Changelog • mqor

mqor 0.0.12

If tasked with assuming the MQI parameters to use, summarise_mqo_stats() will now print these as a message to alert a user which parameters have been selected.
show_annotations now includes the pollutant and year.

plot_mqi_bars(show_annotations = TRUE) will now place legends and annotations in appropriate places.

plot_mqi_report() has gained show_annotations.
plot_mqi_bars() now has a line type legend (for static plots) and a more descriptive plot annotation (for interactive plots) to better describe the horizontal annotations being shown.
summarise_mqo_stats() now validates that only a single year of data has been provided, and returns the input year of data in its params.
Various plotting functions now verify that stats and stats2 have the same year and pollutant.
The fontsize argument within gp now controls the size of annotations when interactive = TRUE.

Fixed an issue determining the resolution of input data for automatic parameter identification.
plot_comparison_bars() now uses RMSU0√(1+β²) as legend labels rather than RMSU0*, reflecting changes in the CEN specification.
Annotation size has been reduced to better fit annotations on most plots.
plot_mqi_bars() and plot_comparison_bars() now check for x-axis label overlaps and will remove overlapping axis labels.

The default_params have been updated based on outcomes from Task 3 of the European Standard on modelling quality objectives for assessment of ambient air (EC-ENV/2024/OP/0036).
The Shiny GUI can now use the demo_shortterm and demo_longterm datasets by selecting “DEMO” on the first screen.
The Shiny GUI now shows the version of MQOR in the navigation bar. This links to the MQOR change log.
When show_annotations = TRUE, the MQOR version is also included as an annotation.

[BREAKING] stats_shortterm and stats_longterm have been renamed stats and stats2 wherever they appear. Long- and short-term data will be automatically determined by each function and used appropriately. While this may break existing code, future code will be more streamlined for the user who can simply provide short- and long-term statistics in any order.
Most plots have gained the show_annotations argument, which allows for the input parameters and complementary indicators to be appended to a greater number of MQI evaluation plots, and for it to be disabled in plot_mqi_scatter().

Filtering options have moved around to be in a more sensible order.
The existing temporal filtering options are now exclusive to short-term data.
A user can now select whether they want to use their uploaded long-term data or have the app time-average their short-term data.
If the user selects to time-average the short-term data, they can additionally apply an independent month filter on the short-term data. This allows for seasonal averages to be calculated for pollutants like ozone.

Fixes from resolving disparities in the technical specification:

vec_ti_cor() is now calculated using the correct formula.
plot_mqi_scatter() will now put TI_CRMSE on the correct segment of the plot (the inverse of mqor 0.0.4).

vec_ti_crmse() is now calculated using vec_crmse() and vec_rmsu() instead of vec_mqi() and vec_pi_bias().
plot_mqi_scatter() will now put TI_CRMSE on the correct segment of the plot.
plot_mqi_scatter() will now extend the extents of the target diagram if either of |TI_CRMSE| or |TI_BIAS| are greater than 2.

default_params has been updated based on recent revisions of the technical document.
Web documentation has been significantly expanded.

The units of reference values in default_params now vary, and the dataset now has a rv_unit column to correctly label them.

read_delta_resource() will now ignore the case of startup.ini column headers.

Development version as part of the European Standard on modelling quality objectives for assessment of ambient air (EC-ENV/2024/OP/0036, European Commission)