Adding in latest serial build of vanilla NEURON

.travis.yml

@@ -0,0 +1,18 @@
+language: python
+
+python:
+  - 3.6
+services:
+  - docker
+
+os:
+  - linux
+
+
+notifications:
+  email: true
+
+before_install:
+  - docker build -t pns .
+script:
+  - docker run pns python -c "print('built')"

Dockerfile

@@ -0,0 +1,34 @@
+# Distributed under the terms of the Modified BSD License.
+ARG BASE_CONTAINER=jupyter/scipy-notebook
+FROM $BASE_CONTAINER
+LABEL maintainer="Russell <[email protected]>"
+USER root
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+    fonts-dejavu \
+    gfortran \
+    gcc && \
+    rm -rf /var/lib/apt/lists/*
+RUN apt-get upgrade    
+RUN apt-get install -y ncurses-base ncurses-bin
+RUN apt-get update && apt-get install -y bzip2 ca-certificates automake libtool  \
+                       libncurses5-dev libreadline-dev libgsl0-dev cmake ssh
+USER jovyan
+
+WORKDIR $HOME
+RUN \
+  wget http://www.neuron.yale.edu/ftp/neuron/versions/v7.7/nrn-7.7.tar.gz && \
+  tar -xzf nrn-7.7.tar.gz && \
+  rm nrn-7.7.tar.gz
+WORKDIR $HOME/nrn-7.7
+ENV PATH /usr/bin/python3/python:/opt/conda/bin:/opt/conda/bin/conda:/opt/conda/bin/python:$PATH
+RUN ./configure --prefix=`pwd` --without-iv --with-nrnpython=/opt/conda/bin/python3
+USER root
+RUN sudo make all && \
+     make install
+USER jovyan
+WORKDIR src/nrnpython
+RUN python setup.py install
+RUN python -c "import neuron"
+ENV NEURON_HOME $HOME/nrn-7.7/x86_64
+ENV PATH $NEURON_HOME/bin:$PATH

README.md

@@ -1,6 +1,10 @@
+[![Build Status](https://travis-ci.com/russelljjarvis/docker-stacks-returned.svg?branch=scidash)](https://travis-ci.com/russelljjarvis/docker-stacks-returned)
+
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/russelljjarvis/docker-stacks-returned/master)
+
 # A hierarchy of Docker images for using SciDash tools
 
-Purpose: The building of development environments raises an unnecessary technical problem. In many cases even if someone has the technical capacity to build, it does not mean they will have time to do so. In order to remove this barrier to participation we have created some Docker images to allow people to use our tools. Each of these images serves Jupyter notebooks and including a Python scientific computing stack (extended from jupyter/docker-stacks/scipy-notebook), and some combination of NEURON-7.4, scoop, DEAP, sciunit, and neuronunit.
+Purpose: The building of development environments raises an unnecessary technical problem. In many cases even if someone has the technical capacity to build, it does not mean they will have time to do so. In order to remove this barrier to participation we have created some Docker images to allow people to use our tools. Each of these images serves Jupyter notebooks and including a Python scientific computing stack (extended from jupyter/docker-stacks/scipy-notebook), and some combination of NEURON-7.7, DASK, DEAP, sciunit, and neuronunit.
 
 ![Docker container hierarchy](https://github.com/scidash/assets/blob/master/mockups/Containerization%20and%20Continuous%20Integration%20Workflow.png)
 
