Visualising the results¶
After running calkulate()
(or calibrate()
and solve()
) on your data, Calkulate contains some plotting functions to help visualise the results. More will be added in time, and contributions are welcome!
Calibrated titrant_molinity
¶
fig, ax = calk.plot.titrant_molinity(
data, xvar=None, show_bad=True, show_batches=True, figure_fname=None,
)
The required argument data
is the metadata table as a pandas DataFrame or Calkulate Dataset.
Optional inputs:
xvar
: name of column to use as the x-axis variable.show_bad
: whether or not to show values wheredata.reference_good == False
.show_batches
: whether or not to show batch-averagedtitrant_molinity
values.figure_fname
: if provided, save figure to this filename.
Measured − certified alkalinity_offset
¶
fig, ax = calk.plot.alkalinity_offset(
data, xvar=None, show_bad=True, show_batches=True, figure_fname=None,
)
The required argument data
is the metadata table as a pandas DataFrame or Calkulate Dataset.
Optional inputs:
xvar
: name of column to use as the x-axis variable.show_bad
: whether or not to show values wheredata.reference_good == False
.show_batches
: whether or not to show batch-averagedtitrant_molinity
values.figure_fname
: if provided, save figure to this filename.