Troubleshooting#
Numba#
Help for troubleshooting specifically numba is provided at at this readthedocs page
Pip Version#
If an error message appears after trying to run pip install autolens
first make sure you are using
the latest version of pip.
pip install --upgrade pip
pip3 install --upgrade pip
Pip / Conda#
If you are trying to install via pip but still haing issues, we recommend you try to install via conda instead, or visa versa.
Support#
If you are still having issues with installation, please raise an issue on the autolens_workspace issues page with a description of the problem and your system setup (operating system, Python version, etc.).
Current Working Directory#
PyAutoLens scripts assume that the autolens_workspace
directory is the Python working directory. This means
that, when you run an example script, you should run it from the autolens_workspace
as follows:
cd path/to/autolens_workspace (if you are not already in the autolens_workspace).
python3 examples/model/beginner/mass_total__source_lp.py
The reasons for this are so that PyAutoLens can:
Load configuration settings from config files in the
autolens_workspace/config
folder.Load example data from the
autolens_workspace/dataset
folder.Output the results of models fits to your hard-disk to the
autolens/output
folder.
If you have any errors relating to importing modules, loading data or outputting results it is likely because you
are not running the script with the autolens_workspace
as the working directory!
Matplotlib Backend#
Matplotlib uses the default backend on your computer, as set in the config file:
autolens_workspace/config/visualize/general.yaml
If unchanged, the backend is set to ‘default’, meaning it will use the backend automatically set up for Python on your system.
general:
backend: default
There have been reports that using the default backend causes crashes when running the test script below (either the code crashes without a error or your computer restarts). If this happens, change the config’s backend until the test works (TKAgg has worked on Linux machines, Qt5Agg has worked on new MACs). For example:
general:
backend: TKAgg