@@ -77,3 +81,19 @@ c.DockerSpawner.extra_create_kwargs.update({
 })
 ```
 Then run `jupyterhub`, visit the indicated URL (e.g. `10.200.11.1:8000`) in your browser, and log in as a system user.  
+
+Ipython Parallel seems to benefit from tini
+
+https://github.com/krallin/tini
+
+NOTE: If you are using Docker 1.13 or greater, Tini is included in Docker itself. This includes all versions of Docker CE. To enable Tini, just pass the --init flag to docker run.
+
+Why tini? (init backwards)
+
+Using Tini has several benefits:
+
+It protects you from software that accidentally creates zombie processes, which can (over time!) starve your entire system for PIDs (and make it unusable).
+It ensures that the default signal handlers work for the software you run in your Docker image. For example, with Tini, SIGTERM properly terminates your process even if you didn't explicitly install a signal handler for it.
+It does so completely transparently! Docker images that work without Tini will work with Tini without any changes.
+If you'd like more detail on why this is useful, review this issue discussion: What is advantage of Tini?.
+

build-all

@@ -1,6 +1,6 @@
-for NAME in scipy-notebook-plus sciunit neuron-mpi-neuroml neuronunit neuronunit-openworm neuronunit-neuroconstruct neuronunit-optimization; do
+for name in scipy-notebook-plus sciunit neuron-mpi-neuroml neuronunit neuronunit-optimization; do
     echo "********************************"
-    echo "Building scidash/$NAME"
+    echo "Building scidash/$name"
     echo "********************************"
-    ./build $NAME
+    ./build $name
 done

dev/Dockerfile

@@ -0,0 +1,15 @@
+FROM scidash/neuronunit-optimization
+COPY stdout_worker.py $HOME/stdout_worker.py
+COPY func2rc.sh $HOME/func2rc.sh
+RUN cat $HOME/func2rc.sh >> ~/.bashrc
+RUN sudo chown -R jovyan /home/jovyan/work
+ENV QT_QPA_PLATFORM offscreen
+ENV PYTHONPATH $PYTHONPATH/home/jovyan/neuronunit/neuronunit/optimization
+RUN /bin/bash -c "source $HOME/func2rc.sh"
+WORKDIR $HOME/neuronunit/neuronunit
+RUN sudo /opt/conda/bin/pip install dask
+
+
+
+RUN sudo rm -r $HOME/work
+RUN sudo rm -r /opt/conda/lib/python3.5/site-packages/neuronunit*

efel_dm/Dockerfile

@@ -0,0 +1,56 @@
+# author Russell Jarvis [email protected]
+# author Rick Gerkin [email protected]
+# neuronunit-showcase
+
+FROM scidash/neuronunit-optimization
+RUN sudo rm -rf /opt/conda/lib/python3.5/site-packages/setuptools-27.2.0-py3.5.egg
+RUN sudo /opt/conda/bin/pip install --upgrade pip
+RUN sudo /opt/conda/bin/pip install --upgrade setuptools
+RUN sudo rm -rf /opt/conda/lib/python3.5/site-packages/allensdk-0.12.4.1-py3.5.egg
+RUN pip install git+https://github.com/fun-zoological-computing/AllenSDK.git
+# RUN conda update -n base conda
+USER $NB_USER
+
+# RUN pip uninstall tornado
+# move to a docker install script.
+RUN sudo /opt/conda/bin/pip install --upgrade pip
+# RUN sudo /opt/conda/bin/pip install git+https://github.com/scidash/sciunit.git@dev # --upgrade# --process-dependency-links --upgrade
+RUN sudo /opt/conda/bin/conda install -y cython
+
+RUN sudo /opt/conda/bin/pip install git+https://github.com/brian-team/brian2.git
+# faster glif
+# RUN sudo /opt/conda/bin/pip install allensdk --upgrade
+# RUN sudo /opt/conda/bin/conda install -y numpy deap dask numba
+# RUN sudo /opt/conda/bin/pip install allensdk --upgrade
+
+RUN sudo /opt/conda/bin/pip install git+git://github.com/BlueBrain/eFEL
+
+WORKDIR $HOME
+# RUN sudo /opt/conda/bin/pip install git+
+# RUN git clone https://github.com/AllenInstitute/sonata
+# WORKDIR /sonata/src/pysonata
+# RUN echo $pwd
+# RUN ls *.py
+# RUN python setup.py install
+
+RUN git clone https://github.com/AllenInstitute/bmtk.git
+WORKDIR bmtk
+RUN python setup.py install
+
+WORKDIR $HOME
+RUN sudo apt-get update -y 
+RUN sudo apt-get upgrade -y 
