Price for excellence in education awarded to Hans Petter Langtangen

Professor Hans Petter Langtangen was awarded the Olav Thon Foundation prize for excellence in education 2016. He is  a world-leading pioneer introducing python scripting in science education, and his book Python Scripting for Computational Science (Springer) was quickly sold out when it was released in 2003, and the new edition is still on the best-selling lists. The price was awarded for his work on modernizing the education at the Faculty of Mathematics and Natural Sciences, University of Oslo.

pythonbook1

Traditionally, science courses with much use of mathematical models applied pen and paper techniques to solve the mathematical problems. This is still so in most courses in the world. However, Langtangen wanted the students to solve mathematical problems through programming from day 1, because this is the way one does mathematics today in industry and research.

In 1999 he started a course at UiO with the aim of teaching scripting and automation in science, and the course notes evolved into the book in 2003, placing UiO in the forefront when it comes to computation in science education.

Impact
Langtangen has educated over 1000 people in Python, both scientists and administrative software developers. When he started in 1999, Python was hardly used at all in Norwegian industry, now it is commonly used. And by “Python” Langtangen mean much more than the language, it’s the way of working: automating manual operations for reliability, being more effective, seeing new ways to do things.

Langtangen is director of the Center for Biomedical Computing, a Norwegian Center of Excellence 2007-2017 at the  Simula Research Laboratory.

This is the second time this price is awarded to a CINPLA member.

CINPLA faculty awarded huge grant for a new consortium: DigiBrain

The Norwegian Research Council launched a new strategic initiative entitled “Digital Life – Convergence for Innovation” this year, and Marianne Fyhn is leading the consortium: DigiBrain: From genes to brain function in health and disease.

The primary objective of DigiBrain is to establish a pipeline for linking genetic information to systems-level measures of brain behaviour by means of multiscale computational modeling and targeted experimental animal studies at the levels of neuron, neural networks and systems. Further, DigiBrain will in collaboration with pharmaceutical and medical technology companies, prominent international research environments, explore new and innovative ways for drugs discovery by use of the multiscale computational model.

Partners (in semi-random order):
UiO: Marianne Fyhn, Gaute Einevoll, Anders Malthe-Sørensen, Camilla Esguerra, Torkel Hafting
OUS: Ole Andreassen
Simula: Aslak Tveito
NMBU: Finn-Arne Welzien
UiB: Srdjan Djurovic
NTNU: Cliff Kentros
UIT: John-Sigurd Svendsen

Pharmasum: Anders Fugelli
Holberg EEG: Harald Aulien

Univ Julich: Markus Diesman
UCSD: Anders Dale

 

 

PhD summerschool: Understanding Measurements in Neuroscience

CINPLA organized the first summer-school for the Norwegian Research School in Neuroscience 16-22 August 2015. The program was ambitious and the students were exhausted, but happy after 60 hours with intense theoretical and practical research training.

The aim of the summer school was to give the students a deeper understanding of what we actually measure with some established state-of-the-art methods in neuroscience.

Main lecturers:
Andy Edwards (patch-clamp), Emre Yaksi & Erlend Nagelhus (Ca2+ imaging), Joel Glover (VSD), Torkel Hafting (tetrode recordings), Torbjørn Ness (computational modeling), Special guest lecturer was Michael Hausser, University College London.

Read more about the summer-school here.
NRSN-logo

Install neo++ in a virtual environment

sudo apt-get install virtualenvwrapper python-pyqt4
mkvirtualenv NEO --system-site-packages
workon NEO

Then copy the following into a bashfile and run it – bash bashfile

#!/bin/bash
# Install script
set -x  # make sure each command is printed in the terminal

function pip_install {
  pip install --upgrade "$@"
  if [ $? -ne 0 ]; then
    echo "could not install $p - abort"
    exit 1
  fi
}

pip_install cython
pip_install h5py==2.5.0
pip_install tables
pip_install sqlalchemy
pip_install sqlalchemy-migrate
pip_install scikit-learn
pip_install pywavelets

git clone https://github.com/NeuralEnsemble/elephant.git
git clone https://github.com/OpenElectrophy/OpenElectrophy.git
git clone https://github.com/rproepp/spykeviewer.git
git clone https://github.com/rproepp/spykeutils.git
git clone https://github.com/jzaremba/guidata.git
git clone https://github.com/PierreRaybaut/guiqwt.git

cd guidata && python setup.py install
cd ..
cd guiqwt && python setup.py build install
cd ..
cd python-neo && python setup.py develop
cd ..
cd spykeutils && python setup.py develop
cd ..
cd spykeviewer && python setup.py develop
cd ..
cd OpenElectrophy && python setup.py develop
cd ..
cd elephant && python setup.py develop

Cinpla PhD students awarded “Ideprisen”

With fierce competition from about 160 other projects, our PhD students was awarded the prize for their development of science-education apps.

In addition to apps for molecular dynamics and waves the team have developed an app to illustrate and understand how nerve cells interact and function in a network. These types of networks are believed to form the basic structures of complex phenomenons observed in the mammalian brain. Together with Inven2 they are now working to further develop their concept.

A screenshot of Neuronify – the nerve cell app.

neuronify-0.91

Read more about this event here (in Norwegian)

Install klustakwik and klustaviewa on ubuntu

Note that this project is being replaced by phy

First of all you need the right dependencies, its easiest to do with anaconda – make a virtual environment!

cd into your preferred directory e.g. $HOME/apps/ in this example, clone the necessary repos, make symlink and install.

git clone https://github.com/klusta-team/klustaviewa.git
git clone https://github.com/rossant/qtools
git clone https://github.com/rossant/galry
git clone https://github.com/klusta-team/spikedetekt
git clone https://github.com/klusta-team/kwiklib
git clone https://github.com/klusta-team/klustakwik.git 

cd klustaviewa

ln -s ../qtools/qtools qtools
ln -s ../galry/galry galry
ln -s ../spikedetekt2/spikedetekt2 spikedetekt2
ln -s ../kwiklib/kwiklib kwiklib

python setup.py develop

make klustakwik and rename the executable

cd $HOME/apps/klustakwik
make 
mv KlustaKwik klustakwik

export path in your ~/.bashrc file

export PATH=$HOME/apps/klustakwik/:$PATH

Download test data (.zip) and change params.prm to this file cd to example dir and enter

klusta params.par