ==

 * Installation of MotionClouds consists simply in downloading the {{{}}} file which contains all routines to compute and use the MotionClouds textures. This script uses [[|python]]] which comes (pre-installed /  easy to download and install) on many operating systems.

 * Installation has some dependencies: 
  1. mandatory: {{{numpy}}} is the core library used to compute textures,
  1. optional: {{{mayavi}}} is used to visualize envelopes,
  1. optional: {{{ffmpeg}}} is used to generate movies.
  1. optional: {{{matplotlib}}}, {{{scipy}}} (with PIL support) and {{{imagemagick}}} are used to generate figures in the documentation.
  1. optional: {{{progressbar}}} for displaying progress of encoding.

=== installation using custom scripts ===

 * depending on your system you should use in a terminal window {{{
}}} or {{{
 * an alternative is to use a virtual machine such as for instance the one provided by the [[|NeuroDebian team]].

=== Installation in Debian-based distributions (such as Ubuntu) ===

 * Use the {{{aptitude}}} front end to install packages: (or alternatively {{{apt -get}}} if you feel confident with that tool instead)

 * {{{python}}} is supported by most distribution and should already be installed. You can check which version is installed : {{{
python -V

 * The same libraries as for MacOsX need to be installed : {{{
sudo aptitude install python-scipy python-numpy python-matplotlib

 * Idem for the progress bar module {{{
sudo easy_install progressbar 

 * Install the {{{ffmpeg}}} encoder to work with mpeg, avi, etc, videos: {{{
sudo aptitude install ffmpeg

 * when creating MoiMoin pages, it is useful to package images in a zip file: {{{
aptitude install zip

=== Installation on MacOsX: EPD ===

 * Enthought distributes a battery-included installation of python. It is recommended to use the i386 version as the 64-bits version lacks a proper compilation of MayaVi. You will still need {{{ffmpeg}}} to make movies (see HomeBrew or MacPorts section below).

=== Installation on MacOsX: HomeBrew (for more experienced users) ===

 * install it following their [[|instructions]] : {{{
ruby -e "$(curl -fsSL"
 * then install the following packages {{{

# install python through HomeBrew as a framework
brew install python --framework

# bootstrap pip
/usr/local/share/python/easy_install pip
/usr/local/share/python/pip install --upgrade distribute

# libraries
brew install gfortran
pip install -U ipython

# useful packages
pip install -U nose
pip install -U progressbar
easy_install pyreport
easy_install -f -U PIL==1.1.7

# numpy et al
pip install -U numpy
pip install -U scipy
pip install -U -e
# pip install -f matplotlib

pip install -U sphinx pyflakes rope
brew install sip
brew install pyqt
pip install -U spyder

# mayavi
brew install vtk --python
pip install -U traitsbackendqt
pip install -U configobj
pip install  -U "Mayavi[app]"
  * be sure to install ffmpeg : {{{
brew install ffmpeg
brew install zip

=== Installation on MacOsX: MacPorts (outdated documentation) ===
On MacOsX, this may be achieved using !MacPorts:
 * [[|MacPorts]] is a generic package manager, somewhat related to Debian's {{{apt}}} scheme. You will need the XCode package which sits in your MacOSX installation DVD or may downloaded on Apple's site or even borrowed to me.
 * Once installed, do the following on the command-line 

  * on Leopard (python 26 works fine too): {{{
sudo port install python25 python_select 
sudo python_select python25
sudo port install  py25-pil py25-numpy py25-scipy py25-ipython py25-matplotlib
sudo port install py25-enthoughtbase py25-mayavi py25-traitsbackendqt
  * on Snow Leopard: {{{
sudo port install python26 python_select 
sudo python_select python26
sudo port install  py26-pil py26-numpy py26-scipy py26-ipython py26-matplotlib
sudo port install py26-enthoughtbase py26-mayavi py26-traitsbackendqt
 * then optionally, {{{
sudo easy_install progressbar pygarrayimage pyglet
  * be sure to install ffmpeg : {{{
sudo port install ffmpeg

TagMotion TagMotionClouds

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