Have a look at the data

Note

This chapter would benefit from some more love and care. Any help on that would be highly appreciated.

Here are some examples how to get a peak at the data. If we need an interactive plot of the raw-data, we can use the plotutils.raw_plot function. If we would like to see some statistics for some of the cycles, the plotutils.cycle_info_plot is your friend. Let´s start by importing cellpy and the plotutils utility:

import cellpy
from cellpy.utils import plotutils

Let´s load some data first:

cell = cellpy.get("../testdata/hdf5/20160805_test001_45_cc.h5", mass=0.8)

Here we used the convenience method cellpy.get to load some example data. If everything went well, you will see an output approximately like this:

(cellpy) - Making CellpyCell class and setting prms
(cellpy) - Loading cellpy-file: ../testdata/hdf5/20160805_test001_45_cc.h5
(cellpy) - Setting mass: 0.8
(cellpy) - Creating step table
(cellpy) - Creating summary data
(cellpy) - assuming cycling in anode half-cell (discharge before charge) mode
(cellpy) - Created CellpyCell object

If you have holoviews installed, you can conjure an interactive figure:

plotutils.raw_plot(cell)

Sometimes it is necessary to have a look at some statistics for each cycle and step. This can be done using the cycle_info_plot method:

fig = plotutils.cycle_info_plot(
    cell,
    cycle=3,
    use_bokeh=False,
)

Note

If you chose to work within a Jupyter Notebook, you are advised to try some of the web-based plotting tools. For example, you might consider installing holoviz suite.