Diive

New Features

- **Decoupling**: Added first version of decoupling code (`pkgs.analyses.decoupling.SortingBinsMethod`).
This allows the investigation of binned aggregates of a variable `z` in binned classes of
`x` and `y`. For example: show mean GPP (`y`) in 5 classes of VPD (`x`), separate for
10 classes of air temperature (`z`).


- **Time series plot**: `core.plotting.timeseries.TimeSeries` plots a simple time series. This will
be the default method to plot time series.

Changes

- **Critical days**: Several changes in `pkgs.flux.criticaldays.CriticalDays`:

- By default, daily aggregates are now calculated from 00:00 to 00:00 (before it was
7:00 to 07:00).
- Added parameters for specifying the labels for the x- and y-axis in output figure
- Added parameter for setting dpi of output figure
- Some smaller adjustments
- `pkgs.flux.co2penalty.CO2Penalty.plot_critical_hours`: 95% predicion bands are now
smoothed (rolling mean)

- **CO2 penalty**: (since v0.44.0 renamed to NEP penalty)

- Some code refactoring in `pkgs.flux.co2penalty.CO2Penalty`, e.g. relating to plot appearances

BinFitterBTS

- `pkgs.fits.binfitter.BinFitterBTS` fits a quadratic or linear equation to data.
- This is a refactored version of the previous `BinFitter` to allow more options.
- Implemented `pkgs.fits.binfitter.PlotBinFitterBTS` for plotting `BinFitterBTS` results
- `PlotBinFitterBTS` now allows plotting of confidence intervals for the upper and
lower prediction bands
- The updated `BinFitterBTS` is now implemented in `pkgs.flux.criticaldays.CriticalDays`

Example of updated `BinFitterBTS` as used in `CriticalDays`

It is now possible to show confidence intervals for the upper and lower prediction bands.

Other

- `core.plotting.heatmap_datetime.HeatmapDateTime` now accepts `figsize`
- When reading a file using `core.io.filereader.ReadFileType`, the index column is now
parsed to a temporarily named column. After reading the file data, the temporary column
name is renamed to the correct name. This was implemented to avoid duplicate issues
regarding the index column when parsing the file, because a data column with the same
name as the index column might be in the dataset.

Bugfixes

- Fixed bug in `pkgs.gapfilling.randomforest_ts.RandomForestTS`: fallback option for
gap-filling was never used and some gaps would remain in the time series.

CO2 Penalty

- New analysis: `pkgs.flux.co2penalty.CO2Penalty` calculates the CO2 penalty as
the difference between the observed co2 flux and the potential co2 flux modelled
from less extreme environmental conditions.




VPD Calculation

- New calculation: `pkgs.createvar.vpd.calc_vpd_from_ta_rh` calculates vapor pressure
deficit (VPD) from air temperature and relative humidity

Fixes

- Fixed: `core.plotting.cumulative.CumulativeYear` now shows zero line if needed
- Fixed: `core.plotting.cumulative.CumulativeYear` now shows proper axis labels

Critical Days

- New analysis: `pkgs.flux.criticaldays.CriticalDays` detects days in y that are
above a detected x threshold. At the moment, this is implemented to work with
half-hourly flux data as input and was tested with VPD (x) and NEE (y). In the
example below critical days are defined as the VPD daily max value where the daily
sum of NEE (in g CO2 m-2 d-1) becomes positive (i.e., emission of CO2 from the
ecosystem to the atmosphere).

Optimum Range Detection

- New analysis: `pkgs.analyses.optimumrange.FindOptimumRange` finds the optimum for a
variable in binned other variable. This is useful for e.g. detecting the VPD
range where CO2 uptake was highest (=most negative).

Cumulative and Anomaly Plots

- New plot: `core.plotting.cumulative.CumulativeYear` plots cumulative sums per year
- New plot: `core.plotting.bar.LongtermAnomaliesYear` plots yearly anomalies in relation to a reference period
- Refactored various code bits for plotting