Installing scikit-beam¶
For Python Novices¶
Installation is simple on Windows, OSX, and Linux, even for Python novices.
1. Get Scientific Python¶
To get started with Python on any platform, download and install Anaconda. It comes with the common scientific Python packages built in.
2. Install scikit-beam¶
TODO: make this actually work!
Open a command prompt. On Windows, you can use the “Anaconda Command Prompt” installed by Anaconda or Start > Applications > Command Prompt. On a Mac, look for Applications > Utilities > Terminal. Type these commands:
conda update conda
conda config --add channels scikit-beam
# to install the latest stable release
conda install scikit-beam
The above installs scikit-beam and all its requirements. Our tutorials also use the IPython notebook. To install that as well, type
conda install ipython-notebook
3. Try it out!¶
Finally, to try it out, type
ipython notebook
This will automatically open a browser tab, ready to interpret Python code. To get started, check out the links to tutorials at the top of this document.
More Information for Experienced Python Users¶
We strongly recommend using conda install scikit-beam, as described above, but pip is also supported.
Essential Dependencies:
python (both 2 and 3 are supported)
setuptools
six
numpy
Optional Dependencies:
scipy
scikit-image
xraylib
lmfit
netcdf4
git clone https://github.com/scikit-beam/scikit-beam
pip install -e scikit-beam
Updating Your Installation¶
The code is under active development. To update to the latest stable release, run this in the command prompt:
conda update -c scikit-beam scikit-beam
The code is under active development. To update to the latest development release, run this in the command prompt:
conda update -c scikit-beam/channels/dev scikit-beam