+RUN sudo apt-get -y install libhdf5-dev vim
+# RUN sudo /opt/bin/conda/pip install setuptools
+# RUN sudo /opt/conda/bin/pip install --upgrade protobuf 
+
+# RUN git clone
+# ing/AllenSDK
+# WORKDIR AllenSDK
+# RUN python setup.py install
+RUN sudo /opt/conda/bin/pip3 install pyscaffold
+RUN sudo /opt/conda/bin/pip install pip --upgrade
+RUN sudo /opt/conda/bin/pip3 install SALib
+# git+https://github.com/SALib/SALib.git
+
+ENTRYPOINT /bin/bash

julia_nb/Dockerfile

@@ -0,0 +1,41 @@
+FROM with_r
+USER root
+#RUN apt-get install -y julia
+# install Julia packages in /opt/julia instead of $HOME
+ENV JULIA_DEPOT_PATH=/opt/julia
+ENV JULIA_PKGDIR=/opt/julia
+ENV JULIA_VERSION=1.0.0
+
+RUN mkdir /opt/julia-${JULIA_VERSION} && \
+    cd /tmp && \
+    wget -q https://julialang-s3.julialang.org/bin/linux/x64/`echo ${JULIA_VERSION} | cut -d. -f 1,2`/julia-${JULIA_VERSION}-linux-x86_64.tar.gz && \
+    echo "bea4570d7358016d8ed29d2c15787dbefaea3e746c570763e7ad6040f17831f3 *julia-${JULIA_VERSION}-linux-x86_64.tar.gz" | sha256sum -c - && \
+    tar xzf julia-${JULIA_VERSION}-linux-x86_64.tar.gz -C /opt/julia-${JULIA_VERSION} --strip-components=1 && \
+    rm /tmp/julia-${JULIA_VERSION}-linux-x86_64.tar.gz
+RUN ln -fs /opt/julia-*/bin/julia /usr/local/bin/julia
+
+# Show Julia where conda libraries are \
+RUN mkdir /etc/julia && \
+    echo "push!(Libdl.DL_LOAD_PATH, \"$CONDA_DIR/lib\")" >> /etc/julia/juliarc.jl && \
+    # Create JULIA_PKGDIR \
+    mkdir $JULIA_PKGDIR && \
+    chown $NB_USER $JULIA_PKGDIR
+
+RUN julia -e 'import Pkg; Pkg.update()' && \
+    (test $TEST_ONLY_BUILD || julia -e 'import Pkg; Pkg.add("HDF5")') && \
+    julia -e 'import Pkg; Pkg.add("Gadfly")' && \
+    julia -e 'import Pkg; Pkg.add("RDatasets")' && \
+    julia -e 'import Pkg; Pkg.add("IJulia"); Pkg.add("StatsPlots");Pkg.add("Plots"); Pkg.add("StatsPlots");Pkg.add("DataFrames")'
+
+RUN julia -e 'import Pkg; Pkg.add("Seaborn"); Pkg.add("PyPlot")'
+RUN julia -e 'import Pkg;Pkg.clone("https://github.com/gsoleilhac/NSGAII.jl")'
+USER jovyan
+# Precompile Julia packages \
+RUN sudo julia -e 'using Pkg; Pkg.add("IJulia"); using IJulia'
+ADD stochastic_gd.jl .
+RUN sudo julia stochastic_gd.jl
+
+# move kernelspec out of home \
+# mv $HOME/.local/share/jupyter/kernels/julia* $CONDA_DIR/share/jupyter/kernels/ && \
+# chmod -R go+rx $CONDA_DIR/share/jupyter && \
+# rm -rf $HOME/.local && $JULIA_PKGDIR $CONDA_DIR/share/jupyter

julia_nb/stochastic_gd.jl

@@ -0,0 +1,53 @@
+println("reminder to Russell")
+println("to install packages use")
+println("launch julia using sudo")
+println("try to import module first using, 'using'")
+println("include('ml.jl')")
+#println("Pkg.add('PyCall')")
+println("\n\n\n\n\n\n")
+using Pkg
+
+function trypy()
+	try
+        ENV["PYTHON"] = "/opt/conda/bin/python"
+        Pkg.rm("PyCall")
+        Pkg.build("PyCall")
+        Pkg.test("PyCall")
+        plt = pyimport("matplotlib.pyplot")
+        x = range(0;stop=2*pi,length=1000); y = sin.(3*x + 4*cos.(2*x));
+        plt.plot(x, y, color="red", linewidth=2.0, linestyle="--")
+        #plt.show()
+
+		#return unreliable_connect()
+	catch ex
+        ENV["PYTHON"] = "/anaconda3/bin/python"
+        Pkg.rm("PyCall")
+        Pkg.build("PyCall")
+        Pkg.test("PyCall")
+
+        math = pyimport("math")
+        Pkg.test("PyCall")
+        plt = pyimport("matplotlib.pyplot")
+        x = range(0;stop=2*pi,length=1000); y = sin.(3*x + 4*cos.(2*x));
+        plt.plot(x, y, color="red", linewidth=2.0, linestyle="--")
+
+        math.sin(math.pi / 4) # returns ≈ 1/√2 = 0.70710678...
+	   end
+end
+Pkg.add("StatsPlots")
+Pkg.add("PyCall")
+Pkg.add("GR")
+Pkg.add("IJulia");
+Pkg.add("Plots");
+Pkg.add("StatsPlots"); #to install the StatPlots package.
+Pkg.add("DataFrames");
+Pkg.add("Seaborn")
+Pkg.add("PyPlot")
+Pkg.add("Knet")
+using DataFrames
