SirIsaac depends on the following packages:
- Python 3
- Scipy
- Numpy
- Matplotlib
- SloppyCell (https://github.com/GutenkunstLab/SloppyCell)
There exist several relatively simple ways to install the first four packages above at once, including
- Anaconda: http://www.anaconda.com
- Sage: http://www.sagemath.org
These systems also have the added benefit of coming prepackaged with other useful software such as iPython and Jupyter.
SirIsaac depends on the latest version of SloppyCell, available on GitHub. In the simplest case, you can install with two steps. First download the git repository by running
git clone https://github.com/GutenkunstLab/SloppyCell.git
which will create a folder named SloppyCell
in the current directory. Next, install SloppyCell by running setup.py. The easiest way to do this is using pip
:
pip install -e SloppyCell/
SirIsaac is similarly available as a git repository on GitHub. To install, first download by running
git clone https://github.com/EmoryUniversityTheoreticalBiophysics/SirIsaac.git
which will create a folder named SirIsaac
in the current directory. Next, install SirIsaac by running setup.py. The easiest way to do this is using pip
:
pip install -e SirIsaac/
A basic suite of unit tests can be run by moving into the SirIsaac directory and running
python -m unittest
This should take about a minute to run. Note that there may be lots of warnings and compiler optimization messages (we're working on it...), but if you see something like the following then all tests have passed:
---------------------------------------------
Ran 9 tests in 56.687s
OK
To further help you get up and running, code to fit and analyze a simple example dataset using SirIsaac is provided in two formats: a Jupyter iPython notebook (simpleExample.ipynb) and a simple Python script (simpleExample.py). The iPython notebook opens in a web browser and includes plots in an interactive format. To open the .ipynb file, run:
jupyter notebook simpleExample.ipynb
To run the .py file in iPython at the command line, run:
ipython --pylab
%run simpleExample.py
plt.show()
To run parameter fitting in parallel, you will need to install mpi4py, which further depends on an installation of mpi (often OpenMPI, depending on your operating system). For more information about installing mpi4py, see here: https://pypi.org/project/mpi4py/
Following are notes from one user detailing OpenMPI installation—these are somewhat outdated (using Python 2.7) but could potentially be useful:
OpenMPI Installation
Download the latest version(4.1.1) from https://www.open-mpi.org/software/ompi/v4.1/
Refer the Building MPI from sources section for the installation.
Another source for OpenMPI Installation - https://gist.github.com/mrosemeier/088115b2e34f319b913a
Other Installations that were done for Ubuntu
pip install mpi4py
sudo apt-get install python-dev \
build-essential libssl-dev libffi-dev \
libxml2-dev libxslt1-dev zlib1g-dev \
sudo apt install libopenmpi-dev
sudo apt-get install python2.7-dev
sudo apt-get install build-essential
sudo apt-get install gcc
sudo apt-get install python-dev gcc
sudo apt-get install python2-dev build-essential gcc libpq-dev
sudo apt-get install libblas-dev libatlas-base-dev
sudo apt-get install build-essential gcc gfortran git
sudo apt install gfortran