@@ -16,7 +16,7 @@ As we do our own research, dadi is constantly improving. Our philosophy is to in
One of Python’s major strengths is its interactive nature. This is very useful in the ex-ploratory stages of a project: for examining data and testing models. If you intend to use dadi’s plotting commands, which rely on `matplotlib`, they you’ll almost certainly want to install IPython, an enhanced Python shell that fixes several difficulties with interactive plotting using `matplotlib`.
My preferred workflow involves one window editing a Python script (e.g. `script.py`) and another running an IPython session (started as `ipython -pylab`). In the IPython session I can interactively use dadi, while I record my work in `script.py`. IPython’s `%run script.py` magic command lets me apply changes I’ve made to script.py to my interactive session. (Note that you will need to reload other Python modules used by your script if you change them.) Once I’m sure I’ve defined my model correctly and have a useful script, I run that from the command line (python `script.py`) for extended optimizations and other long computations.
My preferred workflow involves one window editing a Python script (e.g. `script.py`) and another running an IPython session (started as `ipython --pylab`). In the IPython session I can interactively use dadi, while I record my work in `script.py`. IPython’s `%run script.py` magic command lets me apply changes I’ve made to script.py to my interactive session. (Note that you will need to reload other Python modules used by your script if you change them.) Once I’m sure I’ve defined my model correctly and have a useful script, I run that from the command line (python `script.py`) for extended optimizations and other long computations.
Note that to access dadi’s functions, you will need to `import dadi` at the start of your script or interactive session.
