Basic usage
Installation
There are multiple options:
Recent stable versions can be installed either with pip ($ pip install plottr)
or conda, using the conda-forge channel ($ conda install -c conda-forge plottr).
If you want to play with the most recent versions, or contribute to the development, it makes sense to install from github directly. In that case, clone the github repo, and install into the desired environment using the editable pip install.
Essential tools for inspecting data
There are a few different ways of easy data inspection using tools that come predefined with the basic plottr installation.
interactive use from IPython
loading data from a QCoDeS database
loading data from HDF5 files
In the following we briefly introduce all of these. We will use the autoplot app that comes with plottr by default.
Note
The examples below are also included in the notebook doc/examples/Plottr quickstart.ipynb
that comes with the plottr repository.
Interactive use
The easiest way to inspect data with plottr via the autoplot app is to use
the plottr.apps.autoplot.autoplot() function from IPython or Jupyter.
Loading QCoDeS data
TBD.
Loading data from HDF5
To easily load DataDict from an HDF5 file we can use the function
datadict_from_hdf5(). We can also store a DataDict
with datadict_to_hdf5().
For more information on DataDicts and how to work with them please see Data Formats
Live plotting measurement data
The autoplot app is able to live plot measurement by changing the “Refresh interval (s)” Option in the top toolbar. For a live monitoring of the entire data directory we can use the monitr app. We can start this app by running the following command in a terminal:
$ plottr-monitr <general-data-path>
All folders containing data will show up in the app and we can open an autoplot app for any already or incoming HDF5 data file. For more on how to use the app please see Plottr Apps