Getting Started¶
The galileoQC package is run from a Jupyterlab notebook. You should create a virtual working environment (called whizz in this documentation) with python venv.
Installation¶
To use galileoQC, first install it into your whizz environment using pip (conda installations of galileoQC can work but conda has not been tested as fully as pip):
(whizz) $ pip install galileoQC
Then start up a jupyterlab notebook. For more information about jupyterlab, see [1] . The Jupyterlab-Desktop app [2] also works.
For more information on installation see Install Details.
Session Setup¶
In a jupyterlab notebook, set up your session with the following commands.
Firstly import the necessary Python packages …
from pathlib import Path # useful for file names
%matplotlib widget # needed to, for example, zoom into plots
… then import galileoQC …
import galileoQC as qc
… and finally set the path to your field and plan data. This might look something like this:
# Setup the path to the acquired data, ...
data_root = r'.source/tutorials/'
dx = Path(data_root + r'CanobieData/Canobie.xyz')
dh = dx.with_suffix('.hdf5')
# ..., and plan data.
plan_root = data_root
px = Path(plan_root + r'CanobieData/CanobiePlan.xyz')
ph = px.with_suffix('.hdf5')
The variables dx, dh, px and ph are often used to represent the four key data filenames. Of course, you can use any variable names for your projects but it is worth noting these because you will see them occasionally in the documentation.
If you want to see how to use galileoQC, go to Tutorials and follow along with the examples. You can also download the python tutorial notebooks and example data from github and experiment with the functions yourself.
Now you are ready to QC your data!