E-Cell System is, a software platform for modeling, simulation and analysis of complex, heterogeneous and multi-scale systems like the cell. E-Cell has multi-algorithm, multi-timescale and multi-spatial-representation as its central feature.
You can try E-Cell4 without installing it on your computer’s hard drive.
You can do this by just clicking
All you need to do is just running the cells in each of the example Jupyter notebooks.
- Python (2.7 and 3.4, 3.5, 3.6 both major versions are supported [3.4 is only supported on Linux, 3.6 is only supported on Mac])
- pip (8.1 or later)
- hdf5 (required only on Windows.)
We strongly recommend that you run E-Cell4 with Jupyter Notebook. Some E-Cell4 functions (for visualization, datastore) optionally depend on
- matplotlib (1.5.1 or later)
- ffmpeg
- pandas
We recommend that you install Miniconda to manage Python packages. Note that we do not support Python2.7 64bit for Windows.
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Install Miniconda for Windows from http://conda.pydata.org/miniconda.html
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Run the following commands on command prompt
conda install hdf5 matplotlib notebook pip install ecell
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(Important) E-Cell4 for Windows needs the latest
hdf5. If there's any problem, please update the version of hdf5.conda update hdf5
If you use animated visualization with E-Cell4, please install ffmpeg windows build and add its path to your USER PATH enviromental variable.
We recommend that you install Miniconda to manage Python packages. After installing Miniconda, run the following commands in your terminal.
(NOTICE for Mac users) We do not provide Python3.5 whl for Mac. Instead we provide Python3.6 whl for Mac. To use Python3.6 enviroment, please refer to http://conda.pydata.org/docs/py2or3.html . Continuum.io already offers Python3.6 conda packages.
# After installing Miniconda2 or Miniconda3 (Here we assume that you installed Miniconda3).
~/miniconda2/bin/conda install matplotlib notebook
# Download E-Cell4 whl file for your Python version from https://github.com/ecell/ecell4/releases before running this command.
~/miniconda2/bin/pip install ecell
# If you want animation support, install ffmpeg with homebrew
brew install ffmpeg
# or if you use Ubuntu Linux
# apt install ffmpegHere we download example notebooks from https://github.com/ecell/ecell4-notebooks and open it with Jupyter Notebook.
Open powershell and run these commands. Here we assume that you installed Miniconda(Python3.5) to C:¥Miniconda3
cd C:¥Miniconda3¥Scripts
wget https://github.com/ecell/ecell4-notebooks/archive/master.zip -OutFile master.zip
Expand-Archive master.zip
.¥jupyter-notebook.exe .¥master¥ecell4-notebooks-master¥Here we assume that you installed Miniconda(Python3.5) to ~/miniconda3
wget https://github.com/ecell/ecell4-notebooks/archive/master.zip
unzip master.zip
cd ecell4-notebooks-master
~/miniconda3/bin/jupyter-notebookHere are two extremely simple examples, See http://ecell4.readthedocs.org for more details on running E-Cell4.
Python 2.7.6 (default, Mar 22 2014, 22:59:56)
[GCC 4.8.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from ecell4.core import *
>>> sp = Species("B.A.C")
>>> print(sp.serial())
B.A.C
>>>
%matplotlib inline
import numpy
from ecell4 import *
with reaction_rules():
A + B == C | (0.01, 0.3)
y = run_simulation(
numpy.linspace(0, 10, 100), {'A': 60, 'B': 60}, solver='ode')
%matplotlib inline
from ecell4 import *
with species_attributes():
A | {'D': '1', 'location': 'M'}
surface = Sphere(ones() * 0.5, 0.5).surface()
obs = FixedIntervalTrajectoryObserver(1e-4)
run_simulation(
0.4, y0={'A': 10}, structures={'M': surface},
solver='spatiocyte', observers=obs, return_type=None)
viz.plot_trajectory(obs, interactive=False)
You can pull E-Cell4 docker image with docker pull ecell/ecell4.
This image includes E-Cell4 and its example Jupyter notebooks.
You need to set up your password or get a token to login there.
E-Cell4 docker image is based on jupyter/minimal-notebook.
See https://github.com/jupyter/docker-stacks/tree/master/minimal-notebook for more details about the docker run options.
You need to install IPython and create a hashed password before running the docker image. (Here we use miniconda IPython as an example.)
~/miniconda3/bin/ipython
Python 3.5.2 |Continuum Analytics, Inc.| (default, Jul 2 2016, 17:52:12)
Type "copyright", "credits" or "license" for more information.
IPython 5.1.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
In [1]: from IPython.lib.security import passwd
In [2]: passwd()
Enter password:
Verify password:
Out[2]: 'sha1:78345db65767:e156e28013d2f6741a042c44fcc12d21af7b7529'
And run the docker image with
docker run -d -p 8888:8888 ecell/ecell4 start-notebook.sh --NotebookApp.password='sha1:78345db65767:e156e28013d2f6741a042c44fcc12d21af7b7529'
You can see E-Cell4 example Jupyter notebooks after opening http://localhost:8888 and login.
First run the docker image with
docker run -d -p 8888:8888 ecell/ecell4
Then get the container name with docker ps command
docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
f2109e17eb55 ecell/ecell4 "tini -- start-notebo" 40 minutes ago Up 40 minutes 0.0.0.0:8888->8888/tcp peaceful_panini
And get the token for the container with the follwoing command, in the above case the container ID is peaceful_panini.
docker exec -it peaceful_panini jupyter notebook list
Currently running servers:
http://localhost:8888/?token=d8872dc7e0d5bd78882dcc326255f9848db24fd1a40711af :: /home/jovyan/work
In this case, the token is d8872dc7e0d5bd78882dcc326255f9848db24fd1a40711af
By using this token, you can login to the Jupyter Notebook service (http://localhost:8888).
This product is licensed under the terms of the GNU General Public License v2, See NOTICE for the software included in this product.
- Copyright (c) 2010-, RIKEN
All rights reserved.