+#    using IJulia
+using Knet
+using Plots;
+using StatsPlots;
+using PyCall;
+println("done")

network/#Dockerfile#

@@ -0,0 +1,23 @@
+FROM scidash/neuronunit-optimization
+  # move to a docker install script.
+
+RUN sudo /opt/conda/bin/pip install git+https://github.com/scidash/sciunit.git@dev --process-dependency-links --upgrade
+RUN sudo /opt/conda/bin/conda install -y cython
+RUN sudo /opt/conda/bin/pip install pynn lazyarray
+
+RUN sudo /opt/conda/bin/pip install git+https://github.com/brian-team/brian2.git
+  # faster glif
+#RUN sudo /opt/conda/bin/pip install git+https://github.com/russelljjarvis/AllenSDK.git
+RUN sudo /opt/conda/bin/conda install -y numpy deap dask numba
+RUN sudo /opt/conda/bin/pip install neurodynex
+
+RUN sudo /opt/conda/bin/pip install coverage lmfit
+RUN sudo /opt/conda/bin/pip install allensdk #--upgrade
+RUN sudo /opt/conda/bin/conda install pandas
+RUN sudo /opt/conda/bin/pip install toolz cloudpickle
+RUN sudo /opt/conda/bin/pip install pyscaffold
+
+RUN git clone https://github.com/SALib/SALib.git
+WORKDIR SALib
+RUN python setup.py develop
+RUN sudo /opt/conda/bin/pip install SALib

network/Dockerfile

@@ -0,0 +1,36 @@
+FROM scidash/neuronunit-optimization
+  # move to a docker install script.
+
+RUN sudo /opt/conda/bin/pip install git+https://github.com/scidash/sciunit.git@dev --process-dependency-links --upgrade
+RUN sudo /opt/conda/bin/conda install -y cython
+RUN sudo /opt/conda/bin/pip install pynn lazyarray
+
+RUN sudo /opt/conda/bin/pip install git+https://github.com/brian-team/brian2.git
+  # faster glif
+#RUN sudo /opt/conda/bin/pip install git+https://github.com/russelljjarvis/AllenSDK.git
+RUN sudo /opt/conda/bin/conda install -y numpy deap dask numba
+RUN sudo /opt/conda/bin/pip install neurodynex
+
+RUN sudo /opt/conda/bin/pip install coverage lmfit
+RUN sudo /opt/conda/bin/pip install allensdk #--upgrade
+RUN sudo /opt/conda/bin/conda install pandas
+RUN sudo /opt/conda/bin/pip install toolz cloudpickle
+RUN sudo /opt/conda/bin/pip install setuptools
+RUN sudo /opt/conda/bin/conda install -c conda-forge pyscaffold
+RUN sudo /opt/conda/bin/pip install --upgrade pip
+RUN sudo /opt/conda/bin/conda install python=3.5.0
+# RUN sudo /opt/conda/bin/pip install pyscaffold
+# RUN sudo /opt/conda/bin/pip install SALib
+
+# RUN git clone https://github.com/SALib/SALib.git
+# WORKDIR SALib
+# RUN python3 setup.py develop
+
+# uncomment to give PyNN mpi.
+# note this is a bad idea. For this project.
+# MPI is used for non-embarrasingly parallel computations,
+# we use dask here, for embarrassingly parallel.
+# RUN sudo apt-get update -y
+# RUN sudo apt-get install -y mpich
+# RUN pip install mpi4py
+RUN pip install git+https://github.com/russelljjarvis/modality

network/Dockerfile (rjjarvis's conflicted copy 2019-04-02)

@@ -0,0 +1,23 @@
+FROM scidash/neuronunit-optimization
+  # move to a docker install script.
+
+RUN sudo /opt/conda/bin/pip install git+https://github.com/scidash/sciunit.git@dev --process-dependency-links --upgrade
+RUN sudo /opt/conda/bin/conda install -y cython
+RUN sudo /opt/conda/bin/pip install pynn lazyarray
+
+RUN sudo /opt/conda/bin/pip install git+https://github.com/brian-team/brian2.git
+  # faster glif
+#RUN sudo /opt/conda/bin/pip install git+https://github.com/russelljjarvis/AllenSDK.git
+RUN sudo /opt/conda/bin/conda install -y numpy deap dask numba
+RUN sudo /opt/conda/bin/pip install neurodynex
+
+RUN sudo /opt/conda/bin/pip install coverage lmfit
+RUN sudo /opt/conda/bin/pip install allensdk #--upgrade
+RUN sudo /opt/conda/bin/conda install pandas
+RUN sudo /opt/conda/bin/pip install toolz cloudpickle
+RUN sudo /opt/conda/bin/pip install pyscaffold
+
+# RUN git clone https://github.com/SALib/SALib.git
+# WORKDIR SALib
+# RUN python setup.py develop
+RUN sudo /opt/conda/bin/pip install SALib