Along time diagnostics

Along time diagnostics are added using the add_time_stat() method.

Requested statistics will be computed at the provided frequency.

Add an along time diagnostic computing requested statistics at the
provided frequency.

Parameters
----------
name
    Name of the diagnostic.
field
    Field on which to compute statistics.
freq
    Frequency (day, pass, cycle or any pandas offset aliases [1]_)
stats
    List of statistics to compute (count, max, mean, median, min, std, var, mad)
stat_selection
    Selection clip used to invalidate (set to NaN) some bins.
    Valid conditions are:

        * count
        * min
        * max
        * mean
        * median
        * std
        * var
        * mad

    These clips are Python vector clips.
    Examples:

        * count :>= 10 && max :< 100
        * min :> 3
        * median :> 10 && mean :> 9
freq_kwargs
    Additional parameters to pass to pandas.date_range underlying function.

References
----------
.. [1] https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html        #timeseries-offset-aliases
.. [2] https://pandas.pydata.org/pandas-docs/stable/reference/api/        pandas.date_range.html

This kind of diagnostic is plotted as an along time plot.

An optional parameter, freq_kwargs, is also available.

It is a dictionary of additional parameters to pass to the pandas.date_range underlying function.

For instance:

ad.add_time_stat(
    name="Sigma 0 by day",
    freq="1H",
    freq_kwargs={"normalize": True},
    field=sig0,
    stats=["mean", "std", "var"],
)

Diagnostic setting

In the following example we are setting an along time diagnostic computing 3 statistics (mean, standard deviation and variance) at a daily frequency for the SIGMA0.ALTI field.

sig0 = ad.fields["SIGMA0.ALTI"]

ad.add_time_stat(
    name="Sigma 0 by day",
    freq="day",
    field=sig0,
    stats=["mean", "std", "var"],
)

ad.compute()

Diagnostic plotting

Along time statistics are plotted as along time plots.

CasysPlot requires a stat parameter to be given in order to know which statistic to display.

from casys import CasysPlot

plot = CasysPlot(
    data=ad,
    data_name="Sigma 0 by day",
    stat="mean",
)

plot.show()